ORMS Today February 2016

GRAND CHALLENGES III: Opportunities in security

February 2016

Volume 43 • Number 1 ormstoday.informs.org

Internet of Things What’s next? Sustainable business models

Cognitive computing The power of automated customer knowledge

Analytics & O.R. conference Orlando event to focus on real-world solutions

Vehicle routing:

Driving transformation VR software delivers in response to higher expectations and market demands

Contents February 2016 | Volume 43, No. 1 | ormstoday.informs.org

28 On the Cover Special, smart delivery Biennial survey of vehicle routing software: Minimizing transportation costs while satisfying feasibility constraints.

Image © mihtiander| www.123rf.com

de partm e nt s

F e at ure s 28

34

36

O.R. opportunities in security

By David P. Morton and Suvrajeet Sen Third in a series of articles on NAE’s “Grand Challenges” focuses on O.R.’s potential catalyst role in security concerns regarding infrastructure, nuclear terror and cyberspace.

In praise of cognitive computing

By Guy Mounier What does cognitive computing deliver that makes it superior to previous generations of analytics and why should we embrace it?

Three words: automated customer knowledge.

Internet of Things: What’s next?

2 | ORMS Today

By Tayfun Keskin, Fehmi Tanrısever and Haluk Demirkan Are companies ready for billions of everyday objects to join the Internet? Realigning parties in supply chains and reinforcing new business links demands sustainable business models.

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February 2016

6 Inside Story

8 President’s Desk

10 Issues in Education

12 INFORMS in the News

14 Newsmakers

18 INFORMS Initiatives

20 First Person

22 PuzzlOR

24 Forum

26 Viewpoint

62 Industry News

63 Classifieds

64 ORacle

14 ormstoday.informs.org

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February 2016 | Volume 43, No. 1 | ormstoday.informs.org

INFORMS Board of Directors

President Edward H. Kaplan, Yale University President-Elect Brian Denton, University of Michigan

Past President L. Robin Keller, University of California, Irvine

Secretary Pinar Keskinocak, Georgia Tech

Treasurer Sheldon N. Jacobson, University of Illinois

Vice President-Meetings Ronald G. Askin, Arizona State University Vice President-Publications Jonathan F. Bard, University of Texas-Austin

40

Co m puting 40

Vice President- Esma Gel, Arizona State University Sections and Societies

Vice President- Marco Lüebbecke, Information Technology RWTH Aachen University

Vice President- Jonathan Owen, CAP, General Motors Practice Activities Vice President- Grace Lin, International Activities Institute for Information Industry

Vice President-Membership Susan E. Martonosi,

Professional Recognition Harvey Mudd College

Vice President-Education Jill Hardin Wilson, Northwestern University

Software survey: vehicle routing

By Randolph Hall and Janice Partyka Higher expectations drive transformation: Biennial survey of vehicle routing software reveals many innovations in response to market demands. Side-by-side comparison of 25 packages.

Vice President-Marketing, Laura Albert McLay, Communications and Outreach University of Wisconsin-Madison Vice President-Chapters/Fora Michael Johnson, University of Massachusetts-Boston

Editors of Other INFORMS Publications

Decision Analysis Rakesh K. Sarin, University of California, Los Angeles

Editor’s Cut Anne G. Robinson, Verizon Wireless

Information Systems Research Ritu Agarwal, University of Maryland I NFORMS Journal on Computing David Woodruff, University of California, Davis

n ews

INFORMS Online Kevin Geraghty, 360i INFORMS Transactions Jeroen Belien, KU Leuven on Education

Interfaces Srinivas Bollapragada, General Electric Global Research Center

Management Science Teck-Hua Ho, National University of Singapore Office of the Deputy President (Research and Technology) Manufacturing & Service Christopher S. Tang, Operations Management University of California, Los Angeles

49 Analytics conference

54 Subdivision awards

52 International conference

61 People

Marketing Science K. Sudhir, Yale University

61 Meetings

Mathematics of Operations J. G. “Jim” Dai, Cornell University Research

52 Roundtable retreat

53 Marketing makeover

Operations Research Stefanos Zenios, Stanford University

Organization Science Zur Shapira, New York University

Service Science Paul P. Maglio, University of California, Merced

49

Strategy Science Daniel A. Levinthal, Wharton School, University of Pennsylvania

Transportation Science Martin Savelsbergh, Georgia Institute of Technology

Tutorials in Operations J. Cole Smith, University of Florida Research

INFORMS Office • Phone: 1-800-4INFORMS

Executive Director Melissa Moore

Headquarters

4 | ORMS Today

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February 2016

INFORMS (Maryland) 5521 Research Park Dr., Suite 200 Catonsville, MD 21228 USA Tel.: 443.757.3500 Fax: 443.757.3515 E-mail: informs@informs.org

ormstoday.informs.org

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Inside Story

Peter Horner, editor

peter.horner@mail.informs.org

OR/MS Today Advertising and Editorial Office

In search of security

Send all advertising submissions for OR/MS Today to: Lionheart Publishing Inc. 506 Roswell Street, Suite 220, Marietta, GA 30060 USA Tel.: 888.303.5639 • Fax: 770.432.6969

President John Llewellyn, ext. 209 john.llewellyn@mail.informs.org

Given the endless madness in the world that’s reported nonstop in the mainstream media, amplified by social media and reflected in all manner of wild and crazy ways by the respective U.S. presidential primary campaigns, it’s no wonder people are running scared and looking for more “security.”

While many of the fears are baseless, some are not. Financial fraud and identity theft are real, fast-growing problems both domestically and abroad. Outdated, crumbling or vulnerable transportation, telecommunication and other infrastructure – and the chaos that may ensue should a major network go down in our interconnected world – can’t be ignored.

Terrorism is an international plague on the planet, and the possibility of a nuclear attack remains a threat.

No, this isn’t a cheap attempt to instill even more fear in an already jittery public.

On the contrary, it’s a means to introduce the third in our series of articles on “O.R. as a Catalyst for Grand Engineering Challenges.” Based on a report to the National Science Foundation, the articles detail how operations research can address, and hopefully help solve or mitigate, many of the grand challenges facing the United States and the world today. Previous articles in the series presented a summary of the report (August 2015), as well as a focused article on the topic of “sustainablity” (December 2015). This month’s grand challenge: “security.”

In their article “Opportunities in security” (page 28), David P. Morton of Northwestern University and Suvrajeet Sen of the University of Souther n Califor nia discuss O.R.’s potential role in restoring and improving urban infrastructure, preventing nuclear terror and securing cyberspace. Sen led a team of

prominent O.R. scholars and practitioners who wrote the report to the NSF. Elsewhere in this issue, you’ll find our biennial survey of vehicle routing software (“Higher expectations drive transfor mation,” page 40) in which co-authors Randolph Hall and Janice Partyka describe some of the many innovations that are moving the VR software space forward in response to market demands. Hall is vice president of research at the University of Southern California, as well as professor in USC’s Epstein Department of Industrial and Systems Engineering. Partyka is principal of JGP Services, a consulting group that helps companies with product strategy, market research and communications.

For their article, Hall and Partyka interviewed several representatives of VR software vendors, including Cyndi Brandt of Omnitracs Roadnet, who says, “Routing used to be just about creating a plan, but now it is about execution.” Along those lines, proof of delivery, tracking and compliance are considered supplemental needs that demand system integration.

The VR software survey package includes side-by-side comparisons of 25 products along with a directory of 22 vendors.

In other news, INFORMS recently launched a website called “Analytics Education One Stop Shop” that offers a comprehensive look at university analytics programs.

“Whether you’re a program director, professor, aspiring student or business leader, you’ll find loads of help and information that will guide you,” says Diego Klabjan, a professor at Northwestern University and chair of the INFORMS University Analytics Program Committee. For more on the program, see “INFORMS Initiatives” (page 18) or visit http://education.informs.org/. ORMS — Peter Horner, editor peter.horner@mail.informs.org

6 | ORMS Today

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February 2016

Editor Peter R. Horner peter.horner@mail.informs.org Tel.: 770.587.3172

Assistant Editor Donna Brooks

Contributing writers/editors Douglas Samuelson, Barry List, Matt Drake, John Toczek

Art Director Alan Brubaker, ext. 218 alan.brubaker@mail.informs.org

Online Projects Manager Patton McGinley, ext. 214 patton.mcginley@mail.informs.org

Assistant Online Projects Manager Leslie Proctor, ext. 228 leslie.proctor@mail.informs.org

Advertising Sales Managers Sharon Baker sharon.baker@mail.informs.org Tel.: 813-852-9942 Aileen Kronke, ext. 212 aileen@lionhrtpub.com

Reprints Kelly Millwood, ext. 215 kelly.millwood@mail.informs.org

OR/MS Today Committee James Cochran, chairman

INFORMS Online http://www.informs.org

Lionheart Publishing Online http://www.orms-today.org OR/MS Today (ISSN 1085-1038) is published bimonthly by the Institute for Operations Research and the Management Sciences (INFORMS). Canada Post International Publications Mail (Canadian Distribution) Sales Agreement No. 1220047.

Deadlines for contributions: Manuscripts and news items should arrive no later than six weeks prior to the first day of the month of publication. Address correspondence to: Editor, OR/MS Today, 506 Roswell Street, Suite 220, Marietta, GA 30060. The opinions expressed in OR/MS Today are those of the authors, and do not necessarily reflect the opinions of INFORMS, its officers, Lionheart Publishing Inc. or the editorial staff of OR/MS Today.

Membership subscriptions for OR/MS Today are included in annual dues. INFORMS offers non-member subscriptions to institutions, the rate is $62 USA, $79 Canada & Mexico and $85 all other countries. Single copies can be purchased for $10.50 plus postage. Periodicals postage paid at Catonsville, MD, and additional mailing offices. Printed in the United States of America. POSTMASTER: Send address changes to OR/MS Today, INFORMS-Maryland Office, 5521 Research Park Dr., Suite 200, Catonsville, MD 21228. OR/MS Today copyright ©2016 by the Institute for Operations Research and the Management Sciences.

All rights reserved.

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President’s Desk

‘Me m

b e r-in- C h ie f Me m o’

Ed Kaplan

INFORMS President president@informs.org

Let’s do stuff!

The Internal Revenue Service defines an association as “… a group of persons banded together for a specific purpose,” and INFORMS is certainly that. But we are so much more, as our members voluntarily come together to meet our common needs, explore and address our collective problems, and strive toward our shared goals.

Yet to remain clear (and even better, excited) about what we are about, it behooves us to take a step back and ask where we are heading, and even raise the proverbial question of what we want to be when we grow up (in spite of our field having existed for about three-quarters of a century dating back to its military roots). Sorting out “that vision thing” is more than just a feel-good exercise, for having agreed-upon strategic goals establishes a framework for activities and operations that move us in the right direction.

Considerations such as these led the INFORMS board of directors to embark on a new strategic planning process over the past year with the hope of developing a mission statement and aspirational goals that reflect the breadth of our membership.With facilitation from Glenn Tecker, an expert in governance of voluntary non-profit associations, the board took on this task at its summer and fall 2015 meetings. The resulting plan was formally considered in a motion at the winter 2016 meeting held just before Winter Storm Jonas shut down the East Coast. Call it the Jonas Bonus. Ladies and gentlemen, with the unanimous approval of the board, we have a plan.

We begin with the core purpose of INFORMS, which is: advance the science and practice of quantitative decision-making via operations research and analytics. Next is the mission statement of our organization: INFORMS promotes best practices and advances in operations research, management science and analytics to improve operational processes, decision-making and outcomes. In all that we 8 | ORMS Today

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February 2016

Operations research is not a spectator sport.

do, INFORMS will strive to reflect our three core values of integrity, innovation and equal opportunity.

Then comes the heart of our plan as embodied in the four goals, which are: 1. INFORMS will identify, recognize, and promote the work of our members to show the value their science and practice brings to society.

2. Decision-makers will have access to, and use, innovative technologies and methodologies to transform visions, tasks or responsibilities into better choices, services and products to achieve better outcomes.

3. Organizations will identify operations research and analytics as core components of success and institutionalize their input as part of their decision-making processes.

4. Society: Operations research and analytics will advance society and make the world a better place.

There is logic to these goals. First and foremost, INFORMS exists to serve our members, and what better service than to promote our research and practice? By doing so, we serve to promote the operations research profession, its accomplishments and its promise. This in many ways is the “normal” goal of academic and professional societies, and remains the starting point of all we should do.

But what makes us different from our sister quantitative fields? While the main purpose of science is understanding phenomena, real or abstract, our focus on mathematical modeling is ultimately driven by the desire to help make better decisions. So, while we can (and should) talk and write about this distinguishing feature of our work, what we really should strive for is to put our concepts, mindset and tools in the hands of those making important decisions.

INFORMS can and should do more to help make this happen.

Now, where do we find decision-makers? Most of the important ones reside within organizations, which makes targeting organizations to institutionalize the best of what we have to offer a challenge worthy of a goal. Of course we have been somewhat active in promoting operations research broadly defined to organizations for some time; the INFORMS Prize comes to mind. But again, we can do much more in this area, and we will.

Finally, what is the biggest organization of them all? The world and society at large.

At the summer 2015 board meeting, Glenn Tecker led us through an exercise where, working in small groups, board members and senior INFORMS staff imagined newspaper headlines involving INFORMS they would most like to see in 10 years’ time.The responses were truly exciting: O.R. and analytics help tailor successful personalized treatments for cancer; organizations in all sectors are able to better use limited resources for the benefit of humanity; two INFORMS authors share the Nobel Peace Prize for humanitarian logistics.We can help with the major problems of the world, and we should strive to make the world a better place.

Future columns will revisit each of our four goals to discuss evolving plans, ongoing activities and ways you can get involved with each. Operations research, analytics included, is an amazing and exciting field of study and practice, with opportunities for all ranging from the most theoretically inclined to practitioners in the field (or the weeds!).

It is a profession we should all be immensely proud of.The world is an exciting place, and operations research is not a spectator sport. So c’mon INFORMS, let’s do stuff! ORMS ormstoday.informs.org

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Issues in Education

Matthew J. Drake drake987@duq.edu

How to use cases in the undergraduate classroom This column is based on a presentation that I gave at the 2015 INFORMS Annual Meeting in Philadelphia. I would like to thank Mike Veatch from Gordon College for inviting me to present in the terrific session that he organized. I have written in this column before about writing cases for widespread adoption (see “The Case for Writing Cases� in the August 2012 issue of OR/MS Today), but this time I am sharing some strategies for using cases in the classroom.

Teaching cases have been a mainstay in the MBA classroom for decades. Proponents of using cases often cite several main pedagogical benefits that cases possess over the traditional lecture method.

Cases do a good job simulating a complex decision environment similar to the ones that students will face in their professional careers. Cases require students to separate relevant information from irrelevant information. Cases also require students to synthesize different concepts and analytical techniques to develop holistic recommendations for the decision-maker.

While case usage is ubiquitous for master’s students, they are somewhat less commonly employed in undergraduate classrooms. Undoubtedly this is at least partially due to the fact that many undergraduate courses are designed to simply introduce concepts and techniques rather than to give the students much of a chance to apply them. Indeed, if students are being introduced to an entire field of study for the first time, it can be somewhat unreasonable to ask them to analyze an integrated case study. That does not, however, mean that cases cannot be used effectively in any form at the undergraduate level. All of the major case publishers and clearinghouses such as Harvard, Ivey, Darden and The Case Centre publish cases geared toward undergraduates or incoming MBA students. Several case books containing shorter cases that are 10 | ORMS Today

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February 2016

they were MBA students.This is especially appropriate for advanced, upper-level undergraduate courses, where the distinction between undergraduate and graduate students is often blurred. I usually assign these cases as out-of-class group homework assignments that the students com-

Cases do a good job simulating a complex decision environment similar to the ones that students will face in their professional careers.

more appropriate for undergraduates have recently been published as well.

I have successfully introduced cases into my undergraduate courses in each of the following three ways: 1. Discussion only. Another benefit of cases is that they introduce students to the challenges facing one particular company or industry. Some cases are written in such a way that they do not require any sophisticated analysis and just ask students to consider the situation and generate and evaluate possible strategies.These cases are prime candidates to be used solely as a basis of class discussion. Usually I ask students to read the case before coming to class (and give them a short assignment requiring them to answer a few questions about the case to motivate them to read it), and then we discuss the case in class for 20 to 30 minutes. The teaching notes are usually a good source of possible discussion questions to pose to the class.

2. Instructor presents model. Many cases require a substantial amount of modeling and analysis, but instructors may not want to allocate the requisite class time that students need to complete the entire case analysis. In these situations I often will ask the students to read the case before coming to class (and give them the same short reading assignment discussed above). Then in class I ask them to summarize the decision scenario, and I lead them through the required quantitative and decision analysis. This allows me to still introduce them to the case, but it cuts down on the class time that I need to devote to its coverage.

3. Students conduct full analysis. Some cases are so rich and important that I find it beneficial to have the students complete the entire case analysis as they would if

plete over the course of two weeks or so.

Once the students have submitted their work, I spend anywhere from 20 to 60 minutes in class discussing some of the additional issues and extension questions from the teaching notes with them.

Of course, these are not the only ways that instructors can incorporate cases into the undergraduate classroom, but I have successfully used all three of these methods in various classes. If an instructor is new to using cases in the classroom, I recommend that he or she start slow and introduce one case per course at a time. It is usually not necessary to redesign a course completely in one semester or quarter and introduce three or four new cases, especially if the instructor is not experienced with using them. As the instructor builds confidence, he or she can add another case the next time the course is taught if the material warrants it.

If you have unique experiences or strategies for using cases in OR/MS classes at all levels, I encourage you to submit them to an upcoming special issue of INFORMS Transactions on Education that I am guest editing. The call for papers will be published soon, and the deadline for initial submissions is Dec. 31. Please feel free to email me for details if you have not received the call for papers or if you have any other questions. ORMS Matt Drake (drake987@duq.edu) is the Harry W. Witt Faculty Fellow in Supply Chain Management and associate professor in the Palumbo-Donahue School of Business at Duquesne University in Pittsburgh, Pa.

ormstoday.informs.org

What’s Your StORy? Kayse Lee Maass PhD candidate, Department of Industrial and Operations Engineering (IOE), University of Michigan INFORMS member since at least 2012 What prompted you to enter this field? Why? For as long as I can remember, I knew I wanted to pursue a career related to applied math. However, it was not until I was an undergraduate mathematics and physics major that I learned about operations research.

In my senior year, I was a project manager for an OR course in which our class optimized the food-packing process for Feed My Starving Children and helped increase the number of meals packed by 45%. I loved seeing how valuable analytic skills can be in the decision-making process and felt empowered to use my skills to benefit society. I promptly applied to related PhD programs and could not be happier with my decision. I am now very passionate about raising awareness so that other students can learn about the field well before they graduate from college!

What has been your best INFORMS experience thus far?

The annual conferences are always a highlight of my year. I’ve enjoyed getting to know other researchers from around the world and being a part of the smaller communities within INFORMS, such as the Section on Location Analysis (SOLA), the Health Applications Society (HAS), and WORMS. Additionally, the WORMS luncheon and the student chapter officer breakfast are also favorites of mine.

If you could choose anyone, who would you pick as your mentor?

I have been very fortunate to have many excellent mentors already, including my undergraduate advisor, Patrice Conrath (who introduced me to the field) and my PhD advisor, Mark Daskin. I also participated in the Forum for Women in OR/MS (WORMS) mentorship program at the INFORMS Annual Meeting this year and had a great time discussing how to navigate the academic job search and the transition to life as a junior faculty member with Hiba Baroud, my WORMS mentor. I highly encourage anyone interested to get involved (either as a mentor, mentee, or both) in the WORMS mentorship program.

More questions for Kayse?

Ask her in the Open Forum on INFORMS Connect!

http://connect.informs.org

INFORMS in the News

Women & STEM jobs, CAP, curbing malaria Over the past year operations research, management science and analytics have been showing up in important rankings. In March 2015 U.S. News & World Report named operations research No. 4 in its list of best business jobs, No. 8 in its list of best STEM jobs and No. 20 in its list of 100 best jobs. Pretty impressive! More recently, as you’ll see below, the profession made two USA Today rankings: O.R. made the list of top five best jobs for women and management science made the list of 25 best STEM majors.

Visit the INFORMS Newsroom at www.informs.org for additional news about analytics and INFORMS press releases about intriguing scholarship appearing in INFORMS journals.

Following are excerpts from INFORMS in the news.

O.R. Makes List of Top 5 STEM Professions Employing Women Have a look for yourself at the five jobs with the highest percentage of women working in the profession ...

3. Operations Research Analysts • Percentage of women employed: 55.4 percent • Mean annual wage: $82,940 These analysts use mathematical and analytical methods to help organizations solve complex problems, from using statistics to help inform decisions to gathering input from employees. Most operations research analysts have master’s degrees in operations research, engineering, computer science, mathematics or physics. Some entry-level positions are open to those with bachelor’s degrees.

This field only has 55.4 percent female workers, but that is still a considerable amount when looking at women in STEM. The reason for this, says analyst Laurie M. Orlov in her article on cio.com, is that jobs in the business technology arena capitalize

Women hold 55 percent of STEM jobs.

12 | ORMS Today

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February 2016

on women’s greatest strengths in the workplace: “communication, collaboration and problem solving.”

- USA Today, Jan. 12

Management Science Makes List of Top 25 STEM Majors Finding the optimal way to use a workforce is not an art – it’s a science.

In small groups a missing employee can cause sleepless nights when deadlines approach, while an extra employee can result in missed performance metrics. In large groups, such as Fortune 500 companies, these same problems can cost a company billions of dollars or result in thousands of lost jobs. Management science applies the principles of mathematics to the modern office to streamline processes, cut costs and grow revenue.

for those adulterations? And how can we solve the problem?”

In two papers published in top journals Management Science and Production and Operations Management, Mu’s team found three key reasons behind the milk adulteration problem, as well as a number of creative solutions.

- UDaily, Jan. 12

INFORMS CAP Certification ranked No. 1 While you’ll have to determine your own goals and certification needs, let’s look at a handful of important and valuable certifications all IT professionals should consider earning.

1. Certified Analytics Professional CAP certification enables you to understand the entire analytics process. From framing business and analytic problems to deployment and model lifecycle management, you’ll have full knowledge of everything that goes into general analytics by the time you finish this certification process.

- Data Science Central, Dec. 17, 2015

- USA Today, Dec. 8, 2015

Detecting Sick Milk in China In 2008, thousands of children in China fell ill after drinking milk that had been adulterated with the chemical melamine.

This scandal inspired Liying Mu, University of Delaware assistant professor of operations management, to study ways to eliminate this dangerous and common problem.

“Milk adulteration, such as by adding water, detergent or starch to milk, has been widely reported in many developing countries,” Mu said. “What are the reasons

CAP named most valuable certification.

Healthcare Analytics Trends for the New Year Analytics continues to bring dramatic change to the healthcare industry in the United States and other countries, offering advances and challenges for the year ahead. Following are 10 trends to chart in 2016.

- Brian Denton (president-elect of INFORMS), Health Data Management, Dec. 21, 2015 ormstoday.informs.org

2016 Analytics Trends to Watch For My view of the world is shaped by where I stand, but from this spot the future of analytics for 2016 looks pretty exciting! Analytics has never been more needed or interesting.

- Polly Mitchell Guthrie (INFORMS member), Information Management, Dec. 21, 2015

Temptation Bundling at the Gym Lack of motivation may also play a large role in the reason why 68.8 percent of Americans are overweight or obese.

So are we all screwed? Or is there a way to keep motivation consistently flowing?

The key may be a process called “temptation bundling,” according to a study in Management Science.

The process pairs two activities – one you should do, but avoid; and one you enjoy, but isn’t necessarily productive, explains lead study author Katherine Milkman, associate professor of Operations, Information and Decisions at The Wharton School.

- Men’s Health, Dec. 18, 2015

High Debt Load Tough for Union Negotiators Why are unions having a tough time in this country? One reason is that companies are getting leverage. A recent study found that companies with a higher debt load were less likely to experience a strike during contract negotiations, particularly at companies with large unions, worse financial prospects, or underfunded pension plans.

Some companies seem to anticipate this and load up on debt before contract negotiations, whereas companies that didn’t do this and experienced a strike subsequently add a ton of debt, particularly if the union won the strike. The debt gives the company a bargaining advantage by limiting how much earnings can be shared with workers vis-àvis lenders, and often takes the form of stock buybacks, to avoid bringing money into the company.

[Citation] Myers, B. & Saretto, A., “Does Capital Structure Affect the Be-

havior of Nonfinancial Stakeholders? An Empirical Investigation into Leverage and Union Strikes,” Management Science.

- Boston Globe, Jan. 3

Bed Net Plan for Underfed Kids Curbs Malaria Deaths Giving extra bed nets to children weakened by lack of food could significantly curb child deaths from malaria, according to a mathematical model revealed last month.

A study published in the Malaria Journal found that distributing insecticide-treated bed nets and supplementary food to undernourished children aged from six months to five years could help prevent their deaths from malaria. This is because children with malnutrition are much more likely than healthy children to succumb to the disease, the paper states.

The model proposed by Milinda Lakkam and [former Operations Research editor in chief and INFORMS Fellow] Lawrence Wein, two mathematicians at Stanford University in the United States, shows that such targeted distribution of insecticide-treated bed nets is better at reducing malaria deaths than random distribution. In one tested scenario, where malaria transmission was pegged as seasonal and intermittent, the distribution of bed nets specifically to undernourished children achieved a 69 percent reduction in malaria mortality.

- SciDev.Net, Jan. 6

Portfolios and Their Debt to an O.R. Nobel Winner During WWII, academics developed “operations research” techniques involving statistics and linear programming to hunt enemy submarines, supply troops on the ground and deliver ordnance to targets. Soon after the war ended, operations research academics began to apply their methodologies to investing. In 1952, Harry Markowitz, a graduate student at the University of Chicago, published a paper on portfolio selection in the Journal of Finance.

Markowitz’s quantitative approach to investment theory was radically different from the conventional stock market wisdom at the time, which focused on picking winning stocks and concentrating stock holdings to maximize return.

Markowitz’s work provided investors with quantitative ways to reduce risk and optimize their return.

Investors knew that holding stocks meant taking risks, and they were led to believe that the only way to reduce risk was to become more competent at picking stocks.

Some investors were following the advice of Gerald M. Loeb, the co-founder of brokerage firm E.F. Hutton, who wrote,“once you obtain competency, diversification is undesirable.” Markowitz’s work along with others gave birth to what is now known as Modern Portfolio Theory (MPT). MPT provided investors quantitative ways to reduce risk and optimize their return.

- Monterey Herald, Dec. 12, 2015

How to Improve Decision-Making in Supply Chains David Simchi-Levi, MIT Professor, INFORMS Fellow and former editor in chief of Operations Research (INFORMS journal): The ability to understand a combination of historical behavior, market conditions and future needs drives decision-making. New analytic capabilities that combine machine learning and optimization can take into account historical characteristics and competitor behavior to determine future demand that will allow optimization for the best results – such as profit, market share or revenue.

Examples of decisions where this approach can be used in assortment, pricing, sourcing strategies for new products and predictive maintenance using process sensors. ORMS - SupplyChainOpz, Dec. 23, 2015 Compiled by Barry List, associate director of communications for INFORMS. To share your news-making research, contact List at barry.list@informs.org or 1-800-4INFORMs.

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Newsmakers

Edelman finalists, long queues & STEM majors INFORMS announces 2016 Edelman Award finalists INFORMS named six organizations representing applications of real-world operations research and advanced analytics for the 2016 Franz Edelman Award competition.The winner will be announced at the INFORMS Conference on Business Analytics & Operations Research in Orlando, Fla., in April following a daylong series of presentations before a panel of judges.

The finalists include: • 360i for “360i’s Digital Nervous System” Digital Nervous System is a suite of paid search optimization and management systems for online marketers that rapidly selects keywords and creates campaigns; reverse engineers the Google second-price auction to identify quality score problems before they arise; calculates accurate bids for keywords with sparse data; integrates advanced application programming interfaces into real-time search bids and ad creation; and creates detailed pricing forecasts to produce bids on keywords.

The Digital Nervous System has resulted in $250 million in cost savings and $1 billion in revenue generation for the company’s paid search clients.

• BNY Mellon for “Transition State and End State Optimization Used in the BNY Mellon U.S.Tri-Party Repo Infrastructure Reform Program” BNY Mellon is a leader in the triparty repo market with approximately $2.2 trillion serviced globally, which includes $1.3 trillion or 85 percent of the U.S. tri-party repo market. In response to the 2008 financial crisis, BNY Mellon worked closely with its clients, their investors, and other market participants to meet the recommendations of the U.S.

The Edelman competition is considered the “Super Bowl of O.R.”

Tri-Party Repo Infrastructure Reform Task Force sponsored by the Federal Reserve Bank of New York.

In August 2012, Karen Peetz, BNY Mellon president, spoke before the U.S. Senate Subcommittee on Securities, Insurance, and Investment about the U.S. tri-party repo market and this initiative to practically eliminate intraday credit risk, defined as a 90 percent reduction. BNY Mellon has exceeded the 90 percent goal to reduce secured credit extended in the tri-party repo market as $1.44 trillion risk reduction has been achieved, or 97 percent.

• Chilean Professional Soccer Association (ANFP) for “Operations Research Transforms Scheduling of Chilean Soccer Leagues and South American World Cup Qualifiers” Over the last 11 years, operations research techniques have been applied to schedule professional soccer leagues in Chile. These techniques have yielded a direct economic impact of more than $55 million through a combination of increased ticket sales, cost savings, and subscriber growth for Chile’s soccer television channel and cost reductions for the teams due to the better travel schedules resulting from an improved ordering of home and away games.

These techniques have also been used to schedule the South American 2018 FIFA World Cup qualifiers.

• The New York City Police Department (NYPD) for “Domain Awareness System (DAS)” The Domain Awareness System (DAS) is a network of sensors, databases, devices, software and infrastructure that delivers tailored information and analytics to the field and to precinct desktops enabling police officers to make more informed decisions. Originally designed for counterterrorism purposes, the DAS has been modified for general policing and is now deployed across every police precinct in the five boroughs, and will shortly be on all 36,000 officers’ smartphones and all 2,000 police vehicle tablets. No other police department in the world shares information and delivers analysis to its officers as effectively.

The NYPD is now more effectively using its data to inform decisions at all levels of the Department, allowing it to better serve the City of New York.

• UPS for “UPS On Road Integrated Optimization and Navigation (Orion) Project” The UPS Orion project is based on a sophisticated algorithm that automatically plots the course of more than 30,000 UPS drivers every day, which will increase to 55,000 drivers in 2016.

Because ORION provides an optimized delivery sequence that meets multiple operational constraints, the drivers are relieved of the complexity of determining how to make their deliveries.

Costing $250 million to build and deploy, ORION is expected to save $300 million to $400 million annually, reduce annual CO2 emissions by 100,000 metric tons, and decrease yearly fuel consumption by 10 million gallons.

• U.S. Army Communications Electronics Command (CECOM) for “Bayesian Networks for U.S. Army Electronics Equipment Diagnostic Applications: CECOM Equipment Diagnostic Analysis Tool,Virtual Logistics Assistance Representative” Soldiers in Afghanistan are required to operate and maintain complex electronic weapon systems with minimal resources Newsmakers, continued on p. 16

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GREAT STORIES CREATE LASTING IMPRESSIONS...

YOURS SHOULD TOO.

Learn how to become a compelling data storyteller.

Register today for ESSENTIAL PRACTICE SKILLS FOR HIGH-IMPACT ANALYTICS PROJECTS April 13-14, 2016 | 8:30am-4:30pm University of Central Florida Executive Development Center Orlando, Florida

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Newsmakers

Newsmakers, continued from p. 14

in combat conditions. The inherent logistics challenges of the Combat Outpost (COP) environment make it difficult to provide timely assistance with support personnel.

Research on the life cycle of COP equipment problems shows that early misdiagnoses can initiate a chain of events that can create lengthy system outages and put lives in jeopardy. CECOM has developed and implemented the CECOM Equipment Diagnostic Analysis Tool,Virtual Logistics Assistance Representative (CEDAT VLAR) to directly address the onsite needs of soldiers in Afghanistan by mitigating knowledge gaps in the COP environment.

This has resulted in tens of millions of dollars in cost savings, increased maintenance efficiency, reductions in troubleshooting time, and No Evidence of Failure (NEOF) component returns have been reduced to zero over the last 18 months.

The finalists were chosen after a rigorous review by verifiers, all of whom have led successful analytics projects.

The verifiers come from organizations such as Verizon Wireless, HP, Turner Broadcasting, Carnegie Mellon University, PriceWaterhouseCooper, SAITECH, Princeton Consultants, University of Chicago and University of Maryland.

Art, science and psychology of managing long queues As a world-renown expert in queueing theory, MIT professor Richard Larson, aka “Dr. Queue,” knows all about waiting in lines. So it’s no surprise that when the Washington Post’s Wonkblog reporter Ana Swanson needed an expert source for her story on the art and science of managing long queues, she called on Dr. Queue.

According to Larson, people can expect to spend one to two years of their lives waiting in line, most of it stuck in traffic. But those five-minute waits in the checkout line at the supermarket, stuck behind someone talking on their smartphone while fumbling with a pile of coupons and dollar bills to give to the checker, can be just as annoying.

As Swanson notes in the article, waiting in line not only irritates the customer, 16 | ORMS Today

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February 2016

People can expect to spend one to two years of their lives waiting in line.

it’s bad for business. “A long and unpleasant wait can damage a customer’s view of a brand, cause people to leave a line or not enter it in the first place (what researchers respectively call ‘reneging’ and ‘balking’), or discourage them from coming back to the store entirely,” she writes.

Businesses, of course, realize this and come up with various ways to solve the problem, starting with good, old-fashioned distraction such as magazines in the doctor’s waiting room and near the supermarket checkout lines. Larson, a past president of INFORMS, considers Disney the “undisputed master” of designing queues that are entertaining and that create anticipation for the ride. “In my book, [Disney is] number one in the psychology and in the physics of queues,” Larson tells the Post.

Writes Swanson: “The design is so successful that parents with young children can happily stand in line for an hour for a four-minute ride – a pretty remarkable feat, [Larson] points out. And of course, the capacity of the line and the ride are carefully calculated to balance customer satisfaction with profits.”

“To read the complete article “What really drives you crazy about waiting in line, see https://www.washingtonpost.com/news/ wonk/wp/2015/11/27/what-you-hateabout-waiting-in-line-isnt-the-wait-at-all/ STEM majors with the best value Not surprisingly, WorldWideLearn. com’s updated list of the “STEM Majors With the Best Value for 2015” is loaded

with majors common among members of the analytics community.The list includes information technology (No. 1), computer programming (No. 3), computer and information science (No. 5), engineering (No. 7), data modeling (No. 9), computer systems analysis (No. 11), mathematics (No. 18), management science (No. 21), informatics (No. 22), petroleum engineering (No. 23) and physics (No. 25).

WorldWideLearn.com analyzed 122 majors belonging to the STEM disciplines. To be included in the rankings, each major had to meet at least one of the following criteria: • be on the 2012 STEM-Designated Degree Program List from the Department of Homeland Security, and • be matched by the National Center for Education Statistics to a job on the Bureau of Labor Statistics’ list of STEM occupations Ranking criteria including educational availability, educational affordability, earnings and employment opportunity. ORMS CL ARIFICATION An article in the December 2015 issue of OR/MS Today (“Improving protection for our protectors”) referred to a “growing population of veterans.” Currently, the overall number of U.S. veterans is, in fact, declining, as the aging out of older cohorts more than offsets the influx of new veterans. This fact is immaterial to the rest of the article, which focused on improving veterans’ care.

ormstoday.informs.org

Abstract Submission & Registration is Now Open

2016 INTERNATIONAL CONFERENCE HAWAII June 12–15, 2016 Hilton Waikoloa Village SUBMIT AN ABSTRACT:

http://meetings.informs.org/2016international/abstracts/ Hawaii 2016 delivers an impressive lineup of keynote and plenary speakers interspersed with invited tracks with emerging topics ranging from global supply chains to social networks, affording you the opportunity to network and collaborate with colleagues across the globe and from both academia and industry.

2016 INTERNATIONAL

HAW II PLENARY SPEAKER:

GANG YU, Executive Chairman & Co-Founder of New Peak Group

REGISTER at meetings.informs.org/2016international

INFORMS Initiatives

Analytics education, certification board One-Stop Shop on university analytics

By Diego Klabjan You’ve seen them bursting on the scene in universities across the United States and around the world. With the increasing popularity of analytics in the business world, courses and degreed programs in business analytics, data science and all their offshoots are popping up at engineering schools, business schools and computer science departments.

INFORMS recently launched what is arguably the most comprehensive website about university analytics programs, and whether you’re a program director, professor, aspiring student or business leader, you’ll find loads of help and information that will guide you.

You can access the new INFORMS Analytics Education One-Stop Shop website at http://education.informs.org/.

If you’re teaching analytics in the classroom, you can use the website to access existing materials that will help you design your course and work with students in the classroom.You can obtain case studies from INFORMS Transactions on Education, INFORMS’ suite of journals, the INFORMS Marketing Society’s collection of data sets and more INFORMS sources.The website will lead you to a broad collection of analytics case studies and syllabi, data sets that can be used to assign problems, case competitions and classroom teaching resources from software developers.

If you’re a program director, you will find studies conducted by INFORMS committees with direction on starting and improving analytics programs, with a special emphasis on what industry expects 18 | ORMS Today

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February 2016

INFORMS. Contact Barry List at barry. list@informs.org or informs@informs. org with your details, questions and suggestions for future versions.

Diego Klabjan is a professor at Northwestern University and chair of the INFORMS University Analytics Programs Committee.

Whether you’re a program director, professor, aspiring student or business leader, you¹ll find loads of help and information that will guide you.

from you and your graduates so you can carefully design your program to ensure that your grads are equipped to find positions fast.You can compare your program to the competition by searching INFORMS’ rich database of American programs and courses that are taught at those programs.

Students will find that the OneStop Shop is the first place to go when planning graduate work in analytics. The site’s database lets students search for programs by filtering on terms that are important to them: where a program is located, what type of degree is granted by a program, admission testing requirements, program delivery and type of school.

If you’re in business, government, healthcare or consulting, you’ll find that the One-Stop Shop helps you meet your analytic needs in a centralized way. If you’re seeking job candidates, it will help you identify the most appropriate schools and programs that meet the needs of your organization.

The site has the added feature of letting you gain knowledge about partnership opportunities: If your organization needs to conduct a research project with a university partner, you can identify schools with analytics heft in your field, specialty and geographical area.

INFORMS will spend much of 2016 improving its website, and the One-Stop Shop will expand and be even easier to use in INFORMS Online’s next version.

You can make the database more complete. If your school, program and courses are not in the searchable database, make sure to provide your information to

Mitchell-Guthrie, Levis to lead Analytics Certification Board Polly Mitchell-Guthrie of SAS and Jack Levis of UPS will serve as chair and vice chair, respectively, of the 2016 Analytics Certification Board (ACB) following their election by INFORMS members and CAP designees.

They will be joined on the ACB Board by: Aaron Burciaga, CAP, Accenture Digital; To m D ave n p o r t , Babson College; Bill Franks, Teradata; Esma Gel, Ar izona State University; Jeanne Har r is, Columbia University of New York; Lisa Kart, CAP, Polly Mitchell-Guthrie Gartner; Kathy Kilmer, D i s n ey ; Jo n a t h a n Owen, CAP, GM; Greta Roberts, Talent Analytics; Jim Williams, CAP, FICO; Melissa Moore, INFORMS executive director.

The ACB will meet on a quarterly basis to provide oversight and guidance to Jack Levis the Certified Analytics Professional and the Associate Certified Analytics Professional programs. ORMS For more about the CAP® program, visit https://www.certifiedanalytics.org/about.php

ormstoday.informs.org

What’s Your StORy? Saif Benjaafar Distinguished McKnight University Professor, Director of the Initiative on the Sharing Economy and the Center for Supply Chain Research at the University of Minnesota INFORMS member since 1989 What prompted you to enter this field? Why? I started out as an electrical engineer. I took courses in O.R. and economics and became intrigued about how mathematics could be used to model not just physical phenomena but also economic and social interactions.

What has been your favorite INFORMS experience so far?

Seeing the recent growth in OR work that addresses big societal problems including the environment, energy, and health.

If we were sitting here a year from now celebrating what a great year it's been for you, what would we be celebrating?

After spending three years as Dean of a new school in Singapore, I am happy to devote more time to research. I hope to be celebrating some of the work we would have completed by then.

What is something you learned in the last week?

I just returned from a trip to Italy during which I visited Murano, a series of islands near Venice. Murano has evolved over the centuries to become a major world center for glassmaking.

It turns out that this was an unintended consequence of glassmakers being banished from Venice in the 13th century (glass furnaces posed a fire hazard for the city’s mostly wooden buildings). Over time, this allowed Murano to develop (perhaps not unlike today’s Silicon Valley) the eco-system and the critical mass of talent to grow into the unrivalled center for glassmaking that it became.

What interest do you have outside of work that might surprise us?

I enjoy traveling and spending time in Asia, particularly in my favorite city Hong Kong.

More questions for Saif?

Ask him in the Open Forum on INFORMS Connect!

http://connect.informs.org

First Person

By Michael Mortenson, CAP M.J.Mortenson@lboro.ac.uk

If the CAP fits …

Personal experience of taking the INFORMS Certified Analytics Professional exam.

The OR Society (Operational Research Society, based in the United Kingdom) has a longstanding interest in analytics and in helping its members engage with the field. As part of this, the Society has been investigating the possibility of providing INFORMS’ Certified Analytics Professional certification to Society members and the wider U.K. operational research community. It was decided that it would be useful to have someone with first-hand experience of the exam, i.e., a guinea pig. This was where I came in.

Having agreed to take the exam, I did the usual thing that any conscientious student does: next to nothing for ages and then panicked at the last minute. In many ways the panic was unnecessary; this is not a “book-smarts” exam but one where prior experience is really the only way to pass. You do need to have significant knowledge of the concepts and methods of analytics, but I would say it’s one-part theory to four-parts practice. Many questions specifically focus on practice-based challenges (stakeholder meetings, problem definition, lack of data and so on), and even where the more technical questions arise, predominantly it is on the basis of selecting the right method to fit the problem or identifying the steps to take when model performance dips. In short, and to INFORMS’ credit, this is not an exam that can be bluffed – you have to walk the walk as well as talk the talk.

It is, however, an exam I would recommend, both to analytics/O.R. professionals seeking to “prove” their practical expertise, and to employers looking for recruits who can genuinely hit the ground running. For the benefit of anyone con20 | ORMS Today

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February 2016

I did the usual thing that any conscientious student does: next to nothing for ages and then panicked at the last minute.

sidering the exam I will give you my perspective on assessing your readiness and how to best prepare.

For recent graduates my honest recommendation would be taking the exam after working on some real-life projects. However, you may be able to lean on a mentor or a more experienced colleague. The handbook gives a reasonably thorough definition of the analytics project lifecycle, so it will give you a good idea of the topics to cover.

Specialist consultants will likely have the necessary depth to cover many of the questions. However, the bigger issue is breadth. There are many debates about what “analytics” actually is, and definitions range from “another name for O.R.” to “a branch of computer science.”

This certificate is definitely more at the O.R. end of the spectrum (no bad thing to my mind), and for specialists with a predominantly IT-type background there will be the need to familiarize yourself with the O.R. canon to a fairly extensive level. However, for those from an O.R. background, this alone is unlikely to be enough.You will need a reasonable knowledge of a range of topics, including data warehouses, project management and machine learning.

Ultimately, I think the exam is best suited to analytics professionals working in larger companies or those working on “fullstack”-type projects. Whatever view you have on what analytics is, it is a wide-ranging field and the exam reflects this. For this group, working through the handbook and taking a refresher on anything that looks less familiar is likely to be enough.

Many CAP exam questions specifically focus on practice-based challenges.

Overall, I found the exper ience nerve wracking (my first exam in more than 15 years) but rewarding, suitably challenging and definitely a source of personal achievement. As to whether it makes a massive difference to my career, well, only time will tell. ORMS Michael Mortenson, CAP, is a doctorate candidate at Loughborough University researching the development of analytics education in U.K. universities. Prior to returning to academia, he worked for several years in marketing and ecommerce in the travel industry and in recent years has worked as a consultant providing digital marketing and analytics services to a variety of companies.

ormstoday.informs.org

INFORMS PROFESSIONAL COLLOQUIUM (IPC) Student Nominations Sought Nominations are being sought for aspiring graduate students seeking industry positions to attend the IPC. The 2016 INFORMS Conference on Business Analytics & Operations Research will be held in Orlando from April 10–12. The INFORMS Professional Colloquium is a full-day workshop within the Conference that consists of talks, panel discussions, and role play sessions organized by OR leaders and practitioners from diverse industry segments. The colloquium is not only designed to help the participants transition into a successful industry career, but is also an excellent networking opportunity where the students can interact with OR leaders and practitioners.

VISIT: http://meetings.informs.org/wordpress/analytics2016/professional-colloquium/

CONTACT Ellen Tralongo ellen.tralongo@informs.org

SAS and INFORMS Analytics Section Student Analytical Scholar Competition Accepting applications until Feb. 22, 2016

SAS and INFORMS want to recognize one outstanding student interested in the practice of analytics by paying his or her expenses to attend the INFORMS Conference on Business Analytics and Operations Research held April 10-12, 2016, in Orlando, FL. The purpose of the competition is to practice structuring and presenting a compelling proposal for analytical work. Applicants will be asked to produce a statement of work document for a case study based on a real-life project.

Application deadline: Feb. 22, 2016 For application details, visit: www.informs.org/SAS-AnalyticsScholarCompetition

PuzzlOR

John Toczek

puzzlor@gmail.com

Toy builder As a toy builder you enjoy making toys for both fun and profit. For your latest production batch, you need to decide how many of each toy to make.The three types of toys you make are airplanes, helicopters and cars as shown in Figure 1.

To build an airplane you need three blue blocks, two green rods and one red wheel. To build a helicopter you need two blue blocks, four green rods and one red wheel. To build a car you need one blue block, two green rods and four red wheels.

Your profit margins for each toy are as follows: airplane $7; helicopter $8; car $5.

The parts available to you are as follows: 25 blue blocks, 29 green rods and 30 red wheels. It is OK to have leftover parts.

Question: What is the maximum profit you can achieve?

Send your answer to p u z z l o r @ g m a i l . c o m by April 15. The winner, chosen r a n d o m l y f ro m c o r re c t answers, will receive a $25 Amazon Gift Card. Past questions and answers can be found at puzzlor.com. ORMS

Figure 1: What is the optimal mix of toy cars, planes and helicopters?

John Toczek is the assistant vice president of predictive modeling at Chubb in the Decision Analytics and Predictive Modeling department. He earned his BSc. in chemical engineering at Drexel University (1996) and his MSc. in operations research from Virginia Commonwealth University (2005).

2016 EDELMAN FINALISTS

CONGRATULATIONS TO THE

360i, for “360i’s Digital Nervous System”

BNY Mellon, for “Transition State and End State Optimization Used in the BNY Mellon U.S. Tri-Party Repo Infrastructure Reform Program” Chilean Professional Soccer Association (ANFP), for “Operations Research Transforms Scheduling of Chilean Soccer Leagues and South American World Cup Qualifiers” The New York Police Department (NYPD), for “Domain Awareness System (DAS)” UPS, for “UPS On-Road Integrated Optimization and Navigation (Orion) Project” U.S. Army Communications-Electronics Command (CECOM), for “Bayesian Networks for U.S. Army Electronics Equipment Diagnostic Applications: CECOM Equipment Diagnostic Analysis Tool,Virtual Logistics Assistance Representative” Join us at the Edelman Gala, April 12 in Orlando, FL when the 2016 winner is announced! www.meetings.informs.org/analytics2016

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ormstoday.informs.org

®

CERTIFIED ANALYTICS PROFESSIONAL Analyze What CAP Can Do For You ®

www.certifiedanalytics.org

FORUM

By Stelios Kavadias, Christoph Loch and Stefan Scholtes

A future for operations Getting serious about the context of big problems.

We were rather taken aback when we read an interview with Professor Gerard Cachon in the December 2015 issue of OR/MS Today (“What’s Your Story?” page 11).When asked, “What is the best advice you can give to students in your field?” he replied: “Pick another field. One with big, important problems, like economics, or computer science or climate science.”

At first glance, if this is our current reality, then we are on the verge of bankruptcy in our field. Have we suddenly resolved all challenges related to the design and management of efficient and effective processes and projects? Is it really time to move on into other scientific fields? A statement from a former editor in chief of M&SOM and Management Science cannot be taken lightly; Professor Cachon is one of the leaders of the operations field, so his opinion probably reflects a wider perception about our field.

But we think this worrying perception can be positively addressed by focusing on some of the world’s major unmet needs and our field’s crucial role in meeting them. In so doing, we can show a new generation of OR/MS specialists that they can make a demonstrable contribu-

tion to society by tackling a big, specific problem in a practical, down-to-earth way that complements their scholarly pursuits, as we outline below.

On a purely academic surface, citation evidence supports Professor Cachon’s gloomy advice. Citation rates, even of the leading operations journals, are depressingly low – as is probably the active readership of our papers.We are not producing research that people wait to read, not even academics in our own field, let alone senior decision-makers in the proverbial real world.

Ask a senior operations manager whether they know about management science, and if they would entertain sitting through an academic operations conference?

A few celebrated examples of real impact cannot hide the fact that the academic field that is concerned at its heart with productivity is not very productive at creating high-impact solutions to big problems.This state of affairs is disheartening, and if we don’t change it, students will increasingly follow Professor Cachon’s advice, and the field, as we know it, will disappear – with the management challenges it sets out to address being subsumed into other management disciplines.

A plethora of big, important problems cry out for innovative research in operations.

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Such a downward spiral will most probably first affect newcomers to the field – our Ph.D. students. In fact, assessing the attractiveness of an academic field from the perspective of prospective Ph.D. students is a very sensible health check. Most prospective Ph.D. students across management disciplines share three characteristics:They are very smart, very naïve and very passionate about doing something meaningful through their research. They don’t know what it is, nor how to do it – but they long to be part of a big story. Professor Cachon is right in that if we don’t offer them the opportunity to participate in the solution of “big, important problems” we’ll lose them to other fields. However, while his diagnosis is spot on, we would argue that sending the students to other fields is the wrong treatment.

If we look at our field narrowly and assess additional opportunities for the derivation of closed-form mathematical solutions that have impactful implications, then Professor Cachon is right – it’s a serious challenge. But this reaction reflects a narrow view of our field, one that is oriented toward generic formal methods and one that defines the field from the supply side.The picture completely changes if we look at our field from the demand-side and consider the huge problems that need solving, problems that need operations expertise and an operations mindset.

Fortunately for the field, there is a plethora of big, important problems that cry out for innovative research in operations.Whether developing new antibiotics or a cure for Alzheimer’s, keeping a lid on healthcare costs, preventing terror attacks, managing refugee crises, securing energy supply, saving the climate, or helping African countries assimilate funds and catch up with the rest of the world, there is not a single really big problem in the world that does not pose the same immense operational challenge: how to achieve a desirable goal with limited resources? Our understanding and the evidence-based advice that we, as an academic community, can give to leaders in business and society who wrestle with these big problems is rather limited, and the more limited it is, the bigger the problem. Big problems ormstoday.informs.org

are complex, so generic solutions based on convenient assumptions are simply not valid. Any good operational solution to such a problem has to be context-specific, and its development requires deep knowledge of this context.

Over the past decades, our field has largely focused on the development of generic insights that apply across contexts. We have shed light on isolated phenomena, but the importance of these insights in a specific context can be quite limited and the underlying assumptions that allow the isolated study of a phenomenon are typically not satisfied. Big problems require novel solutions. To contribute to the immense operational challenges posed by these problems, we can draw on the existing insights, but they need to be adapted, often substantially, and they need to be integrated into the specific context of the real problem.

What works for banks doesn’t necessarily work for hospitals, and what works

in the United States doesn’t necessarily work in Africa. The context matters.

If we look at the opportunities for our field with such an attitude, we should be thriving. It is up to us to grab these opportunities, and to involve our Ph.D. students in ways that make them not only technical method specialists but also knowledgeable experts in big domains where they can make big contributions to business and society.

So we may offer an alternative advice (a plea): operations academics, and in particular the leaders in our field, should encourage their Ph.D. students to engage at least as much with the context of one “big problem” as they do with methods.

Both are important: Engagement with big problems without rigorous methodology leads to pseudo-academic advocacy, while rigorous methodology without engagement with big problems adds little value and is unsustainable, particularly in business schools. A symptom of the latter is a junior

faculty job market that is populated by an amorphous mass of “suits” who have lost the spark of passion and are only differentiated by their varying chance of success at publishing technical papers with their supervisors in leading journals that are neither widely read nor cited.We can rekindle the passion in our Ph.D.s if the field begins to complement its exceptional methodological expertise with serious engagement with the context of big practical problems.

This takes a lot of time and effort and, in the absence of market incentives, requires real leadership. ORMS Christoph Loch is dean of the Judge Business School, University of Cambridge (U.K.), Stelios Kavadias is the director of research at the school, and Stefan Scholtes is director of the school’s Ph.D. program. Along with their positions as senior members of the operations group at the Judge Business School, all three hold or have held associate editor positions on such INFORMS journals as Management Science, M&SOM, Operations Research and Mathematics of Operations Research.

NORTHWESTERN ANALYTICS Northwestern University offers two master’s degree programs in analytics that prepare students to meet the growing demand for data-driven leadership and problem solving. Graduates develop a robust technical foundation to guide data-driven decision making and innovation, as well as the strategic, communication and management skills that position them for leadership roles in a wide range of industries and disciplines.

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February 2016

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Viewpoint

By Bradley C. Boehmke and Ross A. Jackson

Unpacking the true cost of ‘free’ statistical software Pollack, Klimberg and Boklage (PKB) [1] recently asked in OR/MS Today if opensource, statistical software is really free.Their employment of truth and sketch of hidden costs suggest their answer is no. In a sense, we agree. Economic thinking acknowledges there is no free lunch. However, when it comes to the relative risks and merits of software, much remains to be discussed.

Despite their titular assertion, PKB did not present “the true cost of ‘free’ statistical software.” Rather, they provided an alternative conceptualization of costs, particularly those of the R programming software.We present a critique of that conceptualization and rebut their seven main claims.Taking a postmodern turn, we leave notions of truth to consumers.

Claim 1: Open-source is a craze. Initial framing of a topic is consequential.

PKB introduced open-source software as “one of the newest crazes.” Their use of craze is problematic. Craze conveys something that is popular but short-lived.

It is currently conjecture that the gain in prominence of open-source software will be short-lived. In fact, evidence suggests otherwise as some of the largest proprietary software developers are open-sourcing their languages (e.g., Swift by Apple, Go by Google). Furthermore, organizations are proving to value open-source capabilities. A recent O’Reilly survey revealed that analysts focusing on opensource technologies make more money than those dealing in proprietary technologies. Time is needed to determine if this is a “craze” or a software market shift.

Claim 2: Technical ability demands.

PKB stated that R requires more technical ability. Although presented as a disadvantage, this is also the foundation of potential benefits. The data analysis process is rarely restricted to a handful of 26 | ORMS Today

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February 2016

tasks with predictable input and outputs that can be pre-defined by a fixed user interface. In proprietary software, only the developer has access to the underlying software to modify the interface.

Open-source software, such as R, blurs the distinction between developer and user, which provides the ability to extend and modify the analytic functionality to the organization’s needs. This allows the data analyst to manage how data are being transformed, manipulated and modeled.

Does this take more technical ability?

Yes, but through the process one gains a beneficial autonomy, which organizations have proven to value.

Claim 3: Inferior data handling capability. Are R’s data handling capabilities inferior to those of SPSS/SAS? Answering this requires clarifying what “data handling” means.We define data handling as the ability to collect, hold and process data. Between commercial software and R, the basics of importing data and the size of data each can process are comparable.Where equivalence lacks is in harvesting data from online sources. Few proprietary statistical software products enable scraping data from Web pages. R does. While differences exist in how these programs connect to distributed data storage and processing capabilities, no evidence to date compares these capabilities.

PKB speculated here; traveling along means, in J.K. Rowling’s words,“We shall be leaving the firm foundation of fact and journeying together through the murky marshes of memory into thickets of wildest guesswork.”

Claim 4: Inferior user support. For PKB, “one of R’s most serious challenges” is a lack of official help.They acknowledged commercial help comes at “a significant financial cost,” but value “expert” insight.

While this assistance is likely more definitive, the transaction occurs within a web of com-

mercial relationships in which the pushing of product and support are ubiquitous. Further, commercial assistance often presents a single solution, where the R community provides multiple solutions. Learning to deal with complexity is essential.This ability is underdeveloped when one simply implements direction. Lastly, the “qualified professional support” from commercial software companies likely comes from customer support personnel.With R, questions regarding algorithms or package code are often answered by programmers.

Claim 5: Lack of quality, scientific controls and rigor. PKB cautioned users that R packages “lack the quality, scientific controls and rigor” of proprietary software. This is a common misperception. Recent Coverity Scan Open-Source Reports (an accepted standard for measuring open-source quality) have found that open-source code quality surpasses proprietary code quality. PKB’s statement minimizes the review process of publishing packages and the development of best practices in the R community.

Lastly, many R packages originate from academic research, institutions or from programmers that hold doctorates. It is questionable to establish a position on the implication that the quality, scientific controls and rigor of industry are inherently superior to those of our academic institutions.

Claim 6: Greater hidden costs. Hidden costs are essential to PKB’s argument.

Their warnings referenced how using R could result in “serious financial costs,” “dismantling costs” and “great risks to the credibility and reputation of any user.” It would seem using R could “immanentize the eschaton.” These hypothetical situations are probably more like R.E.M.’s “It’s the End of the World as We Know It (And I Feel Fine).”

While botched analytics could cause the existential collapse of organizations, the typical result would simply be irksome. PKB support their claim with an anecdote of how two of them were involved in a project in which R was dropped because it lacked adequate statistical details related to goodness of fit testing and odds ratios for logistic ormstoday.informs.org

regression. Through a Google search one can obtain these functions [2]. R does not lack the capabilities PKB listed. Locating and using the functions does require a willing operator.

Claim 7: Appropriateness in academia. In regards to educational use, PKB explained R should not be used “if the main objective in a course is to learn the statistical techniques of data mining/predictive analytics.” There are issues to unpack here. Learning a software interface is far from thinking. Using R requires the development of higher-order thinking and helps one integrate abstract knowledge with praxis. If R is harder to use, the student who learns R should be able to make quick use of commercial software; the opposite does not necessarily hold.

Further, college seems like an ideal place to learn challenging things, especially if through the process one is less constrained and more critical. Limiting analysts by the idiosyncratic purchases of organizations

is suboptimal when one could maximize their cognitive and technical abilities.

Conclusion It seems doubtful that those adroit at dealing with the complexities of statistical software would easily confuse the absence of a purchasing fee with a situation in which there are no externalities. PKB wrote an article directed at warning would-be consumers of risks associated with free statistical software. When unpacked, a more timely warning might be directed to providers of commercial products and their legions of service representatives and consultants.The apparent “craze” suggests they may need to become more efficient to remain relevant.

Time will tell which approach prevails. In the meantime, people will determine if R is right for them. Maybe it is; maybe it isn’t.

But wouldn’t rational consumers try the free solution first? ORMS Bradley C. Boehmke, Ph.D., is an operations research analyst whose research

primarily focuses on strategic cost analytics across the Air Force. Dr. Boehmke is also an adjunct professor at the Air Force Institute of Technology, Department of Operational Sciences. Ross A. Jackson, Ph.D., is a “poetanalyst” engaged in the exploration of linguistic and existential facets of the military-industrial complex. Additionally, Dr. Jackson is an adjunct instructor of economics at Antioch College in Yellow Springs, Ohio.

Disclaimer: The views expressed are those of the authors, and do not represent the official policy or position of the United States Air Force, Department of Defense or the United States government.

REFERENCES 1. Pollack, R. D., Klimberg, R. K., & Boklage, S. H., 2015, “The true cost of ‘free’ statistical software,” OR/MS Today, Vol. 42, No. 5, pp. 3435.

2. Null and deviance residuals can be determined using summary(); p-value and the model’s log likelihood can be calculated using the pchisq() and logLik() functions. Additional evaluation measures (i.e., Hosmer-Lemeshow) are also available.

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This top INFORMS practice prize spans all O.R. and analytics disciplines and application fields. Any work presented in an INFORMS section or society practice-oriented competition is eligible as long as the work did not result in a published paper.

The Wagner Prize competition is high-profile, with its own track at the INFORMS Annual Meeting.

Presentations are widely distributed via streaming video. Finalist papers are published as a special issue in INFORMS respected practice journal Interfaces.

The 2016 competition will be held at the INFORMS Annual Meeting, November 13-16, in Nashville, Tennessee. First-place prize of $1,000 will be awarded at the Edelman Gala, during the April 2017 Conference on Business Analytics and O.R. in Las Vegas, Nevada.

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Image © Joerg Hackeman | 123rf.com

Restoring and improving urban infrastructure is one of many Grand Challenges involving security.

OR: CATALYST FOR GRAND CHALLENGES

Opportunities in security

By David P. Morton and Suvrajeet Sen

Editor’s note: This is the third in a series of articles based on a report to the National Science Foundation titled, “O.R. as a Catalyst for Engineering Grand Challenges.”

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The infrastructure of the United States, and the world, is increasingly interconnected. The ongoing integration of systems – including transportation, energy, water, communications, finance and more – has been central to their growth in scale and reach and has facilitated increases in their functional efficiency. At the same time, these interdependencies make systems more vulnerable to both intentional threats and unintentional hazards. Operations researchers and O.R. practitioners build operational models of such systems precisely because the system’s performance can depend, often in surprising and subtle ways, on how various subsystems interact. As interconnected systems grow in complexity, having a trusted operational model is ever more essential for assessing system vulnerabilities and, in turn, addressing the challenge of how to secure that system. O.R. is ideally positioned to address the challenges of: formulating operational models of suitable fidelity; understanding vulnerabilities using appropriate models for chance hazards and malicious attacks; and, allocating scarce resources to best secure the system. ormstoday.informs.org

In 2008, the U.S. National Academy of Engineering (NAE) unveiled its Engineering Grand Challenges.

Here, we discuss how operations research can contribute to three of these challenges that involve security: 1) restore and improve urban infrastructure, 2) prevent nuclear terror, and 3) secure cyberspace.

Restore and Improve Urban Infrastructure The U.S. Department of Homeland Security (DHS) identifies the nation’s critical infrastructure as involving the following sectors: • Energy • Critical Manufacturing • Communications • Food and Agriculture • Banking and Finance • Information Technology • Healthcare and Public Health • Chemical Industry • Emergency Services • Defense Industrial Base • Water • Nuclear Reactors, Material and Waste • Dams • Commercial Facilities • Transportation Systems • Government Facilities • Postal and Shipping • National Monuments and Icons For decades, O.R. has helped plan, design, construct, monitor and maintain critical infrastructure.The O.R. community has pioneered advances in planning, operating and securing electric power systems and markets; in pricing financial instruments and optimizing financial portfolios; in recommending policy and improving operations for healthcare systems, public health systems and emergency services; in designing and operating manufacturing systems and supply chains; in routing and flow control in communications and transportation networks; in planning, operating and securing water-supply networks; and much more.That said, with an aging but increasingly interconnected infrastructure, and evolving threats arising from changes in geopolitics, we need more research to secure our critical infrastructure.

A principled O.R. approach to securing such systems consists of three steps. First, we must understand how a system operates.We must have a working model, not only of how the system operates under nominal conditions, but also of how it will operate if any subset of its components is degraded or disabled.We cannot enumerate a handful of threat scenarios of how a system might be disrupted and expect it to span what we must consider. Rather, we require an operational model that we can systematically query.

The second step to secure infrastructure requires that we understand its vulnerabilities.To do so, we must dis-

tinguish unintentional hazards (e.g., natural disasters, malfunctions and human errors) and intentional threats (e.g., threats from vandals, criminals, saboteurs and terrorists).

The O.R. literature is replete with probabilistic models to represent the former, and the O.R. tools of game theory and adversarial models can capture the capabilities of an intelligent, informed and determined attacker.

Given a model, or family of models, from the first two steps, the third step involves allocating scarce resources to best enhance system security. O.R. is particularly well suited for formulating models to guide such choices.

Key to securing critical infrastructure is recognizing that components in our systems will fail and our infrastructure will be attacked. We cannot enhance component reliability – and deter determined adversaries – to the point where failures and attacks disappear. The foremost goal in securing infrastructure is that our systems be resilient; i.e., after degradation, operation of a system should adapt to its new configuration with minimal loss of capability.

The notion of taking a system-level view and of aspiring to resilience in the face of inevitable hazards and threats is well recognized by U.S. National Security Strategy [1]: “…the increasing interdependence of the global economy and rapid pace of technological change are linking individuals, groups, and governments in unprecedented ways.This enables and incentivizes new forms of cooperation to establish dynamic security networks... It also creates shared vulnerabilities, as interconnected systems and sectors are susceptible to the threats of climate change, malicious cyber activity, pandemic diseases, and transnational terrorism and crime.”

The O.R. literature includes significant work for securing infrastructure with a seminal paper by Brown et al. [2] describing the modeling framework we have just sketched and applying that framework to improving the security of our border, petroleum reserve and electric power grid. See, for example, [3, 4] for related work on securing air travel, [5] for work on securing municipal water systems and [6] for a recent overview.

Despite the success of this research, our foremost challenges in securing infrastructure remain. Modeling interdependencies in systems of vast physical scale and detail and of disparate time scales is truly challenging.

Populating such models with appropriate data can be challenging because most of the U.S. critical infrastructure is privately owned and operated. Success with such challenges helps build a trusted model through the first step above. However, an all-inclusive operational model typically does not have enough structure to lend itself to rigorous application of the second step to assess system vulnerabilities, let alone to application of the third step to optimize system security. Understanding and communicating to the stakeholders which differences in levels of detail in an operational model make a difference when it comes to understanding system vulnerabilities remains a deep challenge.

February 2016

The

foremost goal in securing infrastructure is that

our systems be resilient; i.e., after

degradation, operation of a system

should adapt to its new configuration with

minimal loss of capability.

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Grand Challenges Prevent Nuclear Terror The efforts of terrorist organizations and rogue nations to obtain nuclear material and technology to produce a nuclear weapon are well documented.

The United Nations’ International Atomic Energy Agency (IAEA) maintains an Illicit Trafficking Database. From 1993 to 2011, more than 2,000 incidents of unauthorized possession of nuclear and other radioactive material were reported. Sixteen of these incidents involved highly enriched uranium or plutonium (i.e., weapons-grade material). The IAEA reports that in cases where such information is available, the majority of these incidents involved traffickers attempting to sell illicit material.That said, motives of nuclear smugglers will likely change as the material changes hands from its origin to its intended destination.

The Domestic Nuclear Detection Office (DNDO) is part of the U.S. Department of Homeland Security. DNDO is charged with developing the Global Nuclear Detection Architecture (GNDA). Doing so requires coordination across multiple federal agencies including the U.S. Departments of Energy, Defense, State and the Nuclear Regulatory Commission. As part of the GNDA, the National Nuclear Security Administration (NNSA) works with other countries to: “Deter, detect, and interdict illicit trafficking in nuclear and other radioactive materials across international borders and through the global maritime shipping system. The goal is to reduce the probability of these materials being fashioned into a weapon of mass destruction or a radiological dispersal device (‘dirty bomb’) to be used against the United States or its key allies and international partners.”

Concern with this threat predates Sept. 11, 2001.

The NNSA program has its origins in 1998, when the United States, with the Russian State Customs Committee, launched a program that included placing radiation portal monitors (RPMs) at Russian customs checkpoints to deter smuggling of nuclear material out of Russia.That program has since expanded to border crossings and sea ports across the globe.

Much of the work associated with deploying the GNDA has involved NNSA and DNDO installing RPMs at international and domestic seaports, airports, rail and road border crossings. Customers and border protection officers are equipped with mobile radiation detectors. DNDO is developing other mobile detectors that can be deployed in so-called surge operations informed by intelligence reports. Further initiatives aim to secure cities and address challenges of detecting smuggling attempts between authorized ports of entry including smuggling attempts via small maritime craft and general aviation.

Conventional wisdom seems to be that obtaining weapons-grade material may be the most serious hurdle faced by a would-be nuclear terrorist:

From 1993 to 2011, more than

2,000 incidents of unauthorized

possession of nuclear and other

radioactive material were reported.

Sixteen of these

incidents involved highly enriched uranium or plutonium

(i.e., weaponsgrade material).

30 | ORMS Today

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February 2016

“It should not be assumed that terrorists or other groups wishing to make nuclear weapons cannot read.”

– Richard Garwin and Georges Charpak

“With modern weapons-grade uranium … terrorists, if they have such material, would have a good chance of setting off a high-yield explosion simply by dropping one half of the material onto the other half … even a high school kid could make a bomb in short order.”

– Luis Alvarez

For this reason, the NAE report has chosen to focus on nuclear material, outlining the challenges as follows: 1. How to secure nuclear material: Securing nuclear material requires a model of the supply chain.The IAEA inspects state nuclear programs in an attempt to ensure material is not being misused or diverted; O.R. models should play a role in the timing and nature of these inspections. If a rogue nation has developed an illicit nuclear program, the international community has at its disposal various options including diplomacy, embargoes, poaching, sabotage and military strikes. Understanding how to best interdict such a program relies heavily on O.R. [7].

2. How to detect material, especially at a distance: Much work in improving detection capability requires technological breakthroughs for better detectors. However, there are important opportunities for better detection algorithms; for deploying systems of detectors in multilayered defense around cities and at border checkpoints; and, in developing inspection protocols at ports. O.R. has contributed in these areas; see, e.g., [8, 9, 10]. Further challenges exist in securing borders between ports of entry.

3. How to render a potential device harmless: The U.S. nuclear arsenal has an elaborate system of safety technology designed to prevent accidental, and intentional but unauthorized, detonations.The U.S. has worked to downblend, or secure, weapons-grade nuclear material at storage sites in former Soviet States, and O.R. tools could inform how to prioritize such activities. O.R. played a role in scheduling the dismantling process for U.S. nuclear weapons at the Pantex site [11].

4. Emergency response, cleanup and public communication after explosion. This challenge has much in common with the discussion above on resilience of critical infrastructure.

Here, we require modeling of interconnected systems of critical infrastructure having incurred a massive disruption.This challenge is ideally suited for O.R. tools for precisely the reasons sketched in the infrastructure section. ormstoday.informs.org

5. Determining responsibility for an attack. The foremost challenge in attribution concerns nuclear forensics, which identify the source of the nuclear material. O.R. tools can enable “systems-based forensics,” e.g., given limited information regarding a captured nuclear smuggler, we may be able to infer via an “inverse problem” his origin and intended destination.

The O.R. community has already made significant contributions, but the challenge of preventing nuclear terror has engaged a small number of O.R. researchers, and there are significant opportunities to have greater impact. Moreover, in addition to nuclear and radiological threats, analogous challenges exist regarding chemical and biological attacks.

Secure Cyberspace Information and control systems are deeply embedded in our critical infrastructure.These systems have been designed for efficiency, with security typically included as an afterthought. We literally “patch” security holes as they are exposed in our daily computing devices.

O.R. is in an ideal position to balance efficient operation of infrastructure systems and the ability of

O.R. is in an ideal position to balance efficient operation of infrastructure systems and the ability of these systems to thwart, and be resilient to, cyber-attacks.

these systems to thwart, and be resilient to, cyberattacks. Cybersecurity threats range from individual criminal hackers to organized criminal groups to terrorists to nation states. Adversaries can disrupt our critical infrastructure on a massive scale. China and Russia have probed the U.S. electric power

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Grand Challenges grid. Traditional “perimeter” defenses, like firewalls, are eventually penetrated or otherwise bypassed.

They do not deal with denial-of-service attacks, and they fail to deal with adversaries already inside the perimeter. Improving intelligence is key in protecting infrastructure, including cyberspace.

O.R.’s wide reach positions our community to provide the kind of understanding of system complexity identified in the The Networking and Information Technology Research (NITR) strategic plan [12], which calls for a “new system science … to provide unified foundations, models, tools, system

Contributors to the Report “O.R. as a Catalyst for Engineering Grand Challenges,” a report to the National Science Foundation, was compiled by a team of contributors led

by Suvrajeet Sen of the University of Southern California: • • • • • • • • • • • •

Cynthia Barnhart, Massachusetts Institute of Technology John R. Birge, University of Chicago E. Andrew Boyd, PROS Michael C. Fu, University of Maryland Dorit S. Hochbaum, University of California-Berkeley David P. Morton, Northwestern University George L. Nemhauser, Georgia Institute of Technology Barry L. Nelson, Northwestern University Warren B. Powell, Princeton University Christine A. Shoemaker, National University of Singapore David D. Yao, Columbia University Stefanos A. Zenios, Stanford University

REFERENCES 1. U.S. White House, 2015, National Security Strategy.

2. Brown, G.G., Carlyle, W.M., Salmerón, J., Wood, R.K., 2006, “Defending critical infrastructure,” Interfaces, Vol. 36, pp. 530-544.

3. Pita, J., Jain, M., Western, C., Paruchuri, P., Marecki, J., Tambe, M., Ordonez, F., Kraus, S., 2008, “Security via randomization: A game-theoretic model and its application to the Los Angeles International Airport,” Proceedings of IEEE Conference on Technologies for Homeland Security.

4. McLay, L.A., Jacobson, S.H., Lee, A.J., 2010, “Risk-based policies for aviation security checkpoint screening,” Transportation Science, Vol. 44, pp. 333-349.

5. Murray, R., Haxton, T., Janke, R., Hart, W.E., Berry, J., Phillips, C., 2010, “Sensor network design for drinking water contamination warning systems: A compendium of research results and case studies using the TEVA-SPOT software,” (Technical Report EPA/600/R-09/141), National Homeland Security Research Center, Office of Research and Development, U.S. Environmental Protection Agency.

6. Alderson, D.L., Brown, G., and Carlyle, W.M., 2015, “Operational models of infrastructure resilience,” Risk Analysis, Vol. 35, pp. 562-586.

7. Brown, G.G., Carlyle, W.M., Harney, R., Skroch, E., Wood, R.K., 2009, “Interdicting a nuclear weapons project,” Operations Research, Vol. 57, pp. 866-877.

8. Atkinson, M.P., Cao, Z., Wein, L.M., 2008, “Optimal stopping analysis of a radiation detection system to protect cities from a nuclear terrorist attack,” Risk Analysis, Vol. 28, pp. 353-371.

9. Dimitrov, N.B., Michalopoulos, D., Morton, D.P., Nehme, M.V., Pan, F., Popova, E., Schneider, E.A., Thoreson, G.G., 2011, “Network deployment of radiation detectors with physics-based detection probability calculations,” Annals of Operations Research, 187, pp. 207-228.

10. Wein, L.M., Wilkins, A.H., Baveja, M., Flynn, S.E., 2006, “Preventing the importation of illicit nuclear materials in shipping containers,” Risk Analysis, Vol. 26, pp. 1,377-1,393.

11. Asgeirsson, E., Berry, J., Phillips, C.A., Phillips, D.J., Stein, C., Wein, J., 2004, “Scheduling an industrial production facility,” Proceedings of IPCO X, pp. 116–131.

12. National Science and Technology Council, 2012, “The Networking and Information Technology Research (NITR) and Development Program Strategic Plan.”

13. Executive Office of the President, National Science and Technology Council, 2011, “Trustworthy Cyberspace: Strategic Plan for the Federal Cybersecurity Research and Development Plan.”

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capabilities and architectures that enable innovation in highly dependable cyber-enabled engineered and natural systems.” The new science that the report promotes appears to be at the intersection of three perspectives: 1) O.R. models and algorithms; 2) systems and controls; and 3) computer science.

This multi-disciplinary approach has already started to take root, and we anticipate that this convergence will provide the foundations for cybersecurity.

Given the inherent vulnerabilities of cyber defenses, increased attention has been given to robust design.

While a centralized electric power grid has enormous economies of scale, this architecture can be vulnerable to cyberattacks and unintentional hazards. Distributed generation allows micro- and regional grids to remain up and running as the larger grid recovers from a disruption.

The proper design of a distributed generation network is precisely the type of network design problem long addressed by the O.R. community.

While software reliability has been studied in the O.R. community for decades, designing systems to handle cyber-threats is relatively uncharted territory. We expect that collaboration between O.R. groups and practitioners of cybersecurity will guide the manner in which security is designed into cybersystems.We draw attention to the following from the U.S. strategy for R&D to secure cyberspace [13]: “To operate effectively as a moving target in cyberspace, we must understand our system’s state, be aware of our surroundings, know the soundness of the structures on which we rely, and know what is happening around us ... Ultimately, we must provide knowledge-driven systems that remove the human from the loop in many system decisions. But for those decisions that do require human decision-making, the combination of high complexity and short processing time strains human cognitive processes, so we must provide novel methods of presenting information, directing attention, and navigating between analytics at different scales.”

The analytics cited highlight the interplay between data and decisions, calling for greater infusion of O.R. into cybersecurity.The challenges of cybersecurity rely on the ability to bring a variety of processes and resources together in a timely manner to enhance our ability to thwart adversaries, even as they are intent on continual barrages of attacks. Current statistical approaches for intrusion and anomaly detection often focus on attacks at a network node. However, denial-of-service attacks often cascade through a network, and so network-wide, i.e., higher dimensional, models become necessary.The O.R. community, especially the military O.R. community, has been a source of many ideas behind such cascading threats.This experience, together with O.R.’s close ties to computer science, should provide fertile ground for collaboration to face this important security challenge. ORMS ormstoday.informs.org

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Cognitive computing for automating customer knowledge Image © Jakub Jirsak | 123rf.com

If your customer relationship management (CRM) system could actually think, would Elon Musk and other AI detractors want to kill it?

Much has been made lately of the fearful admonitions about machine learning or AI by technology luminaries such as Musk, Stephen Hawking and Bill Gates. But would a CRM system – employing cognitive computing to do a better job helping customers get what they need faster – be dangerous? Would a CRM work flow that tells the advisor that a customer needs to adjust their portfolio to avoid a coming risk be a candidate to become emperor of the world? Of course not. Businesses are already using cognitive computing to make the bond with their customers Automated data science is the key to winning the battle for customer stronger by making themselves more valuable, and they are gaining loyalty at scale. new revenue with that strengthened bond.

Now to add some perspective, a cognitive computing platform is not a sentient being, but it is two generations beyond business analytics, and even one generation beyond machine learning. So what is it that cognitive computing delivers that makes it superior to previous generations of analytics and why should we embrace it? In three words, automated customer knowledge.

In today’s big data environment, companies are gathering and storing vast amounts of information about their customers, but it is rarely translated into actionable customer knowledge. Businesses know this information can help them better understand their customer, innovate products and services, and improve revenues, but they have not been able to accomplish that with previous technologies. What they require is a technology smart enough to make sense of all that data and transform it into actionable and measureable customer outcomes.

Cognitive computing does just that automatically, providing a clear means to make the most of a company’s proprietary data. Some innovators are already

By Guy Mounier disrupting their industries with this technology. They use it to intuit what customers need and to enhance customer insights in order to hone their cross-sell offers and increase revenues. At a time when corporations are trying harder than ever to keep and grow their customer base, this technology can offer a sustainable competitive advantage by capitalizing on existing relationships.

Cognitive Computing Implications for CRM There are many applications for cognitive computing, but one of the most compelling is its ability to make sense of the great volumes of customer data – both static and dynamic – to learn, think and recommend. Global banks are using the technol34 | ORMS Today

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ogy to connect external and internal information to accelerate revenue across corporate accounts managed by a diminishing number of bankers.Wealth management organizations are enriching their internal data with information about a customer’s key life events obtained from external public social and professional data sources, helping their advisors proactively up-sell to existing clients.

For customer care operations, cognitive computing platforms help companies substantially reduce the time and resources they spend achieving customer issue resolution. Even more interesting is that these organizations are finding that the technology can be used to convert their customer care centers into profit centers.

This nifty trick is accomplished by resolving customer issues quickly and proactively, making the customer feel known and appreciated, and then using the resulting “wow” moments to make up-sell recommendations during the very same client interaction.

The Cognitive Computing Advantage Automated data science is the key to winning the battle for customer loyalty at scale. Companies can learn from their data and enrich their learnings with information from external sources. Unlike traditional business intelligence or big data projects that take months or years to execute, cognitive computing helps companies attain payback within weeks. Businesses are using this technology to leverage existing human and technology investments in CRM, customer experience tools, big data analytics and more. In essence they paid for all that IT infrastructure, and cognitive computing allows them to fully capitalize on it.

Global corporations took some time to understand the benefits of cognitive computing, but that is now changing.Technology giants like IBM have used cognitive computing to help companies in a number of ways, e.g., the new “Chef Watson” app for Bon Appétit, utilization management decisions in lung cancer treatment and developmental assistance in Africa. Companies that are truly innovative don’t throw away or waste the vast amounts of data that they already have; instead, they are using cognitive computing to extract predictive value, i.e., answers to important business questions, and leverage their data for business gains in a more rapid fashion.

Not only does cognitive computing offer a competitive advantage, it also helps unlock the value of data to counter emerging threats from non-traditional market entrants and competitors. It is one of the key technology solutions used today by businesses across the world to fend off competition, increase revenue from existing customers and thrive in fast-changing market conditions.

The Technology Customer-facing employees often have to resolve issues in split seconds.They might struggle to identify

the best course of action, which impacts customer experience. Cognitive computing can help these front-line professionals by providing suggested actions or best practice recommendations. The technology does this by extracting actionable insights from structured and unstructured customer data. Sales agents and customer relationship professionals can use these best practice recommendations to identify up-sell and cross-sell opportunities.With this technology, companies can get a 360-degree view of their customer.

Cognitive computing technology can be used to create a customer knowledge layer that enriches data collected over years of customer interaction and domain experience. The platform combines data (which resides in the CRM, care or account management system) with files from various internal and external sources. Once the information has been enriched, the technology continuously applies data enrichments, predictive recommendation algorithms and unsupervised semantic learning. The process is both continuous and dynamic. Unlike other predictive analytics that are rules-based and static, this technology is self-learning, real-time and contextual.

Every interaction and result educates the platform, helping it become even more effective over time.

Since the technology is lightweight and quick to deploy, cognitive computing can impact business revenues within weeks. This is achieved using a compressed platform-based methodology. By choosing a technology partner that has relationships with key consulting firms and systems integrators, businesses can potentially get first use cases developed in weeks. Also, the cognitive computing technology is offered via a private cloud-based solution, making it easy for companies to deploy on their internal cloud or an industry standard external offering.

In

today’s big data

environment, companies are

gathering and storing vast

amounts of

information about their

customers, but it is

rarely translated

The Potential We have just begun addressing the potential use cases of cognitive computing in the business world.Those leading the way know this to be true because they are continually discovering new revenue-generating applications with customers across multiple industries. In an environment where businesses are finding it hard to gain new customers and even harder to retain existing customers, cognitive computing offers a chance to differentiate. Innovative companies understand that deeper customer knowledge is the key to surviving and thriving in this competitive landscape, and that cognitive computing not only enhances customer experience, but also delivers new revenue. ORMS

into actionable

customer knowledge.

Guy Mounier is co-founder and CEO at CustomerMatrix.

Before that, he co-founded and ran BA Insight – a leader in agile information integration. Mounier holds a master’s degree in mathematics from Harvard University and a master’s degree in computer science and electrical engineering from Ecole Centrale Paris. A version of this article appeared in Analytics magazine.

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Sustainable business models for the

Image © Roberto Rizzo | 123rf.com

Internet of Things

Are companies ready for billions of everyday objects to join the Internet?

By Tayfun Keskin, Fehmi Tanrısever and Haluk Demirkan 36 | ORMS Today

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There is an emerging market at the gate: the Internet of Things (IoT), which is expected to generate $14 trillion revenue in the next decade [2]. The IoT refers to the equipping of all objects and people in the world with some form of identifying devices or sensors that can be networked together (such as refrigerators and thermostats using the Internet) [5]. Even though the technologies required to enable IoT have been available for more than 10 years, managers are still in need of innovative business models to monetize IoT-enabled markets.

According to a recent MIT Technology Review Business report titled “The Internet of Things” [8], the IoT is planning to reshape the market with the network effects.A number of large enterprises, such as Google, Amazon, Uber, Apple, GE, Cisco and Philips are making large amounts of investments to IoT to get benefits from “platform economics” and “network effect.”

Despite the so-called “first mover advantage,” history shows that first movers of disruptive information technologies typically have had problems with monetizing their leadership role. Although these leaders might have a good grasp of the technology, they may fail to understand market dynamics, complementarities and the multi-sided nature of an IT-enabled industry. For example, AltaVista, one of the earliest search engines, could not recognize that sponsored links could be the key for monetization before Google took over the lead. Similarly, Netscape failed to identify strategic complementarities between the Internet browser and an operating system.

These examples demonstrate that firms may fail regardless of their technological purview unless they develop a viable business model. In other words, a technological invention may not be enough to succeed in the long term; and a well-developed business model is needed for sustainable growth.

The main objective of this article is to examine opportunities and challenges of different business models in the IoT-enabled markets, and provide a basic roadmap to managers for sustainable growth.

Components of the IoT Market IoT has potential to create never-before-seen synergies between three primary markets: durable goods, software and consumable goods [7]. The “Things” part is conventionally classified as durable goods. These are everyday objects we use, such as refrigerators, televisions and thermostats that include IoT products. ormstoday.informs.org

Typically, vendors of these durable goods only receive a one-time payment from the consumers because they generally do not anticipate other revenue streams from the sales of durable goods.

However, IoT-enabled durable goods create synergies with the consumable goods market.

Consumable goods can range from a simple basket of groceries to complex information services. For instance, a smart fridge can order groceries without the need of conventional human intervention. This synergy between smart fridge and groceries creates a two-sided market where one side of the market has the potential to subsidize the other.

Companies such as Amazon.com are already offering this service with Amazon Fresh. However, it is also possible for any store to offer the same product or service to the IoT-enabled grocery market.

It would not surprise us to see an Amazon-branded fridge connected to the Amazon.com ecosystem in the near future. These connections between the markets become more complex when we factor in the software that runs on the durable good. For example, a smart fridge can run on a proprietary or an Android operating system.

The software industry has substantial competing experience in two-sided markets [4]. Research on two-sided network effects and competitive platforms in markets enabled by information systems [3] includes one of the first studies that review the benefits and risks from network effects of IoT-enabled three-sided markets. Firms can benefit from these network effects in terms of scalable revenues once they recognize the synergistic connections, while consumers benefit from subsidized goods and services.

Business Models for the IoT The introduction of IoT markets has realigned the parties in supply chains, reinforcing new business links and relationships among them as shown in Figure 1. Firms can create different business models by offering different combinations of software, durable goods and consumable goods. In the paragraphs that follow, we discuss the economics of various business models and integration strategies in IoT markets from the perspective of the durable goods manufacturer (DGM).

Figure 1: IoT-enabled durable goods supply chain.

approach can better exploit the resources and create more compelling products and services to the consumers, possibly expanding the market for IoT solutions as well.

The IoT markets are characterized by high levels of technological and market uncertainty, as well as informational asymmetries about the prospects of the new venture. The supply market (software developers) is at its very infancy and is subject to unpredictable shocks and changes. In a disintegrated market, the development of an IoT solution requires the right set of components provided by both the SP and the DGM. A successful technology development hinges on information sharing between the supplier and the manufacturer about customer expectations and technological capabilities of the respective parties. Without such information, the final product will suffer from design and marketing issues (Table 1A).

B. Cross integration: Integrated durable and consumable (IDC) goods business model

DGM integrates IoT product with consumable goods provider (CGP) but uses generic software (Figure 2B). This model is similar to forward vertical integration in economics; however, CGP and DGM are not directly vertically aligned in the value chain. DGM sells durable goods with IoT capabilities to the CM, and then the consumers shop from CGP using the installed IoT product. Based

The introduction of

IoT markets has realigned the

parties in supply chains, reinforcing

new business links and

relationships among them.

A. Backward integration: Integrated software and durable goods (ISD) business model

DGM chooses to vertically integrate with a software provider (SP) and jointly develop an integrated durable good and software (Figure 2A).This enables DGM to in-house the development of software and optimize its features based on the provided durable goods and consumer market (CM). The integrated

Figure 2: Proposed business models.

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Internet of Things on the agreement between DGM and CGP, as the customers shop from CGP it creates a secondary revenue stream for DGM such as advertisements and any fees for using IoT solution and customer-usage data.

Cross integration does not mean that DGM and CGP are merged, and a single firm manages both manufacturing of durable goods and sales of consumable goods. Yes, Amazon does that sometimes.

In our case, cross integration refers to the customization of IoT to operate between DGM and CGP, to reduce any information sharing issues (Table 1B).

Cross integration helps to mitigate informational problems. As Harrigan [6] points out, managing customer expectations and information sharing can be more important than access to capital in this case.

C. Full integration: Integrated software, durable and consumable (ISDC) goods business model

This model (Figure 2C) represents the fully integrated business case in which the DGM provides a durable good that is integrated to operate with customized software and a certain CGP.The capabilities of the IoT value chain are fully optimized and customized (Table 1C).

D. Disintegration: Disintegrated software, durable and consumable goods business model

This business model (Figure 2D) represents the unbundled approach in which the DGM designs its product to operate with any software and CGP.The unbundled approach enables the SUPPLY TECHNOLOGY DEMAND consumers of the durable goods DEVELOPMENT to freely choose among different A. Backward Integration: Integrated Software and Durable Goods (ISD) Business Model IoT software and consumable goods providers to maximize his/ Risks Inflexibility to adapt to the Limited ability to benefit from Reduced ability to adapt successful changes in the software disruptive technological developments software in the market. If consumers her utility from the service. This supply market (e.g., switching and competition in the software decide to use generic software in business model provides the concost for third-party software market. the market, ISD may not be able to sumer with the highest flexibility in the market). adapt fast. when configuring his or her IoT Benefits Secured supply for the Facilitated technology development Increased ability to respond to product. For instance, the condevelopment of a specific through enhanced information sharing customer’s changing expectation product. and access to capital. about the features of the IoT product. sumer may keep updating his or her IoT software as new features B. Cross Integration: Integrated Durable and Consumable (IDC) Goods Business Model become available, similar to inRisks Increased risk of not finding Reduced control on the supply side Inflexible to adopt changes in stalling apps in smart phones, as a good third-party software of the technology development. The demand if the consumers change that works well with an success of the business model hinges their preferences and start shopping well as switching between differintegrated manufacturer on the development of the third-party from different consumable goods ent consumable goods providers retailer eco-system. software market. providers.

(Table 1D).

Benefits

Increased motivation for the supply market to develop products specific to the integrated system.

Facilitated technology development through enhanced information sharing between durable goods manufacturer and consumable goods provider.

Tailoring IoT to the specific needs and the configurations of the CGP.

Better information about consumer demand and expectations for the IoT. It enables DGM and CGP to better align and optimize their supply chains, and may result with better customer experience.

C. Full Integration: Integrated Software, Durable Goods and Consumable (ISDC) Goods Business Model Risks

Very high inflexibility to respond to the developments in the third-party software market.

High risk of asset specificity. Scalability is a major problem; this business model provides a highly customized product for the consumers who are willing to shop from a particular CGP.

High inflexibility to respond to the customer’s changing shopping preferences.

Benefits

Secured supply for the specific IoT product.

Facilitated technology development through enchanted information sharing across the supply chain.

Increased efficiency in assessing and meeting customer demand through a highly customized product.

D. Disintegration: Disintegrated Software, Durable Goods and Consumable Goods Business Model Risks

High supply risk due to loss of control in the software market.

High risk of delays in technology development due to lagging software and consumable goods markets.

Possible misalignment of the IoT product and customer expectations if the generic software developed in the market does not integrate well with the durable and consumable goods market.

Benefits

Increased flexibility to switch to successful third-party software providers.

Increased competition in the software market, which may facilitate technology development.

High flexibility to adapt to the changes in the customer’s preferences for the IoT software and the consumable goods providers.

Table 1: Possible risks and benefits of proposed business models.

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Technological and Managerial Challenges Each of these business models face a number of technological and managerial challenges and also create opportunities. Technological challenges may include massive scaling, openness, security and human interface [9]. Managerial challenges may include pricing, market presence, network effects and ever-present threat of envelopment. For example, smart fridges enable automatic grocery purchases. This is not only convenient for the consumer but also has the potential to change consumer valuation both for groceries and for the smart fridge.

IoT’s disruption provides opportunities for firms to become important players. The ormstoday.informs.org

secret is to predict “profit” and “subsidy” sides of the networked market correctly, and then shape the future network through network effects.

Durable goods manufacturers have always struggled with inherent properties of their products: long life expectancy and elastic demand.

Once a durable good is sold, it would take years, if not decades, for the same consumer to generate income for the firm. IoT offers continuous and relatively inelastic demand for a durable good manufacturer in a networked market.

Finally, focusing on the core competency gets another meaning in a multi-sided market. IoT creates synergies for markets and complementarities between products like never before. Firms face the risk of envelopment if they do not utilize these opportunities outside their core competencies.

Roadmap and Conclusion In the future, we expect the IoT industry will contain a few select firms that utilize the multi-tiered market. For example, a startup firm may dominate the market with a new smart fridge by selling it considerably under its cost, subsidized by future grocery sales.

The future direction of the IoT-enabled industry depends on how the market will evolve; which sides will be subsidized and which sides will bring revenues. If previous examples in the IT market are an indicator, software platforms have the biggest potential to set standards and disrupt other IoT-enabled markets such as durable and consumable goods.

We expect that players in the IoT market must be flexible in terms of their business processes.

Therefore, our final recommendation is as follows: Be flexible, and prepare yourself to change your firm’s business model as this networked market evolves.

IoT markets are in their infancy and are subject to high: (1) informational problems, (2) technology development risks, (3) market adaption risks, and (4) hurdle rates at the software development side. Compared to risks in the market, costs associated with integration and making an investment to develop asset specificity are not high. This implies that a fully integrated business model, as depicted in the top-right quadrant of Figure 3, is attractive for the firms. Indeed, Amazon entered the market with this model.

As the market matures and the risks above are mitigated, firms will need to expand their market shares, which require making IoT solutions compatible with other consumable goods providers. In the long run, firms will need to move to

Figure 3: Roadmap from fully integrated to disintegrated business model.

a fully integrated business model for sustainable growth. ORMS Tayfun Keskin (keskin@uw.edu) is an assistant professor of management information systems at the School of Business, University of Washington Bothell. He has a Ph.D. from the University of Texas at Austin’s McCombs School of Business.

Fehmi Tanrısever (tanrisever@bilkent.edu.tr) is an assistant professor of business administration at Bilkent University. He has a Ph.D. in supply chain and operations management from the McCombs School of Business.

Haluk Demirkan (haluk@uw.edu) is a professor of service innovation and business analytics at the Milgard School of Business, University of Washington Tacoma. He has a Ph.D. in information systems and operations management from the University of Florida. He is a longtime member of INFORMS.

REFERENCES 1. Andriole, S. J., 2015, “Who Owns IT?” Communications of the ACM, Vol. 58, No. 3 (March 2015), pp. 50-57.

2. Bort, J., 2013, “Cisco’s John Chambers Has Found a New $14 Trillion Market,” Business Insider (May 29, 2013); http://www.businessinsider.com/ciscos-john-chambers-has-found-a-new-14trillion-market-2013-5.

3. Economides, N. and Katsamakas, E., 2006, “Two-sided Competition of Proprietary vs. Open Source Technology Platforms and the Implications for the Software Industry,” Management Science, Vol. 52, No. 7, pp. 1057-1071.

4. Eisenmann, T., Parker, G. and Van Alstyne, M.W., 2006, “Strategies for Two-Sided Markets,” Harvard Business Review (October 2006).

5. Gartner, “Gartner Says the Internet of Things Installed Base Will Grow to 26 Billion Units by 2020,” Dec. 12, 2013 (retrieved June 25, 2015). http://www.gartner.com/newsroom/ id/2636073 6. Harrigan, K.R., 1986, “Matching vertical integration strategies to competitive conditions,” Strategic Management Journal, Vol. 7, No. 6, pp. 535-555.

7. Perera, A. Zaslavsky, Christen, P. and Georgakopoulos, D., 2014, “Context Aware Computing for the Internet of Things: A survey,” IEEE Communications, Surveys and Tutorials, Vol. 16, No. 1, pp. 414-454.

8. Regalado. A., 2014, “Business Adapts to a New Style of Computer,” MIT Technology Review Business report titled “The Internet of Things” (July-August 2014).

9. Stankovic, J.A., 2014, “Research Directions for the Internet of Things,” IEEE Internet of Things Journal, Vol. 1, No. 1, pp. 3-9.

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S

VEHICLE ROUTING SOFTWARE SURVEY

Biennial survey of vehicle routing software reveals many innovations in response to market demands.

Image © Yuri Bizgajmer | 123rf.com

By Randolph Hall and Janice Partyka

Higher expectations drive transformation In the two years since the last survey, vehicle routing has begun a transformation that mirrors changes occurring throughout the software industry, pushed forward by expectations set in consumer markets for transportation and retail. For instance, Waze (and its owner Google) has seen an explosion of followers in app-based, crowd-sourced navigation, residing on the mobile phone. Rather than relying on static maps that may be older than your car, Waze navigates and updates from information gathered from its users, and, as more users gravitate to its platform, the data becomes increasingly valuable (see accompanying sidebar article). For retail, Amazon’s same-day deliveries along with user-friendly interfaces for tracking and ordering have set new standards for customer empowerment.

We spoke with representatives of Omitracs Roadnet, Descartes, DNA-Evolutions, ALK and Appian TMW, and also surveyed vendors, to get the pulse of the industry. All of these companies offer software to solve variations of the “vehicle routing problem” – finding an optimal assignment of customers to vehicles, as well as the optimal sequence and schedule of customers served by each vehicle. The aim is to minimize transportation costs while satisfying feasibility constraints as to when and where stops are visited, what can be loaded in each vehicle, and what routes drivers can serve. Solutions are usually generated in advanced and executed as planned, though sometimes routes are dynamically updated throughout the day.

Routing software is used to plan deliveries from central locations, pick-ups from shippers, routes of service fleets (e.g., appliance repair), and bus and taxi schedules. The companies that use routing software vary greatly in size, ranging from small businesses with a fleet of 10 vans or fewer, to large corporations routing thousands of trucks. What these companies have in common is the need to coordinate and sequence tasks across multiple drivers and stops, ensuring predictable and expedient customer service at the lowest cost.

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Which way to go The Cloud Routing software emerged in the 1980s at a time when routing software resided on personal computers or on mainframes. While these options still exist, the direction has been toward cloud-based solutions or software-as-a-service (SaaS). As Cyndi Brandt of Omnitracs Roadnet tells us, “When customers have different versions of the software or only install part of the solution, it’s hard for us to support them. Our customers use 10 to 15 versions, and they don’t always update. By moving to SaaS, Omnitracs Roadnet can manage data better and offer better features.”

According to Brandt, half of Omnitracs Roadnet customers are using SaaS. Other companies have observed similar trends.

“The cloud has removed the barrier of infrastructure and systems are easier to deploy,” says James Stevenson at Appian TMW.“This is more important in large enterprises, such as those with multiple branches.”

Ken Wood of Descartes indicates that the majority of its customers are cloud based, but he sees potential for future hybrid solutions to enable integration.

“There are too many components outside the firewall that will be used as inputs to solutions,” he says.

By Randolph Hall

As a new graduate student at U.C. Berkeley in the early 1980s, I was intrigued by the possibility of empowering travelers with information as a way to improve transportation. My first publication, titled “Habituality of Traveler Decisions and Travel Time Reliability,” proposed a method motivated by three theories. First, travel can be more reliable and faster when exploiting the full diversity of a network, utilizing different routes at different times (i.e., breaking habits). Second, for stochastic and time-dependent networks, the fastest path from point A to B is not a path in the classic sense, but instead an adaptive strategy that permits changes based on information learned while en route. And last, when initiating a journey, one should not only care about the travel time along individual links of a path, but whether they offer multiple options along the way, thus permitting changes as you acquire new information.

Thirty-five years later, however, it was as though I had forgotten my own ideas, choosing the same route almost every day for 20 years traveling to work, and the same (but different) route traveling home. Then I discovered the mobile phone app Waze. Crowd-sourcing travel time data by tracking the movements of its users’ mobile phones, Waze offered me dynamic choices, as well as an estimated time of arrival that reflected current travel conditions. Soon I was navigating through back streets of Echo Park, Silver Lake and downtown Los Angeles that I would have never considered. I had gotten out of my rut, but had my journeys become better?

Waze has several challenges in getting its algorithms to produce the best choices. First, because travel times constantly change (especially around the start of rush periods), it is not sufficient to have a good estimate of travel times at time of departure; a forward projected travel times along all points of a route is also needed (a USC spin-off company, TallyGo, is working on this issue).

Second, travel times vary significantly along route segments depending on where you are heading next and which lane you have selected, and thus precise lane- and destination-based measurement is important. Third, travel time is partly a reflection of roadway congestion, but also a reflection of driver behavior, making the fastest route at least partly dependent on the individual. And last, owing to Waze’s own success, the system has the power to over-saturate streets (particularly the obscure ones) with traffic, resulting in unanticipated “Wazeinduced congestion.”

So am I still using Waze? Absolutely. It has broken my habits, made me aware of routes I had never considered, and given me information on traffic congestion at the moment I’m traveling. But I do often ignore its choices because my experience tells me alternate routes are likely to be better, and I am fully aware that its ETA will be overly optimistic at certain times of day and overly pessimistic at other times of day. And no matter how many times Waze tells me otherwise, I do know that my office is not situated on a freeway on-ramp.

Our survey of fleet routing software tells us that the crowd-sourcing revolution has not spread throughout industry. But vehicle routing is ripe for disruption, as fleet drivers, like the rest of us, are ready to break habits to get places faster. Once perfected, smartphones, coupled with crowd sourcing and cloud computing, provide the perfect platform to do so.

Smartphones With pervasive consumer adoption of smartphones, it is not surprising that the technology is affecting how vehicle routes are conveyed to drivers.

Marc Gerlach of DNA Evolutions has found that “the availability of cheap and powerful mobile devices will step-by-step replace fixed installed units.” In addition, he says, “most of our customers are providing telematics systems to communicate with the drivers on apps running on smartphones and tablets.”

Nevertheless, as Brandt indicates, rugged devices installed on vehicles still have a place “for proof of delivery, mobile forms or tracking how a truck is being driven, such as idling or speeding.” Device use also varies among transportation segments.As Stevenson tells us,“Long haul is less likely to use smartphones since they are required to comply with hours of service rules that require automated data logging connected to the engine bus.” However, tablets or “phablets” (cross between tablet and phone) can sometimes serve this purpose. Recent regulatory changes mandating automated data logging has created a push in this direction.

What we did not find in our surveys and interviews is a big move toward integrating Waze-style crowd-sourced data with fleet routing. One challenge is that travel time estimates produced for cars are not very accurate for trucks, which travel more slowly and must observe height and weight restrictions on roads.

ALK Technologies is a provider of mapping data specifically for trucks, as well as truck navigation products, such as “CoPilot Truck.” As Dan Popkin from ALK indicates, ALK has long provided mechanisms for customers to identify improvements

in maps, which are then implemented through ALK’s quality assurance process. More recently, ALK has offered “MapSure” as a more automated way for customers to edit their own map files and submit changes into ALK’s data sets. As far as crowd-sourced navigation for trucks, Popkin says,“These are things we are looking into. It’s an exciting opportunity for the future.”

Integration “Routing used to be just about creating a plan, but now it is about execution.” That’s the view of Omnitracs Roadnet’s Brandt, who lists proof of delivery, tracking and compliance as supplemental needs that demand system integration. Omnitracs, long a leader in the truck telematics industry, acquired Roadnet at the end of 2013, and Descartes acquired Airclic in 2014, with an eye toward these forms of integration.

Another emerging form of integration is “self-scheduling,” which Descartes’Wood describes as “a self-chosen delivery time.”

Wood also mentioned the need to satisfy “increased expectations Software Survey, continued on p. 46

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Routing Functions

Computa with 50 tion Time to S o Hard-timRoutes, 1,000 lve Problem Sto e Windo ws (Spe ps, Two-Hour cify Platf orm) What Ty p in the S es of Algorithm oftware s (Open E are Employed nded)?

Node R outing Arc Rou ting Same D ay Re-r outing Daily Ro uting Weekly Routing Route P lanning & Analy Ability to sis Create Te rritories Utilizes R e a ltim to Re-a ssign S e Traffic Inform tops Am Utilizes ong Dri ation R vers e a ltime Tra to Re-s ffic Info equenc rmation e Stops Provides fo r Drivers Dynamic Turn-byUtilizes Turn Inst H ructions Collecte istorical Travel d from M & obile De Stop Time vices

Space

Performance

Hard Dis k

Memory

Process or Spee d

Recomm ended H ardware

Maximum Size of Problem Solvable by the System c. Numb er of Sim ultaneo us Term inals

Window s iOS Android Web-ba sed Soft ware as a Servic e (SaaS ) a. Num ber of S tops

Software Product Listing

Platforms Supported

b. Num ber of V ehicles

Year Introduced

ArcGIS Network Analyst

1990 y y y y Unlmtd. Unlmtd.

Unlmtd. Windows Multi- 500 MB SSD or Linux. core per SIC, twice SSD 2 GHz plus 4 GB size of recomor for OS network mended. higher. data x64

ClearD Optima

2008 y y y y Unlmtd.

Unlmtd.

Unlmtd.

Descartes Routing, Mobile & Telematics

2005 y – y y Unlmtd.

Unlmtd.

Unlmtd. Depends Depends Depends Depends sub Algo- y y y y y y y y – y y on on on on second rithms customer customer customer customer used require- require- require- requirevary by ments ments ments ments scenario

DirectRoute

1996 y – – y 60,000

Unlmtd.

Unlmtd. Windows 7 OS or newer

DISC

2000 y y y y Unlmtd.

Unlmtd.

Unlmtd. Depends Depends Depends Depends A few MJC2- y y y y y y y y on on on on seconds, develapplica- applica- applica- applica- standard oped tion tion tion tion PC/laptop in-house algorithms

y y y

Epicenter SaaS Simulation Platform

2014 y y y y Unlmtd.

Unlmtd.

Unlmtd.

y y y

eRoute Logistics

2001 y – y y Unlmtd.

Unlmtd.

Unlmtd.

Intelligent Routing

2014 – – y y

–

–

Esri

Clear Destination Inc.

Descartes

TMW Systems

MJC2

Forio

WM Logistics

Intelligent Routing Products (PTY Ltd)

–

n/a

1 GHz

DNA Evolutions GmbH

logvrp

2010 – – – y Web app Web app Unlmtd.

500 100

Netakil

Web API Unlmtd.

ODL Studio

Web API Unlmtd.

2014 y – – – No set Unlmtd. limit but <2,000 recommended

Open Door Logistics

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February 2016

16 GB

n/a

n/a

Three 2.33 GHz 64 GB Dell PowerEdge 2950 servers Good internet connectivity

200 GB

6 + core y – y y y y y y algorithms

y y y

2 mins. Heuristic y y y y y y y y

y y y

Intel i7 4 GB+ 125 GB+ 5 mins.

Quadcore 2.8 GHz or higher

–

2006 y – – y Depends Depends Depends Multicore 2 GHz+ on on on platform applica- applica- application tion tion

JOpt

42 | ORMS Today

Intel processor

<5 mins.

n/a

1.5 TB

Proprietary

y y y y y y y y – y y

Depends Several y y y y y y y y upon how fast you want it!

5 mins.

(Assuming OD metrix built)

Close loop

y y y y y y y y

y y y

Latest 50 MB 5m+ Multiple y – – y – y – – – y y Google local (accept- HeurChrome network ance istics, Require- cache setting dynamic ment depen- select dent) 4 GB+

10 GB

<5 mins.

Combi- y – y y y y y – nation of construction, SA, GA

Enough Enough Enough Enough ~30 LS, to run to run to run to run mins., heurdecent decent decent decent depends istics, Web Web Web Web conSA, browser browser browser browser straints hybrid

Unlmtd. Modern Minimum Problem PC dual depencore dent, 2 GHz min.

4 GB

Up to 10 GB

y – y y y y y –

– – –

– – –

10 mins. Heuristic y – – y – y y – – – – should (Jsprit suffice library)

ormstoday.informs.org

Solution Algorithms

Mapping

Part of a Suite that Provides:

Features

Types of Fleets that Other Special Features Currently Use the Product

Usage

Most Significant Installations

S

Single S ite Lice nse (50 routes) a. License Fee Inclu de Map for One R egion?

Source of Mapp ing Use d in You r Offerin g b. Insta llation S upport Cost ($/h our) c. Typic a Installa l Support Hou rs tion (50 routes) Needed for Conside ration o f Driver Geogra Skills & phic Re Needs? striction Driver H s? ours of S (e.g.,rest e rv ic e Rules breaks, 11 -hour rule , etc.)?

Travel T imes fro m Extern al Sourc es?

If yes, w hat is th e sourc e?

Display Crowd-s ourced Informa tion?

If yes, w hat type of inform ation?

Are Ma p Stree t Views A RFID Sc vailable anner ?

Supply Chain M a n a g Custom ement S er Orde oftware r Proce Compute ssing S ystem Fire or r-Aided Dispa Emerge tch for Police, ncy Veh icles Assigns Individu a l D Turn-by rivers to -Turn R Routes oute Ins Load M truction anifest s Loading Plan for Trucklo ETA Auto ad maticall y Sent to Local P the Cus ickup a tomer n d Delivery Long-h aul Les s than Tru Long-h ckload aul Truc kload Courier Buses Taxis Service Fleets Emerge ncy Serv ices (pol 24 by 7 ice, fire, Live Cu etc.) stomer Support Service Drivers Using S iOS martph ones?

Android Window s Support Drivers Using Ta Utilize a blets? n App S tore for Mgmt.

Distribu Use Dev tion? ices to Monitor Drivers ?

Numbe r of Com panies Using S oftware

Pricing Information

Depend- y HERE, Depend- Depend- y y y y HERE, y Depend- y – – – – y y – – y y y – y y – y y y y y y y y y y 1001+ – ent on TomTom ent ent on TomTom, ent upon

deployor on the deployetc. the

ment Custom consul- ment source option Data tant option chosen Per stop y HERE pricing

$187.50 2 hours y y y y Source – per hour come from mobile devices

–

y y y y – y y y y y y y – y – – y – – y y y – y y y 101–500 Many big box retailers selling furniture appliances and mattresses

Call for pricing details

Call for pricing details

–

–

y y y – – y y – – y y y – y y – y – y y y y y y – y 1001+ DHL, Schwans, Ferrellgas, Home Depot, Best Buy, US Foods, Sears and many others

y y y y PC Miler –

–

y y y y – y y y – y y y y y – – y – y y y y y y y y 501–1000 –

– Call for pricing details

Contact y ALK PC Contact us for Miler us for pricing Streets pricing

POA

–

–

It’s based y Google on the Maps number of users

–

y Navteq and Bing

$65/ y OSM vehicle/ (Mapbox) month

POA

n/a

–

$100

Call y y y y Google for Maps support details

24 hours

POA

y y y y Several y Several y y y y – y y y y y y y y y y – y – y y y y y y – y 101–500 All our customers have large operations with 100s or 1,000s of vehicles

Web- – y – y Google y Multiple y y y – – y y y – y y – – y – – y – – y y y y y – y 1–100 Boeing, Liberty email or Maps & Mutual, Harvard, 8-5 PST Waze Wharton support

–

–

–

y – y – y y y y – – y – – y y – y y – – – – – y – – 1–100 –

16 Hr y y y y Android – (address Users’ quality Choice depend(e.g. ent) Google)

–

y – – – – y y y – – y – – – – – y – – y – y – y y y 1–100 62 Waters (62.co.za)

– – – – – y – – – – y y y y – – y – – – – – – – – – 101–500 Amazon Fresh, Pitney Bowes, Henry Schein Animal Health & various confidential software producers in different branches.

– – – – – – y y – – y y y y y y y – – – – – – – – – 1–100 International companies + SMEs. Specifics are confidential. Major industries: couriers, distributors, passenger freight

y – – – – y – – – – y y y – y – y – – – – – – – – – 101–500 –

– y y –

–

Case – Google Included Included y y y y Google specific Maps, in $600 in $600 Maps $10,000 Open trial trial to Street package package $30,000 Maps

–

–

Starting y Google $20 to Maps $500/ month

–

–

–

–

None (Webbased SaaS)

None (Webbased SaaS)

y y y y Google Maps

No y Open Contact 0 - 4 hrs y y – – license Street Open cost Map Door software (free Logistics is free data).

–

February 2016

|

ORMS Today

| 43

OptimoRoute

2013 – – – y 5,000

Optrak

Optrak Distribution Software Ltd.

1992 y – – y No fixed No fixed limit. limit.

Will run Will run >4,000 > 200

Paragon HDX

2002 y – – y 20,000

30,000

2,000

Paragon Routing and Scheduling Optimizer 1983 y – – – 20,000

30,000

2,000

Roadnet Anywhere

2008 y – – y Unlmtd.

Unlmtd.

Unlmtd.

–

Roadnet Transportation Suite

1985 y y y – Unlmtd.

Unlmtd.

Unlmtd.

Route4Me

2009 y y y y 10,000

1,000

Unlmtd.

Routist

2013 – – – y Unlmtd.

Unlmtd.

Unlmtd. Standard PC with a Webbrowser

Routyn

2010 y y y y Unlmtd.

Unlmtd.

Unlmtd.

OptimoRoute Inc.

Paragon Software Systems, Inc.

Paragon Software Systems, Inc.

Omnitracs Roadnet

Omnitracs Roadnet

Route4Me

Fleetmatics

Wide Scope

Unlmtd.

Unlmtd.

n/a

Sci–Log (Scientific Logistics) Scientific Logistics, Inc.

No No 2011 – – – y No practical practical practical limit limit limit

STARS 6.0

1995 y – – y Unlmtd.

SAITECH, inc.

44 | ORMS Today

|

February 2016

Unlmtd.

Unlmtd.

Not applicable / Cloud service

Not applicable / Cloud service

i5 2 GHz processor

Not applicable / Cloud service

Routing Functions

Computa with 50 tion Time to S o Hard-timRoutes, 1,000 lve Problem Sto e Windo ws (Spe ps, Two-Hour cify Platf orm) What Ty p in the S es of Algorithm oftware s (Open E are Employed nded)?

Node R outing Arc Rou ting Same D ay Re-r outing Daily Ro uting Weekly Routing Route P lanning & Analy Ability to sis Create Te rritories Utilizes R e a ltim to Re-a ssign S e Traffic Inform tops Am Utilizes ong Dri ation R vers e a ltime Tra to Re-s ffic Info equenc rmation e Stops Provides fo r Drivers Dynamic Turn-byUtilizes Turn Inst H ructions Collecte istorical Travel d from M & obile De Stop Time vices

Space

Performance

Hard Dis k

Memory

Process or Spee d

Recomm ended H ardware

Maximum Size of Problem Solvable by the System c. Numb er of Sim ultaneo us Term inals

Window s iOS Android Web-ba sed Soft ware as a Servic e (SaaS ) a. Num ber of S tops

Software Product Listing

Platforms Supported

b. Num ber of V ehicles

Year Introduced

Not 2 mins. applion cable / OptimoCloud Route service cloud

–

y – y y y y y – – y –

8 GB

20 GB

15 mins. Construc- y – y y y y – – – – y depend- tion ing heuron istics, conLNS straints

PC/ Fast WinIntel dows Core, e.g.

Server 3.6 GHz

2 GB Min

50 GB

About 2 mins.

Propri- y – y y y y y – – – y etary Heuristic

PC/ Fast WinIntel dows Core, e.g.

Server 3.6 GHz

2 GB Min

50 GB

About 2 mins.

Propri- y y y y y y y – – – y etary Heuristic

–

–

–

1 minute

Custom y – y y – y – – – y – heuristics

–

–

–

–

1 Custom y – y y y y y – – – – minute heuristics

Webbrowser or Mobile Smartphone

Any

Any

Any

–

–

–

8 GB RAM + 2.9 GHz GPU

Any

n/a

n/a

n/a

Windows PC

Fast

2 GB+

20 secs. Proprietary Metaheuristics

y y y y y y y y

3 to 5 mins. SaaS

y – y y – y y – – – y

Proprietary metaheuristic

8 GB 100 MB 10 mins. Meta- y – y y y y y y RAM with heurper each 8 GB istics, 2,000 RAM, linear stops 2.9GHz programCPU ming n/a

y y y

y y y

1-15 mins. (# of CPUs used)

Propri- y – y y y y y – etary parallel computing

– – y

10 GB + 1 sec a few mins.

Local y y y y y y y search, MIP

y – –

ormstoday.informs.org

Solution Algorithms

Mapping

Part of a Suite that Provides:

Features

Types of Fleets that Other Special Features Currently Use the Product

Usage

Most Significant Installations

S

Single S ite Lice nse (50 routes) a. License Fee Inclu de Map for One R egion?

Source of Mapp ing Use d in You r Offerin g b. Insta llation S upport Cost ($/h our) c. Typic a Installa l Support Hou rs tion (50 routes) Needed for Conside ration o f Driver Geogra Skills & phic Re Needs? striction Driver H s? ours of S (e.g.,rest e rv ic e Rules breaks, 11 -hour rule , etc.)?

Travel T imes fro m Extern al Sourc es?

If yes, w hat is th e sourc e?

Display Crowd-s ourced Informa tion?

If yes, w hat type of inform ation?

Are Ma p Stree t Views A RFID Sc vailable anner ?

Supply Chain M a n a g Custom ement S er Orde oftware r Proce Compute ssing S ystem Fire or r-Aided Dispa Emerge tch for Police, ncy Veh icles Assigns Individu a l D Turn-by rivers to -Turn R Routes oute Ins Load M truction anifest s Loading Plan for Trucklo ETA Auto ad maticall y Sent to Local P the Cus ickup a tomer n d Delivery Long-h aul Les s than Tru Long-h ckload aul Truc kload Courier Buses Taxis Service Fleets Emerge ncy Serv ices (pol 24 by 7 ice, fire, Live Cu etc.) stomer Support Service Drivers Using S iOS martph ones?

Android Window s Support Drivers Using Ta Utilize a blets? n App S tore for Mgmt.

Distribu Use Dev tion? ices to Monitor Drivers ?

Numbe r of Com panies Using S oftware

Pricing Information

$950$1,950 per month

y y y –

–

–

–

– – – – – y y y – – y – – y y – y – – y y y y y – – 101-500 –

On appli- – HERE On appli- 120 y y y – cation (non UK), cation includes Ordnance customSurvey izations (UK)

–

–

–

y – – – – y y y y y y y y y – – – – – y y y y y – – 1-100 Matthew Clark, Fuchs Oils, NOCO, Wakefield Candad

Depends y HERE on client requirements

POA

y

–

y HERE

–

–

–

–

Included in the license

2

Will depend on client requirement.

Depend- y y y – ent on complexity and size

–

Will depend on client requirement.

Depend- y y – – ent on complexity and size

–

–

–

– – – – – y y y – y y y y y – – y – – y – y y y – y 1-100 IKEA, Dreams, Argos

y – – – – – y y – y y y y y y – y – y y – y y y – y 101-500 Martin-Brower, McLane, George’s Inc., DHL, CEVA, Toyota Materials Handling, National Food Corp, Agreliant, Tesco, Sainsbury’s

–

–

–

–

– – – – – y y y – y y – – – – – – – y y y y y y y –

–

–

– y y y INRIX

– TomTom, HERE

–

–

y y – –

–

–

– – – – – y y y y y y y – – – – – – y y y y y y y y 1001+ –

$500 – OSM per SMB, and Unlmtd.

All Major drivers Vendors

0

0

y y – y Commer- – cial and Proprietary

–

Contact – Fleetmatics

–

–

y y y –

y – y y y y y y y y y y y y y y y y y y y y y y y y 1001+ One customer plans 2M routes per year, another plans 5,000 stop routes daily for parcel fullfilment

y – – – – y y – – – – – – y – – y – y y y y y y y y 1-100 –

€300

24

y y y y TomTom, y Road y – – – – y y y y y y y y y – – y – y y y y y y y y 1-100 Large drinks INRIX blocks, distributors, 3PL Traffic operators, dairy producers, wholesale distributors, longhaul carriers, etc.

–

€47,500 y Open Street Maps

Contact y Various Contact Contact y y y –

Call

– Call for Included specifics in the licensing fee

1 day

–

–

–

y y y y Call

–

–

–

–

–

–

y – – – – y y y – – y y y y – – y – – – – – – – – – 1–100 Walmart, Pepsi Beverages, Reinhart Foodservice, Young’s Market, RaceTrac

–

–

y – y – – y y y y – y y y y – – y y – y y y y y – – 1–100 Just-in-time manufacturing, express, carrier, petroleum company

February 2016

|

ORMS Today

| 45

Computa with 50 tion Time to S o Hard-timRoutes, 1,000 lve Problem Sto e Windo ws (Spe ps, Two-Hour cify Platf orm) What Ty p in the S es of Algorithm oftware s (Open E are Employed nded)?

Node R outing Arc Rou ting Same D ay Re-r outing Daily Ro uting Weekly Routing Route P lanning & Analy Ability to sis Create Te rritories Utilizes R e a ltim to Re-a ssign S e Traffic Inform tops Am Utilizes ong Dri ation R vers e a ltime Tra to Re-s ffic Info equenc rmation e Stops Provides fo r Drivers Dynamic Turn-byUtilizes Turn Inst H ructions Collecte istorical Travel d from M & obile De Stop Time vices

Routing Functions

Hard Dis k

Space

Performance

Memory

Process or Spee d

Recomm ended H ardware

Maximum Size of Problem Solvable by the System c. Numb er of Sim ultaneo us Term inals

Window s iOS Android Web-ba sed Soft ware as a Servic e (SaaS ) a. Num ber of S tops

Software Product Listing

Platforms Supported

b. Num ber of V ehicles

Year Introduced

StreetSync Pro

2011 y y y y Unlmtd.

Unlmtd.

Unlmtd.

PC w/ HighSpeed Internet Access

2GHz+

2GB+

2GB+

Several mins.

Proprietary

y – y y y y y y

y y y

StreetSync Standard

2014 y y y y Unlmtd.

Unlmtd.

Unlmtd.

PC w/ HighSpeed Internet Access

2GHz+

2GB+

2GB+

Several mins.

Proprietary

y – y y y y y y

y y y

Truckstops

1983 y – – – Unlmtd.

Unlmtd.

Implementation dependent

Implementation dependent

Set by user, min.

1-5 mins.

Proprietary heuristics

y y y y y y y y

y y y

RouteSolutions

RouteSolutions

Mapmechanics

S

VEHICLE ROUTING

No PC, Implefixed Server mentahardware optional tion dependent

Software Survey, continued from p. 41

of delivery as a continued expansion of the Amazon model.” In addition,Appian TMW’s Stevenson relates,“companies now want full end-to-end solutions.They want the day’s activities fed into a complete feedback loop.”This means providing information on actual performance that can be used to improve future routing.

Gerlach of DNA-Evolutions sees the future challenge as the “interfacing of all systems along the supply chain. This will lead to more cloud- and web-based offerings on one hand, and the dispatching process will have to consider more aspects and data will thus become more complex.” One example is integration with the energy industry, where routing and production planning need to be optimized together.

This Year’s Survey Twenty-two companies participated in this year’s online survey, ranging from small vendors (less than 100 customers) to large corporations (1,000+ customers). We asked for demographic information on the companies (such as contact information and date of introduction), platform (hardware, operating system, driver devices, maps), features and capabilities, and installations.

We also asked several open-ended questions, inviting comments on recent and expected industry changes, innovations and impacts of the economy on the industry. Keep in mind that results are all self-reported and unverified.

What’s notable in this year’s survey?

Operating systems: Almost everyone offers a SaaS solution, most provide a Windows solution, and half have solutions implemented on mobile devices (iOS or Android).

Digital maps: Solutions are diverging. HERE, TomTom, ALK, Google Maps and OpenStreetMaps were some of those mentioned.

Special features and innovations: These included integrated telematics, bulk load routing, integrated workforce 46 | ORMS Today

|

February 2016

management, integrated call centers and ultra low-latency route optimization.

Installations: Most common are private fleets transporting consumer goods (think of Home Depot, Walmart, Coca-Cola, Walgreens), but for-hire carriers were also mentioned (DHS, R+L), as well as transporters of industrial goods. It was less common for companies to support taxi or bus fleets, but some do.

As to where the industry is heading, predictions include heading toward “connected fleet solutions,” integration of real-time information, cloud offerings and mobile offerings via smart phones.

“Amazon Now” was mentioned as an influence, creating a standard for coordinated immediate delivery. Descartes emphasized the need to harmonize the consumer’s delivery experience across multiple channels of transportation. And, as James Stevenson explained,“We are now seeing same-day delivery that bypasses distribution centers. It is the ultra last-minute transportation, a bit like Uber, that’s setting the direction.” Amazon,Waze and Uber – all software-driven companies that depend on routing – are setting new standards for the industry.

In selecting a vehicle routing product, look for vendors that have experience serving similar industries to your own, and test the software on a representative data set to assess the quality and speed of solutions. Ask for references and determine whether any prior customers have switched to another product and why.

And look ahead to see whether the company has the capability to maintain and update the software to meet your future needs.

Consider total cost of ownership, including license costs, staff support and future upgrades and maintenance. ORMS Randolph Hall (rwhall@usc.edu) is vice president of research for the University of Southern California, as well as professor in the Epstein Department of Industrial and Systems Engineering. Janice Partyka (jpartyka@jgpservices.net) is principal of JGP Services (www.jgpservices. net), a consulting group that helps companies with product strategy, market research and communications.

ormstoday.informs.org

Solution Algorithms

Mapping

Part of a Suite that Provides:

Features

Types of Fleets that Other Special Features Currently Use the Product

Usage

Most Significant Installations

Single S ite Lice nse (50 routes) a. License Fee Inclu de Map for One R egion?

Source of Mapp ing Use d in You r Offerin g b. Insta llation S upport Cost ($/h our) c. Typic a Installa l Support Hou rs tion (50 routes) Needed for Conside ration o f Driver Geogra Skills & phic Re Needs? striction Driver H s? ours of S (e.g.,rest e rv ic e Rules breaks, 11 -hour rule , etc.)?

Travel T imes fro m Extern al Sourc es?

If yes, w hat is th e sourc e?

Display Crowd-s ourced Informa tion?

If yes, w hat type of inform ation?

Are Ma p Stree t Views A RFID Sc vailable anner ?

Supply Chain M a n a g Custom ement S er Orde oftware r Proce Compute ssing S ystem Fire or r-Aided Dispa Emerge tch for Police, ncy Veh icles Assigns Individu a l D Turn-by rivers to -Turn R Routes oute Ins Load M truction anifest s Loading Plan for Trucklo ETA Auto ad maticall y Sent to Local P the Cus ickup a tomer n d Delivery Long-h aul Les s than Tru Long-h ckload aul Truc kload Courier Buses Taxis Service Fleets Emerge ncy Serv ices (pol 24 by 7 ice, fire, Live Cu etc.) stomer Support Service Drivers Using S iOS martph ones?

Android Window s Support Drivers Using Ta Utilize a blets? n App S tore for Mgmt.

Distribu Use Dev tion? ices to Monitor Drivers ?

Numbe r of Com panies Using S oftware

Pricing Information

Route y HERE Included Typically y y y y Via y Via y y – y – y y y – y y y y y – – y – – y y y y y y y 101-500 Numotion, Solutions. (formerly unnecTomTom TomTom Ole Mexican, com NAVTEQ) essary TelematTelematR.H. Barringer, lists ics ics SteriHealth pricing integraintegra tion tion

Route y HERE Included Typically – – – y Via our y Via our y y – y – y y y – y y y y y – – y – – y y y y y y y 101-500 Coca-Cola Solutions. (formerly unnecTomTom TomTom Enterprises, com NAVTEQ) essary integraintegraGhirardelli lists tion tion Chocolate, Mosquito pricing Squad, State of Michigan

Contact y HERE Included Varies, y y y y HERE y Display y y y y – y y y y y y y y y – – y – – y y y y y – y 1001+ Walgreens, R + L Maps in please Platform of traffic Truckload Services, or purchase contact situation Agrifoods, Kurt local price Weiss, TNT supplier

VENDOR DIRECTORY Forio 1159 Howard Street San Francisco, CA 94103 415.440.7500, x87 george@forio.com www.forio.com

Intelligent Routing Products (PTY Ltd.) 15 PC, Rietvlei Heights Centurion, Pretoria Gauteng 157 South Africa +27 12 743 6789 info@intelligentrouting.co.za intelligentrouting.co.za

Clear Destination Inc. 4000 St-Ambroise, Suite 389 Montreal, QC H4C2C7 Canada 514.933.8686 info@cleardestination.com www.cleardestination.com

Descartes 120 Randall Dr. Waterloo, ON N2V1C6 Canada 800.419.8495 info@descartes.com www.descartes.com

DNA Evolutions GmbH Bei der Laug 56 Ulm 89081 Germany +49 731 3890813 sales@dna-evolutions.com www.dna-evolutions.com

Esri 380 New York Street Redlands, CA 92373 909.793.2853 www.esri.com

Fleetmatics 1100 Winter St., Suite 4600 Waltham, MA 02451 866.844.2235 reveal.support@fleetmatics.com www.fleetmatics.com

Mapmechanics 4500 140th Avenue, Ste. 101 Clearwater, FL 33762 727.483.5562 info@mapmechanics.com www.truckstopsrouting.com

MJC2 33 Wellington Business Park Crowthorne Berkshire RG45 6LS UK info@mjc2.com www.mjc2.com/vehicle-routing-software.htm

Netakil Çamlaraltı Mah. Hüseyin Yılmaz Cad. No: 67, Pamukkale Teknokent B Blok Z-13 20160 Pamukkale, Denizli, Turkey +90 258 215 50 27 info@logvrp.com www.logvrp.com

Omnitracs Roadnet 849 Fairmount Ave Towson, MD 21286 410.847.1900 www.omnitracs.com/platforms/roadnettransportation-suite

Open Door Logistics

Scientific Logistics, Inc.

Unit 5 Tarlings Yard, Church Road, Bishops Cleeve Cheltenham Gloucestershire GL52 8RN UK +44 208 144 4009 info@opendoorlogistics.com www.opendoorlogistics.com

75 Fifth Street, Suite 363 Atlanta, GA 30067 info@scientific-logistics.com www.scientific-logistics.com

TMW Systems 6085 Parkland Blvd.

Mayfield Heights, OH 44124 216.831.6606 www.tmwsystems.com

OptimoRoute Inc. 2657 Alma Street Palo Alto, CA 94306 sales@optimoroute.com www.optimoroute.com

Wide Scope Avenida 5 de Outubro, 72 - 7C Lisbon 1050-059 Portugal (+351)213156312 info@routyn.com www.routyn.com

Optrak Distribution Software Ltd. Suite 6 The Maltings, Hoe Lane Ware SG12 9LR UK 01992 517100 vrs-sales@optrak.com www.optrak.com

WM Logistics

Paragon Software Systems, Inc. 2591 Dallas Parkway, Suite 300 Frisco, TX 75034 972.731.4308 sales@paragonrouting.com www.paragontruckrouting.com

5910 FM 1488 RD Magnolia, TX 77354 713.559.4260 wmlcontact@wm.com wmlogistics.wm.com/index.jsp

Route4Me P.O. Box 3014 Fort Lee, NJ 07024 212.201.0714 support@route4me.com www.route4me.com/

RouteSolutions 3460 Marron Rd., Suite 103-137 Oceanside, CA 92056 858.541.2738 info@routesolutions.com www.routesolutions.com

SAITECH, inc.

P.O. Box 431 Holmdel, NJ 07733 732.410.9192 www.saitech-inc.com

February 2016

|

ORMS Today

| 47

REGISTER TODAY!

EVERY BUSINESS… EVERY ORGANIZATION… AND EVERY ANALYTICS PROFESSIONAL...

Experiences the ups and downs, and the twists and turns of analytics. Making analytics work in real organizations can be a dynamic (dare we say wild?) ride for even the most seasoned practitioners.

Analytics 2016 will help you conquer the challenge.

OPENING KEYNOTE

Paul Ballew, Global Chief Data & Analytics Officer, Ford Motor Company

TUESDAY KEYNOTE:

"OR IN TODAY'S DYNAMIC BUSINESS ENVIRONMENT"

Samuel K. Eldersveld, Ph.D., Lead, Director of Operations Research, Uber Technologies, Inc.

meetings.informs.org/analytics2016

ormstoday.informs.org

news Business analytics conference to focus on real-world solutions Every business, every organization and every analytics professional experiences the ups and downs and the twists and turns of analytics. Making analytics work in real organizations can be a dynamic ride for even the most seasoned practitioners. The 2016 INFORMS Conference on Business Analytics and Operations Research, set for April 10-12 at the Hyatt Regency Grand Cypress in Orlando, Fla., will help you to conquer the challenge.

The conference consistently delivers proven applications and processes that will improve your business’s bottom line. This year nearly 1,000 leading analytics professionals and industry experts will come together to share ideas, network and learn about a wide range of problem-solving techniques and methods.

With presentations that revolve around real-world solutions, attendees will hear the full story behind successful analytics projects. This, in turn, will help attendees gain insight and drive business planning.

This year’s world-class lineup of speakers and strategic thought leaders will present talks on a wide range of problem-solving techniques and methods. Invited tracks on analytics leadership and soft skills, decisions and risk analysis, fraud detection and life sciences, Internet of Things, marketing analytics, revenue management and pricing, sports and entertainment and supply chain analytics will be of great interest to anyone looking to make analytics work in their organization. The program will be rounded out by about 30 hand-picked, member-contributed talks, in-depth technology workshops, poster presentations, panels and several opportunities for networking.

Keynote speakers Paul Ballew of Ford and Samuel Eldersveld of Uber will headline this year’s event, with talks scheduled for April 11

(Ballew) and April 12 (Eldersveld).

Paul Ballew is the global chief data and analytics officer at Ford Motor C o m p a n y. A p pointed in December 2014, Ballew leads Ford’s global Paul Ballew data and analytics teams including development of new capabilities supporting connectivity and smart mobility. Prior to joining Ford, he was chief data, insight & analytics officer at Dun & Bradstreet. In this capacity he was Samuel Eldersveld responsible for the company’s global data and analytic activities along with the company’s strategic consulting practice. Previously, Ballew served as Nationwide’s senior vice president for customer insight and analytics. He directed customer analytics, market research, and information and data management functions, and supported the company’s marketing strategy. His responsibilities included development of Nationwide’s customer analytics, data operations and strategy.

Ballew joined Nationwide in November 2007 and established the company’s customer insights and analytics capabilities.

Samuel K. Eldersveld received his Ph.D. in operations research from Stanford University in 1992. Dr. Eldersveld

Inside News

52 International conference

52 Roundtable retreat

53 Marketing makeover

54 Subdivision awards

61 People

61 Meetings

For your career and your company The following special events will be held in conjunction with the INFORMS Conference on Analytics and O.R. in Orlando, Fla.:

Analytics Certification CAP® Exam Certified Analytics Professional Saturday, April 9, 9 a.m.-noon, Hyatt Regency Grand Cypress What is a Certified Analytics Professional and an Associate Certified Analytics Professional?

Employers need help with identifying and developing qualified analytics professionals who can add value. INFORMS, the largest association in the world for those in analytics, operations research and the management sciences, offers the Certified Analytics Professional (CAP) program and the Associate Certified Analytics Professional program for emerging professionals.

For information and to apply: certification@mail.informs.org

INFORMS Continuing Education INFORMS will be offering two continuing education (CE) courses, “Essential Practice Skills for High-Impact Analytics Projects” and “Foundations of Modern Predictive Analytics” after the conference in Orlando on April 13 and 14. Conference attendees can save more than 25 percent off the regular price of a CE course through special bundled pricing.

Both courses will be held April 13-14 from 8:30 a.m.-4:30 p.m. at the University of Central Florida Executive Development Center.

For information and to register, visit: continuinged@informs.org.

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n ews Business Analytics Conference 2016 Conference, continued from p. 49

worked as a mathematician for manufacturing and planning at Boeing from 19912000 in the Phantom Works division. He joined Expedia as a startup and spent time at Starbucks before moving to Amazon as a principal research scientist in Seattle. Dr. Eldersveld joined Uber Technologies Inc. in 2015 to work with the data sciences teams in San Francisco. Dr. Eldersveld was also affiliated with the University of Washington Foster School of Business as a nontenure-track auxiliary faculty member and lecturer in the department of Information Systems and Operations Management from 2005-2008.

This yearâ&#x20AC;&#x2122;s conference is chaired by Elea Feit, assistant professor of marketing at LeBow College of Business, Drexel University. Other committee members

The Hyatt Regency Grand Cypress in Orlando, Fla., will host the conference.

Focused tracks & speakers Analytics Leadership & Soft Skills

Health Care & Life Sciences

Office of Creative Research - Ian Ardouin-Fumat General Services Administration - Johan Bos-Beijer Columbia University - Kaiser Fung Naval Postgraduate School - Jeffrey Kline, Professor of Practice, O.R. Princeton Consultants - Irvin Lustig, Optimization Principal Deloitte - David Steier

Decision & Risk Analysis American Airlines - Tim Niznik, Director of Operations & Decision Support University of Arkansas, IDI - Greg Parnell, Research Professor, Department of Industrial Engineering & Director, M.S. in Operations Management Bill & Melinda Gates Foundation - Chris Sailer Innovative Decision Analysis - Terry Bresnick, President U.S. Census Bureau - Nancy Potok, Deputy Director & Chief Operating Officer

Fraud Detection & Cyber Security The MITRE Corporation - Rob Case, Chief Scientist LexisNexis - Mark Isbitts, Director of Market Planning KPMG LLP - Brian Murrow, Principal, Financial Risk Management FICO - Scott Zoldi, Chief Analytics Officer

NORC - Jon Gabel, Senior Fellow, Healthcare Abbott Laboratories - Devjeet Haldar, Divisional VP, Business Analytics & Information Management Cedars-Sinai Medical Center - Chirag Patil, Board Certified Neurosurgeon; Lead Investigator, Precision Science Initiative for Brain Cancer; Program Director, Neurosurgery Training Program; Director, Center for Neurosurgical Outcomes Research MPA Healthcare Solutions - Gregory Pine, CEO Mayo Clinic - Nilay Shah, Associate Professor of Health Services Research

Internet of Things Intel Corporation - Peggy Irelan, Senior Principal Engineer, Director & CTO, IoT Intelligent Software Platforms & Analytics Solutions The Kroger Company - Doug Meiser, O.R. Manager John Osbourne II, Chairman, The ZigBee Alliance & General Manager, Research & Development

Marketing Analytics General Motors - James Lemieux, Senior Applied O.R. Professional Seneca College - Daymond Ling, Professor, School of Marketing Equifax - Trevis Litherland, Senior Data Scientist Alex Vayner, Vice President, Data Scientist Innovation Leader

Python Predictions - Pieter Van Bouwel, Senior Analyst University of Maryland - Michel Wedel, PepsiCo Professor of Consumer Science

Revenue Management & Pricing Turner Broadcasting System - Wes Chaar, Director of O.R. United Airlines- David O. King, Managing Director, Cargo Revenue Management & Sales Strategy Predictix- Robert Menich, Chief Data Scientist MIT - Georgia Perakis, William F. Pounds Professor of O.R. InterContinental Hotels Group - Andrew Rubinacci, SVP, Distribution & Revenue Management Strategy

Sports & Entertainment Florida Panthers - Brian Macdonald, Director of Hockey Analytics Walt Disney Studios- Tracy Wilson, SVP, Global Marketing Finance

Supply Chain Analytics Caterpillar - Craig Brabec, Chief of Analytics Gartner - Noha Tohamy, Vice President, Supply Chain Research The Walt Disney Company - Kory Whitacre, Project Manager, Supply Chain Innovation & Technology University of Tennessee-Knoxville - Sean Willems, Haslam Chair in Supply Chain Analytics

Plus 30 additional talks and 60 poster presentations!

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Award-winning Applications include analysts and managers from companies such as InterContinental Hotels Group, Walt Disney World, Walmart, Mayo Clinic, Exponent, Chevron, Accenture, The Kroger Company, Intel Corporation, Schneider National, Deloitte Consulting, BlueLabs, MITRE and Lockheed Martin, as well as leading universities and government agencies.

The committee develops the topic tracks, selects speakers and organizes the presentations that comprise the heart of the conference.

The talks are organized into the following focused tracks as described above. The program also includes six tracks of contributed talks, tracks on software solutions and poster presentations that include case studies, best practice examples and academic research with a practitioner orientation.

Special programs within the conference are designed for future analytics leaders.

The Early Career Connection provides early career professionals with new perspectives into some of the most critical problems facing industry today, enabling them to broaden their research agendas.

The INFORMS Professional Colloquium is designed to help practice-oriented master’s and Ph.D. students transition into successful careers. Participants in both programs can register for the full conference at a discounted rate but must be nominated and selected to attend.

The Analytics Career Fair is INFORMS’ premier, professional career event that allows top analytics employers and seasoned professionals the ability to connect in a casual atmosphere. The career fair is included in the registration for this conference.

The Hyatt Regency Grand Cypress offers an impressive collection of on-site activities, in addition to being just one mile from Walt Disney World and close to everything else Orlando has to offer. Conference registration rates start at $1,065 for INFORMS members. Special rates are available for students, retired attendees, conference newcomers and selected speakers. A team discount is also available.

For more information, visit meetings. informs.org/analytics2016. ORMS

Learn from the best in high-impact O.R. and analytics applications.

Franz Edelman Competition & Award An impressive lineup of finalists will compete for the top prize in this “super bowl” of applied operations research, showcasing analytics projects that had major impacts on their client organizations. The finalists and their projects include: 1. 360i: “360i’s Digital Nervous System” 2. BNY Mellon: “Transition State and End State Optimization Used in the BNY Mellon U.S. Tri-Party Repo Infrastructure Reform Program” 3. Chilean Professional Soccer Association (ANFP): “Operations Research Transform Scheduling of Chilean Soccer Leagues and South American World Cup Qualifiers” 4. The New York City Police Department (NYPD): “Domain Awareness System (DAS)” 5. UPS: “UPS On Road Integrated Optimization and Navigation (Orion) Project” 6. U.S. Army Communications-Electronics Command (CECOM): “Bayesian Networks for U.S. Army Electronics Equipment Diagnostic Applications: CECOM Equipment Diagnostic Analysis Tool, Virtual Logistics Assistance Representative”

INFORMS Prize This prize is awarded annually to the company that effectively integrates analytics into organizational decision-making and has repeatedly applied ORMS principles in pioneering, novel and lasting ways. The 2015 prize-winning team will describe its innovative O.R. work in a regular conference session. The 2016 winner will be announced at the Edelman Gala on Monday evening.

Daniel H. Wagner Prize This prize emphasizes the quality and coherence of the analysis used in practice. Dr. Wagner strove for strong mathematics applied to practical problems, supported by clear and intelligible writing. The Wagner Prize recognizes those principles by emphasizing good writing, strong analytical content and verifiable practice successes. The competition is held and the winner is announced at the INFORMS Annual Meeting in the fall. The 2015 winner, CDC, Georgia Tech and Emory, will reprise their presentation at this conference.

Innovative Applications in Analytics Award The Innovative Applications in Analytics Award, sponsored by the INFORMS Analytics Section, recognizes creative and unique developments, applications or combinations of analytical techniques. Its goal is to promote the awareness of the value of analytics in unusual applications or in creative combination to provide unique insights and/or business value.

UPS George D. Smith Prize The George D. Smith Prize is aimed at strengthening ties between academia and industry by rewarding institutions of higher education for effective and innovative preparation of students to be good practitioners of operations research. UPS generously underwrites the prize.

Crop Challenge Sponsored by Syngenta and the INFORMS Analytics Section Nearly 7 million hectares of farmland are lost to soil erosion every year. Many people who produce the world’s food are living in poverty. Biodiversity is disappearing fast. And the challenge won’t get any easier: By 2050, for example, 4 billion people will be living in countries with water scarcity.

Something needs to change. We only have one planet, and we’re using its resources 50 percent faster than it can take. What we’re asking it to provide is simply not sustainable.

Each year farmers have to make decisions about what crops to plant given uncertainties in expected weather conditions and knowledge about the soil at their respective farms.

These decisions have important impacts; an unusual weather pattern can have disastrous impacts on crops, but planting to hedge against stressful weather patterns can dramatically reduce yields in normal years. How can a farmer make seed variety decisions that optimally reduce risk and increase yield?

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n ews International Conference heading for Hawaii The 2016 INFORMS International Conference will be held at the Hilton Waikoloa Village Resort from June 12-15.

Located on the Kohala Coast of Hawaii (the Big Island), the resort and surrounding area offer unparalleled beauty combined with the unique Hawaiian cultural heritage.

The conference, one of the largest international conferences in operations research and management science, offers an impressive lineup of plenary speakers interspersed with invited tracks. The invited tracks will span the full range of emerging topics, from global supply chains to social networks and all aspects in between. The informative program is designed to educate attendees on the current advances in OR/ MS that are at the cutting edge of the field anywhere in the world. Through a series of diverse speakers, panels, tutorials and structured networking, the conference will provide attendees a forum for rich intellectual exchange on a broad range of OR/MS applications.

Gang Yu, co-founder and executive chairman of New Peak Group, will deliver the plenary talk on June 12. Prior to founding New Peak Group, he was the co-founder and chairman of Yihaodian – a leading ecommerce company in China. Dr. Yu also served as vice president of worldwide procurement at Dell Inc. and as vice president of worldwide supply chain operations at Amazon.com.

Dr. Yu has received numerous international awards in recognition of his achievements including: the 2002 Franz Edelman Management Science Achievement Award from INFORMS, the 2002 IIE Transaction Award for Best Application Paper, the 2003 Outstanding IIE Publication Award from the Institute of Industrial Engineers and the 2012 Martin K. Starr Excellence in Production and Operations Management Practice Award from POMS. He has published more than 80 journal articles, four books and holds three U.S. patents.

In addition to the technical tracks, the program includes two receptions primarily focused on networking with international attendees and colleagues. A welcome reception will be held on Sunday evening 52 | ORMS Today

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where Conference Chair Saif Benjaafar and the rest of the conference committee will welcome attendees to Hawaii. The Tuesday evening general reception will be an authentic Hawaiian luau that is sure to be a feast for all of your senses. Men and women in ornate costumes will perform a festival drum dance from the Hilton Waikoloa Village Resort, site of the 2016 International islands of Tahiti. A tradiConference. tional Polynesian luau feast will be served as well. The event is included kayaking, paddle boating and a dolphin in the conference registration fee. encounter experience.

The sprawling 62-acre Hilton Waikoloa Registration fees for this conference Village Resort offers gardens, waterfalls, start at $630 for INFORMS members. Dislagoons and waterways that create stunning counted student/retired rates are available. visuals throughout the property. The resort Early registration rates will expire on May also boasts numerous restaurants, three 20. For more information, visit: meetings. pools, eight tennis courts, two golf courses, informs.org/2016international. ORMS

Roundtable holds retreat

By Bill Browning

The INFORMS Roundtable Fall Retreat was held Oct. 18-19, 2015, at the Dan Abraham Healthy Living Center on the Mayo Clinic campus in Rochester, Minn.

“Personal Health and Individualized Medicine” was the meeting theme.

Richard Weinshilboum, M.D., professor of molecular pharmacology and experimental therapeutics and internal medicine, gave the keynote talk Sunday evening on “Pharmacogenomics and Individualized Medicine.”

Monday began with a guided meditation session. Deb Rhodes, M.D., then described the three pillars of the Mayo Clinic Healthy Living Program approach – nutrition, physical activity and resiliency. Phil Hagen, M.D., spoke about outcomes measurement in lifestyle and behavior change.

Interactive sessions for the Roundtable attendees included a presentation in the Non Exercise Activity Thermogenesis (NEAT) Studio on “sitting disease” and NEAT practices for work and travel. Mayo

Clinic physical activity experts then led a discussion on the benefits of activity trackers (e.g., Fitbit, Garmin, Jawbone, Withings), their data analysis and where these devices are going. Mayo Clinic physical therapists also led an interactive group postural assessment, including exercises to improve posture alignment.

In the afternoon, Dr. Kalyan Pasupathy, associate professor of healthcare systems engineering, described systems engineering and operations research projects conducted by the Mayo Clinic Engineering Learning Lab. Phil Hagen, M.D., presented data on the importance of sleep to health and performance. Don Hensrud, M.D., medical director of the Mayo Clinic Healthy Living Program, was the final speaker and provided an overview of the program’s activities, as well as closing comments.

The retreat concluded with a farewell dinner at the Dan Abraham Healthy Living Center. ORMS ormstoday.informs.org

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Website redesign, new logo possibilities

By Mary Leszczynski Good things are happening in the INFORMS Public Affairs & Marketing Department! And more great things are on the way.

I am extremely lucky (most of the time) to have a relatively new boss (Jeff Cohen) who questions everything and constantly raises the bar on what we do and how we do it. Sometimes he makes me crazy (PLEASE don’t tell him I said that!), but as a designer and a brand champion, his approach is invaluable.

At times, we are constrained by time and workload, and while the first solution is serviceable, it’s not something I would be proud to put in my portfolio.

We have revamped our department, hiring some incredibly talented and creative individuals, and are producing incredible work that I am really proud of – and I hope you are, too.

As we look ahead at 2016, perhaps the biggest project we are going to undertake is the redesign of our website, www.informs.org. We’ll keep you updated on this ambitious project, and we look forward to creating a new website that better meets the needs of our members, and better promotes the exciting work you do in operations research, the management sciences and analytics.

While we were crafting the RFP soliciting bids for this project, Jeff asked, “What about the logo? If we are going to spend all of this time, money and energy creating this great new site for our members, shouldn’t we be reimagining all of the elements?”

The process began with a creative brainstorming session.

Who was the audience?

What is our story?

What do we want the world to know about INFORMS and OR/MS?

Long pause. “Maybe?”

I responded. A billion thoughts were crashing through my head. Why? Will the members like it?

How do I draw OR/MS? How do you represent the diversity of disciplines?

Are we just changing the logo to change it? Are we designing for the professional society?

Or designing for the subject matter? How many colors? Will the members like it? (Yes, I know I repeated that, but at the end of the day, that’s who our stakeholders are, and I want them to connect with the logo.)

So the process began with a creative brainstorming session. Who was the audience? What is our story? What do we want the world to know about INFORMS and OR/MS? The team left the session, each person returning with a set of sketches. We critiqued, we refined, we researched, we explained, and we critiqued some more.

In January, we presented options to the board of directors to get their sense as to whether we should venture down

this path. In the end, we wanted to share this initiative with our members, and get their feedback.

So that’s what we’re doing. The question is, should INFORMS update our logo? And what do you think about the two logos (shown here) we presented to the board in January? And, if you want to know about the use of color or design elements, just ask. I’m happy to share that with you, too!

Importantly, no one is saying we have to redesign the logo. But as we undertake the new website and a number of other creative projects, we want to make sure we are considering all of the elements.

And that we are portraying INFORMS, and more importantly our members and your work, in the best, most exciting way possible.

We look forward to your feedback.

It’s important.

Thanks in advance for your time and support. Please send your thoughts to socialnetworking@mail.informs.org.

ORMS Mary Leszczynski is INFORMS’ design & brand manager.

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n ews 2015 INFORMS Subdivision Awards The following awards were presented by the respective INFORMS subdivisions, societies, sections, interest groups, etc., at the 2015 INFORMS Annual Meeting in Philadelphia in November.

APPLIED PROBABILITY Best Publication in Applied Probability Award

Mohsen Bayati and Kavita Ramanan (l-r).

Recipients: Mohsen Bayati, Marc Lelarge and Andrea Montanari Recognized work: “Universality in Polytope Phase Transitions and Message Passing Algorithms”

BEHAVIORAL OPERATIONS MANAGEMENT

ICS Student Paper Award

Best Working Paper Award Recipients: Ernan Haruvy, Elena Katok and Valery Pavlov Recognized work: “Bargaining Process and Channel Efficiency” Runner-up: Tim Kraft, Leon Valdes, and Yanchong Zheng, “Transparency and Indirect Reciprocity in Social Responsibility: An Incentivized Experiment” Honorable mention: Hummy Song, Anita L. Tucker, Karen L. Murrell and David R. Vinson, “Adopting Coworkers’ Best Practices: Public Relative Performance Feedback as a Tool for Standardizing Workflow”

COMPUTING ICS Harvey J. Greenberg Service Award

AVIATION APPLICATIONS Dissertation Prize

Young Woong Park (left) receives ICS Student Paper Award.

Recipient: Young Woong Park, Northwestern University Recognized work: “An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning” Runners-up: Xiao Liu, Ohio State University, “Decomposition Algorithms for Two-Stage Chance-Constrained Programs”; Leonardo Lozano, Clemson University, “A Backward Sampling Framework for Interdiction Problems with Fortification”; Jorge A. Sefair, University of Florida, “Dynamic Shortest-Path Interdiction”

CPMS: PRACTICE SECTION OF INFORMS The Daniel H. Wagner Prize for Excellence in Operations Research Richard Barr (right) receives service award.

Michael Bloem and David Lovell (l-r).

Recipient: Michael Bloem, Stanford University Recognized work: “Optimization and Analytics for Air Traffic Management”

Recipient: Richard Barr

INFORMS Computing Society Prize

Best Student Presentation

Recipients: Eva K. Lee, Georgia Institute of Technology; Fan Yuan, Georgia Institute of Technology; Bali Pulendran, Emory University; Helder Nakaya, Emory University; Troy Quere, Emory University; Greg Burel, Centers for Disease Control and Prevention; Ferdinand Pietz, Centers for Disease Control and Prevention; Bernard Benecke, Centers for Disease Control and Prevention Recognized work: “Machine Learning Framework for Predicting Vaccine Immunogenicity”

DATA MINING Best Student Paper Award

Presentation of the ICS Prize.

Recipients: Suvrajeet Sen, Dinakar Gade, Julia Higle, Simge Küçükyavuz, Lewis Ntaimo and Hanif Sherali

Chiwei Yan and Senay Solak (l-r).

Recipient: Chiwei Yan, MIT Recognized work: “Robust Aircraft Routing” Honorable mention: Lei Kang, University of California, Berkeley, “Statistical Analysis of Dispatcher Fuel Loading Behavior”

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Kamran Paynabar, Sam Davanloo Tajbakhsh, Fulton Wang, Murat Yildirim and Mingdi You (l-r).

Recipient: Mingdi You, University of Michigan Recognized work: “When Wind Meets Turbines: A New Statistical Approach for Characterizing the Heterogeneous Wake Effects in Multi-turbine Wind Farms”

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Finalists: Sam Davanloo Tajbakhsh, “Sparse Precision Matrix Selection for Fitting Gaussian Random Field Models to Large Data Sets”; Fulton Wang, MIT, “Falling Rule Lists”; Murat Yildirim, Georgia Tech, “Sensor-Driven Condition-Based Generation Maintenance and Operations Scheduling”

Publication Award

Best Publication Award in Environment & Sustainability

DECISION ANALYSIS Frank P. Ramsey Medal James S. Dyer and James E. Smith (l-r).

J. Eric Bickel and L. Robin Keller (l-r).

Recipient: L. Robin Keller, University of California, Irvine Recognition: Distinguished contributions in decision analysis

Practice Award

Recipients: David Brown and James Smith Recognized work: “Optimal Sequential Exploration: Bandits, Clairvoyants and Wildcats” Finalists: Kenneth Lichtendahl, Yael Grushka-Cockayne, Phillip Pfeifer, “The Wisdom of Competitive Crowds”; and Jeffrey Stonebraker, “Product-Generation Transition Decision Making for Bayer’s Hemophilia Drugs: Global Capacity Expansion Under Uncertainty with Supply-Demand Imbalances”

Victoria Chen and Esra Büyüktahtakın (l-r).

Recipients: Halil Ibrahim Cobuloglu and Esra Büyüktahtakın (l-r).

Recognized work: “A mixed-integer optimization model for the economic and environmental analysis of biomass production”

Best Publication Award in Natural Resources

ENERGY, NATURAL RESOURCES AND THE ENVIRONMENT Student Paper Travel Award

Sándor Tóth and Andres Weintraub (l-r).

Frank Koch and Michael C. Runge (l-r).

Recipient: Michael C. Runge, Kirk E. Lagory and Kendra Russell Recognized work: “Using Multi-criteria Decision Analysis to Explore Management Options in the Grand Canyon”

Student Paper Award

Sauleh Siddiqui and Safak Yucel (l-r).

Recipient: Safak Yucel Recognized work: “Impact of Electricity Pricing Policy on Renewable Energy Investments and Carbon Emissions”

Recipients: Rodolfo Carvajal, Miguel Constantino, Marcos Goycoolea, Juan Pablo Vielma and Andres Weintraub Recognized work: “Imposing Connectivity Constraints in Forest Planning Models”

ENRE Young Researcher

Best Publication Award in Energy

Steffen Rebennack and Enzo Santis (l-r).

Robert Hammond, Asa Palley and Canan Ulu (l-r).

Recipient: Asa Palley, Duke University Recognized work: “Eliciting and Aggregating Forecasts when Information is Shared” Finalists: Mehmet Eren Ahsen, “Information aggregation and classification under anchoring bias: an application to judgments based on breast imaging”; and Shweta Agarwal, London School of Economics and Politics, “Probability revision rules to model the effect of interventions on uncertainties”

Ben Hobbs, Anthony Papavasiliou and Shmuel Oren (l-r).

Recipient: Steffen Rebennack Recognized work: “Combining sampling-based and scenario-based nested Benders decomposition methods: application to stochastic dual dynamic programming”

Recipients: Anthony Papavasiliou and Shmuel S. Oren Recognized work: “Multi-Area Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network”

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n ews FINANCIAL SERVICES Best Student Research Paper

INFORMATION SYSTEMS SOCIETY Distinguished Fellow Award Recipients: Anitesh Barua, Ram D. Gopal, Anindya Ghose and Vishwanath Venkatesh

Management Science Best Paper in Information Systems Presentation of the Best Student Research Paper.

Winner: Chi Seng Pun Second place: Deung-geon Ahn Honorable mention: Richard Neuberg

HEALTH APPLICATIONS Pierskalla Best Paper Award

Diwakar Gupta, William Pierskalla, Baris Ata and SooHaeng Cho (l-r).

Recipients: Baris Ata, Anton Skaro and Sridhar Tayur Recognized work: “OrganJet: Overcoming geographical disparities in access to deceased donor kidneys in the United States” Runners-up: Stephen E Chick, Martin Forster and Paolo Pertile, “A Bayesian Decision-Theoretic Model of Sequential Experimentation with Delayed Responses” Finalists: Dan Yamin, Yoku Ibuka, Alison P. Galvani and Jeffery P. Townsend, “Optimal dosing of rotavirus vaccination in Japan”; Hadi El-Amine, Ebru K. Bish and Douglas R. Bish, “Robust Post-donation Blood Screening under Prevalence Rate Uncertainty”; Justin Jia and Hui Zhao, “Mitigating The U.S. Drug Shortages: Pareto-Improving Contract Design”

Recipients: Mingfen Lin, Nagpurnanand R. Prabhala and Siva Viswanathan Recognized work: “Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending” Finalists: Prasanna Tambe and Lorin M. Hitt, “Job Hopping, Information Technology Spillovers, and Productivity Growth”; Robert Seamans and Feng Zhu, “Responses to Entry in Multi-Sided Markets: The Impact of Craigslist on Local Newspaper”

Recipients: Kayse Maass, University of Michigan Student Chapter; Michael Prokle, University of Massachusetts Student Chapter; Eghbal Rashidi, Mississippi State University Student Chapter Recognition: Outstanding student volunteers who have been “moving spirits” in their universities, their student chapters and the Institute.

Student Chapter Annual Awards

University of Massachusetts Student Chapter.

Nunamaker-Chen Dissertation Award Winner: Jason Chan Recognized work: “Social and Health Impacts of the Internet” Winner: Lei Wang Recognized work: “Three Essays on the Interface of Location-Based Services, Consumers’ Shopping Behavior and Firms’ Marketing Strategy” Runner-up: Marios Kokkodis “Online Labor Markets: Reputation Transferability, Career Development Paths and Hiring Decisions”

ISS Early Career Award Recipients: Param Vir Singh, Gal Oestreicher-Singer and Eric Overby

University of Toronto Student Chapter.

Recipients: (Summa Cum Laude): University of Massachusetts and University of Toronto; (Magna Cum Laude): Lehigh University, Northwestern University, Purdue University, Stanford University and University of South Florida; (Cum Laude): Arizona State University, Mississippi State University and North Carolina State University-Raleigh.

Recognition: Outstanding participation and performance during the year of 2014

INFORM-ED INFORMS

Case Competition Award

Judith Liebman Award

First place: Vera Tilson and Greg Dobson, University of Rochester Recognized work: “Medication Waste Reduction in an in-hospital Pharmacy: A Case That Bridges Problem Solving between a Traditional Case and an Industry Project” Second place: Kathleen Iacocca, University of Scranton, “Distribution Strategies at Yaka Pharmaceuticals” Third place: Wendy Swenson Roth, Georgia State University, “Using Optimization for Team Information”

Seth Bonder Scholarship for Applied Operations Research in Health Services

Ed Kaplan, Kayse Maass and Dave Hunt (l-r).

JUNIOR FACULTY INTEREST GROUP JFIG Paper Competition Award First place: Juan Pablo Vielma, MIT Recognized work: “Embedded Formulations and Complexity for Unions of Polyhedra”

Mark von Oyen and Hadi El-Amine (l-r).

Recipient: Hadi El-Amine, Virginia Tech

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Judith Liebman winner Eghbal Rashidi.

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Second place: David Goldberg, Georgia Institute of Technology, and Linwei Xin, University of Illinois at Urbana-Champaign, “Asymptotic Optimality of Tailored Base-Surge Policies in Dual Sourcing Inventory Systems” Third place: Shuangchi He, National University of Singapore, “Diffusion Approximation for Efficiency-Driven Queues: A Space-Time Scaling Approach” Honorable mention: Soroush Saghafian, Harvard University, “Ambiguous Partially Observable Markov Decision Processes: Structural Results and Applications”; Rouba Ibrahim, University College London, “Capacity Sizing in Queueing Models with a Random Number of Servers”; Erick Moreno-Centeno, “Roundoff-Error-Free Algorithms for Solving Linear Systems via Cholesky and LU Factorizations”

Distinguished Service Award

Recipients: Mehmet Gümüs, Saibal Ray and Haresh Gurnani Recognized work: “Supply-side story: Risks, guarantees, competition and information asymmetry,” Management Science, Vol. 58, No. 9, 2012, pp. 1694-1714.

Service Management SIG Best Paper Award

Steve Gilbert and Brian Tomlin (l-r).

Recipient: Steve Gilbert, University of Texas at Austin

Distinguished Fellows Award

LOCATION ANALYSIS Andres Musalem, Brian Tomlin and Marcelo Olivares (l-r).

Chuck ReVelle Rising Star Award

Recipients: Yina Lu, Andres Musalem, Marcelo Olivares and Ariel Schilkrut Recognized work: “Measuring the Effect of Waiting Time on Customer Purchases”

Best Paper Award Marty Lariviere and Brian Tomlin (l-r).

Ivan Conteras and Tim Lowe (l-r).

Recipients: Ivan Contreras, Concordia University

Recipients: Martin Lariviere and Christopher Tang

Management Science Best Paper Award in Operations Management

Recipients: Chen Peng, Feryal Erhun, Erik Hertzler and Karl Kempf Recognized work: “Capacity Planning in the Semiconductor Industry: Dual-Mode Procurement with Options”

Young Scholar Prize

MSOM Student Paper Competition

Vishal Agrawal, Beril Toktay, Brian Tomlin and Mark Ferguson (l-r).

Ashish Kabra, Daniela Saban, Tugce Martagan, Hummy Song, Safak Yucel and Fei Gao (l-r).

First place: Ashish Kabra, INSEAD Recognized work: “Bike-Share Systems: Accessibility and Availability” Second place: Daniela Saban, Stanford University, “Procurement Mechanisms for Differentiated Products” Finalists: Fei Gao, University of Pennsylvania, “Online and Offline Information for Omnichannel Retailing”; Hummy Song, Harvard University, “Learning From the Best: The Effects of Public Relative Performance Feedback on Variability and Productivity”; Safak Yücel, Duke University, “Impact of Electricity Pricing Policy on Renewable Energy Investments and Carbon Emissions”; and Tugce Martagan, Eindhoven University of Technology, “Optimal Purification Decisions for Engineer-to-Order Proteins”

Recipients: Vishal Agrawal, Mark Ferguson, Beril Toktay and Valerie Thomas Recognized work: “Is Leasing Greener than Selling?” Management Science, Vol. 58, No. 3, March 2012, pp. 523-533.

Gabriel Weintraub and Brian Tomlin (l-r).

Recipients: Baris Ata and Gabriel Weintraub

MILITARY APPLICATIONS 2015 Koopman Prize

iFORM Best Paper Award

Bao Nguyen.

Saibal Ray, Haresh Gurnani, Mehmet Gumus and Brian Tomlin (l-r).

Recipients: Bao Nguyen Recognized work: “Assessment of a Ballistic Missile Defense System”

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n ews Seth Bonder Scholarship for Applied Operations Research in Military Applications

OPTIMIZATION Student Paper Prize

Paul Grigas (left) receives Student Paper Prize.

Ross Schuchard and L. Robin Keller (l-r).

Recipient: Ross Schuchard, ARCYBER/George Mason University

J. Steinhardt Prize

Khachiyan Prize

Recipient: Paul Grigas Recognized work: “A new perspective on boosting in linear regression via subgradient optimization and relatives” Honorable mention: Ruoyu Sun, “Guaranteed matrix completion via non-convex factorization”; and Shimrit Shtern, “A semi-definite programming approach for robust tracking”

Jean Bernard Lasserre (right) receives the Khachiyan Prize.

Recipient: Jean Bernard Lasserre Recognized for: Lifetime achievements in the field of optimization

Farkas Prize of the Optimization Society

Prize for Young Researchers

Keith Womer (center) receives Steinhardt Prize.

Recipient: Keith Womer Recognition: Outstanding contributions to military operations research

Omega Rho Distinguished Lecturer

Robert Weismantel (left) receives the Farkas Prize.

Fatma Kılınç-Karzan (left) receives Prize for Young Researchers.

Winner: Fatma Kılınç-Karzan Recognized work: “On Minimal Valid Inequalities for Mixed Integer Conic Programs”

Javad Lavaei (right) receives Prize for Young Researchers.

Margaret Brandeau.

Presenter: Margaret L. Brandeau, Stanford University Lecture: “Creating Impact with Operations Research in Health”

Somayeh Sojoudi (right) receives Prize for Young Researchers.

Winner: Javad Lavaei and Somayeh Sojoudi Recognized work: “Exactness of Semidefinite Relaxations for Nonlinear Optimization Problems with Underlying Graph Structure”

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Recipient: Robert Weismantel Recognition: Outstanding contributions to the field of optimization

ORGANIZATION SCIENCE Best Dissertation Proposal Competition Recipient: Julia DiBenigno, MIT Recognized work: “Understanding organizational change in response to institutional pressure: The case of army mental healthcare for active-duty soldiers” Finalists: Pooria Assadi, Simon Fraser University, “Empirical Investigation of the Causes and Effects of Misconduct in the U.S. Securities Industry”; Feng Bai, University of British Columbia, “Beyond dominance and competence: A moral virtue theory of status attainment”; Santiago Campero, MIT, “Does firm status confer a recruiting advantage? Evidence from high tech entrepreneurial firms”; Jillian Chown, Toronto, Rotman School of Management, “Implementing organizational change within a professional workforce: A multi-method exploration”; Tiffany Johnson, Penn State, “Scaling cliffs and chasms: Examining micro-processes of inclusion through the lens of autism job coaches”; Derek Harmon, University of Southern California, “The structure of strategic communication: Theory, measurement and effects”; Amer Madi, INSEAD, “Finding existential meaning at work: When and why do people seek existential meaning at work and how is it maintained, changed, or lost?”; Francois Neville, Georgia State, “Taking center stage: An examination of the role of executives during organizational interactions with secondary stakeholder activists”

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PUBLIC SECTOR O.R. Best Paper Competition

Recognized work: “Real-time Monitoring and Diagnosis of High-Dimensional Data Streams via Spatio-Temporal Smooth Sparse Decomposition” Finalists: Cynthia Rudin, “Direct Learning to Rank and Rerank”; QianMei Feng, Yin Shu, Edward Kao, David Coit and Hao Liu, “Markov Additive Processes for Degradation with Jumps under Dynamic Environments”; Youngjun Choe and Eunshin Byon, “EM-Based Cross-Entropy Method With an Asymptotically Unbiased Information Criterion”

Recognized work: “From Single Commodity to Multiattribute Models for Locomotive Optimization: A Comparison of Optimal Integer Programming and Approximate Dynamic Programming”

Railway Applications Student Paper Award

Best Student Poster Competition Dionne Aleman, Shivam Gupta and Alex Mills (l-r).

First place: Shivam Gupta, Milind Dawande, Ganesh Janakiraman and Ashutosh Sarkar Recognized work: “Distressed Selling by Farmers: Model, Analysis, and Use in Policy-Making” Second place: Eike Nohdurft, Elisa Long and Stefan Spinler, “Efficient spatial allocation of epidemic crisis intervention resources with a focus on Ebola in West Africa” Honorable mention: Na Li, Nan Kong, Quanlin Li and Zhibin Jiang, “Operational Performance Evaluation of Reverse Referral Partnership in the Chinese Healthcare System”

QUALITY, STATISTICS & RELIABILITY Best Student Paper

Nikola Besinovic (left) receives Student Paper Award.

Abdallah Chehade (center) won the Best Student Poster Competition.

Recipient: Abdallah Chehade Recognized work: “Optimize the Signal Quality of the Composite Health Index via Data Fusion for Degradation Modeling and Prognostic Analysis”

RAILROAD APPLICATIONS Problem Solving Competition

First place: Nikola Besinovic Recognized work: “A novel two-stage approach to robust periodic timetabling” Second place: Joris C Wagenaar, “Solving the depot problem” Third place: Shuguang Zhan, “Real-time high speed train rescheduling in case of a partial segment blockage”

REVENUE MANAGEMENT AND PRICING Section Award

Tirthankar Dasgupta, Yanjun Qian and Eunshin Byon (l-r).

Recipient: Yanjun Qian Recognized work: “Multi-stage Nanocrystal Growth Identifying and Modeling via In-situ TEM Video” Finalists: Kaveh Bastani, “An Online Sparse Estimation-based Classification (OSEC) Approach for Real-time Monitoring in Additive Manufacturing”; Yan Jin, “Diagnostic Monitoring of Multivariate Process via a LASSO-BN Formulation”; Junbo Son, “RUL Prediction Based on Noisy Condition Monitoring Signals using Constrained Kalman Filter”

Best Refereed Paper Award

Negin Alemazkoor (left) helped win the Problem Solving Competition.

First place: Negin Alemazkoor, Conrad Ruppert and Hadi Meidani Second place: Ivan Cardenas Gallo, Carlos Sarmiento Cardona and Gilberto Morales Zamora Third place: Sudhir Kumar Sinha, Sumit Raut and Harshad Khadilkar

Railway Applications Distinguished Member Award

Hao Yan (left) accepts the Best Refereed Paper Award.

Clark Cheng (left) receives the Distinguished Member Award.

Recipients: Kamran Paynabar, Hao Yan and Jianjun Shi

Recipient: Clark Cheng

Vivek F. Farias, Srikanth Jagabathula, Bill Cooper and Devavrat Shah (l-r).

Recipients: Vivek F. Farias, Srikanth Jagabathula and Devavrat Shah Recognized work: “A Nonparametric Approach to Modeling Choice with Limited Data.”

SERVICE SCIENCE Best Article Award Recipients: Chris K. Anderson and Benjamin Lawrence Recognized work: “The Influence of Online Reputation and Product Heterogeneity on Service Firm Financial Performance” Honorable mention: Euthemia Stavrulaki and Mark M. Davis, “A Typology for Service Supply Chains and Its Implications for Strategic Decisions”

February 2016

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n ews SIMULATION Lifetime Professional Achievement

Douglas Morrice and Bernard Zeigler (l-r).

Recipient: Bernard P. Zeigler Recognition: Career contributions to the field of simulation

Runners-up: Jing Peng, University of Pennsylvania, “Participation vs.

Effectiveness of Paid Endorsers in Social Advertising Campaigns: A Field Experiment”; Vilma Todri, New York University, “Social Media Analytics: The Effectiveness of Marketing Strategies in Online Social Media”; and Zhenhuan Sui and David Milam, Ohio State University, “A Visual Monitoring Technique Based on Importance Score and Twitter Feeds”

TECHNOLOGY, INNOVATION MANAGEMENT AND ENTREPRENEURSHIP Distinguished Speaker Award Recipient: Steven Eppinger, MIT Sloan School of Management

Best Dissertation Award Distinguished Service Award

Enver Yücesan and Peter J. Haas (l-r).

Recipient: Enver Yücesan Recognition: Long-standing, exceptional service to the simulation community

Outstanding Simulation Publication Award

Recipient: Alessio Cozzolino, Bocconi University Recognized work: “Three Essays on Technological Changes and Competitive Advantage: Evidence from the Newspaper Industry” Runner-up: Russell James Funk, University of Michigan, Ross School of Business, “Essays on Collaboration, Innovation and Network Change in Organizations” Finalists: Hila Lifshitz-Assaf, Harvard, “Shifting Loci of Innovation: A Study of Knowledge Boundaries, Identity and Innovation at NASA”; Catherine Magelssen, Rutgers, “Property Rights Theory and Ownership of Firm-Specific Advantages: The Implications of Contracting and Licensing within the Multinational Firm”

Best Paper Award Recipients: Daniel W. Elfenbein, Barton H. Hamilton and Todd R. Zenger Recognized work: “The Small Firm Effect and the Entrepreneurial Spawning of Scientists and Engineers” Runner-up: Jasjit Singh and Lee Fleming, “Lone Inventors as Sources of Breakthroughs: Myth or Reality?”

Dissertation Prize

Alexandre Jacquillat (center) receives Dissertation Prize.

Recipient: Alexandre Jacquillat, MIT Recognized work: “Integrated Allocation and Utilization of Airport Capacity to Mitigate Air Traffic Congestion”

Robert Herman Lifetime Achievement Award

Michel Gendreau (center) receives Dissertation Prize.

Recipient: Michel Gendreau

WOMEN IN OR/MS Advancement of Women in OR/MS

TRANSPORTATION SCIENCE & LOGISTICS Best Paper Award Russell Barton, Jeremy Staum, Barry Nelson and Wei Xie (l-r).

Recipients: Russell R. Barton, Barry L. Nelson and Wei Xie Recognized works: “Quantifying Input Uncertainty via Simulation Confidence Intervals” (INFORMS Journal on Computing) and “A Bayesian Framework for Quantifying Uncertainty in Stochastic Simulation” (Operations Research)

SOCIAL MEDIA Best Student Paper Competition Recipient: Nathan Kallus, MIT Recognized work: “Predicting Crowd Behavior with Big Public Data”

60 | ORMS Today

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February 2016

Aleda Roth and Margaret Brandeau (l-r).

Recipient: Margaret Brandeau, Stanford University

TSL’s Best Paper Award presentation.

Recipient: Belgacem Bouzaiene-Ayari, Clark Cheng, Sourav Das, Ricardo Fiorillo and Warren B. Powell Recognized work: “From Single Commodity to Multiattribute Models for Locomotive Optimization: A Comparison of Optimal Integer Programming and Approximate Dynamic Programming”

ormstoday.informs.org

ormstoday.informs.org

People Ramayya Krishnan, dean of the H. John Heinz III College and professor of management science and information systems at Carnegie Mellon University, is the 2015 recipient of Nayudamma Centre for Development Alternatives (NCDA) Nayudamma Award. The award was presented at a special ceremony on Dec. 21 at Krishnan’s undergraduate alma mater, the Indian Institute of Technology Madras (IIT-Madras), where he also delivered the 21st Professor Yelavarthy Nayudamma Memorial Lecture.

The Nayudamma Award honors individuals for their significant contributions around the world in areas of sustainable development. An INFORMS Fellow, Krishnan was recognized for his research and leadership in making data-driven decisions in key societal domains, including transportation, smart cities and living analytics.

“As a scholar, Krishnan’s work on data-driven decision-making in cyber physical environments is well known for its multi-disciplinary contributions to the fields of operations research and information systems. This work and that of his colleagues at the intersection of information technology, public policy and management is having a significant impact on organizations in both the public and private sectors via the multiple research centers he has helped establish at the University,” said CMU Provost Farnam Jahanian. “As dean of Carnegie Mellon’s Heinz College of Information Systems and Public Policy, his work with our faculty exemplifies the university’s commitment to advancing knowledge and improving the human condition.”

Added Dr. Anumakonda Jagadeesh, director of the Nayudamma Centre for Development Alternatives: “A scientist of international repute, Dr. Krishnan’s contributions to the fields of big data, smart cities, living analytics and information technology are matchless. The volume, variety and velocity of data coming into organizations continue to reach unprecedented levels. This phenomenal growth means that one must not only understand big data in order to decipher the information that truly counts, but must also understand the possibilities of big data analytics.”

Meetings

Go to www.informs.org/Conf for a searchable INFORMS Conference Calendar.

INFORMS Annual & International Meetings

INFORMS Community Meetings

April 10-12, 2016

March 17-19, 2016

INFORMS Conference on Business Analytics & Operations Research

2016 INFORMS Optimization Society Workshop

Hyatt Regency Grand Cypress Orlando, Fla. Chair: Elea McDonnell Feit, Drexel University http://meetings.informs.org/analytics2016

Princeton University, Princeton, N.J. Chair: Warren Powell, Princeton University https://orfe.princeton.edu/conferences/ios2016/

June 12-15, 2016

2016 INFORMS International Meeting Hilton Waikoloa Village Waikoloa, Hawaii Chair: Saif Benjaafar, University of Minnesota http://meetings.informs.org/2016international

Nov. 13-16, 2016

INFORMS Annual Meeting Music City Center & Omni Nashville Nashville, Tenn.

Chair: Chanaka Edirisinghe, RPI http://meetings.informs.org/nashville2016

April 2-4, 2017

INFORMS Conference on Business Analytics & Operations Research Caesars Palace, Las Vegas Las Vegas, Nevada

Oct. 22-25, 2017

INFORMS Annual Meeting

March 20-22, 2016

2016 INFORMS Telecommunications Conference Renaissance Hotel, Boca Raton, Fla. Chair: Michael R. Bartolacci, Penn State University https://sites.psu.edu/informstelecom2016/

June 16-18, 2016

2016 INFORMS Marketing Science Conference Shanghai, China Chair: Icey Han, Fudan University http://www.fdsm.fudan.edu.cn/marketingscience2016/

June 30- July 1, 2016

MSOM Conference University of Auckland Business School Auckland, New Zealand Co-chairs: Tava Olsen and David Robb, University of Auckland Business School http://www.cscm.auckland.ac.nz/2016-msom-conference

Dec. 11-14, 2016

George R. Brown Convention Center & Hilton Americas Houston, Texas Chair: William Klimack, Chevron

Winter Simulation Conference

The award’s namesake (Nayudamma) was an internationally renowned organic chemist, practical technologist and academic leader, as well as the former president of the International Council for Science’s Commit-

tee on Science and Technology in Developing Countries. He is perhaps best known, however, for dedicating his life to demonstrating how science and technology can and should be used for human benefit. ORMS

Crystal Gateway Marriott Arlington, Va. Chair: Todd Huschka, Mayo Clinic

Ramayya Krishnan February 2016

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Industry News

Frontline Systems releases XLMiner.com platform for advanced analytics Frontline Systems, developer of the Solver in desktop Microsoft Excel, recently released XLMiner.com, a SaaS (software as a service) platform for data mining, text mining, forecasting and predictive analytics using only a browser. XLMiner for the Web offers business analysts point-and-click tools to create predictive analytics models themselves, without being expert data scientists or programmers.

Simultaneously, Frontline Systems announced that more than 100,000 users have adopted its advanced analytics add-ins for Excel Online and Google Sheets, according to data from Microsoft and Google.The add-ins include Solver for linear and nonlinear optimization; Risk Solver for Monte Carlo simulation and risk analysis; XLMiner Analysis ToolPak for linear and logistic regression; and XLMiner Data Visualization for Excel Online.

“Rapidly growing use of advanced analytics by spreadsheet-savvy business analysts, both desktop and cloud, is a ‘stealth trend’ that many industry observers have missed,” says Daniel Fylstra, Frontline’s president and CEO. “Other vendors are talking about ‘democratizing analytics’ through easier to use tools, but Frontline has been delivering on this vision for years.”

Frontline’s Solver and XLMiner brand names have long histories, related to Microsoft Excel, but today they represent advanced prescriptive and predictive analytics tools, offered in desktop and cloud versions for spreadsheet users, application users and developers.

Frontline’s Solver for desktop Excel, first introduced with Excel 3.0 in 1990, has been included in more than 1.2 billion copies of Microsoft Office and Excel, but now Frontline’s advanced Solvers work in desktop and cloud spreadsheets, desktop and cloud versions of its RASON modeling language, and desktop and cloud Solver SDK tools for developers. XLMiner, originally an Excel add-in created by Cytel Software and marketed

by Statistics.com, was acquired by Frontline in 2011, rewritten from the ground 62 | ORMS Today

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February 2016

up to use Web UI technologies and stateof-the-art analytics algorithms, and is now available for use on the Web with spreadsheets or independently without them.

The new XLMiner SaaS application offers point-and-click access to data in uploaded spreadsheets, CSV or text files,Azure SQL databases and Apache Spark Big Data clusters – including Frontline’s own Spark cluster running 24x7 on Amazon Web Services, which has been in use by Frontline’s academic customers since June 2015. An earlier case study shows how XLMiner users can build predictive models from big data that match the accuracy of a similar HortonWorks case study using a public FAA airline data set but without any of the complexity of Hadoop, Pig, Python and other developer tools.

For years, XLMiner has been the most popular way to introduce predictive analytics, and Frontline’s Solvers have been the most popular way to introduce prescriptive analytics in MBA and undergraduate business courses. In the last seven years, more than 500,000 students have learned analytics using Frontline’s software tools. XLMiner for the Web significantly expands access to data mining, text mining, forecasting and predictive analytics tools for students (and commercial users) with MacBooks, iPad tablets, and similar devices.

While XLMiner emphasizes ease of use, especially for first-time users of predictive analytics, on its higher-level subscription plans it can handle large data sets and very challenging problems – for example finding “best subsets” of many variables via exhaustive search in multiple linear regression. It performs operations such as clustering, principal components analysis, text analysis and latent semantic indexing, and training of ensembles of neural networks or classification and regression trees on Frontline’s RASON Server – a cloud analytics platform on Microsoft Azure that also handles challenging optimization and simulation models for Frontline’s customers.

AIMMS 4.14 offers many performance improvements AIMMS recently released AIMMS 4.14, which includes the following performance improvements when solving

MIP/LP problems with CPLEX and various AIMMS WebUI features to improve the user experience: Parallel solving automatically enabled for CPLEX. The default values of the CPLEX options “Parallel mode” and “Global thread limit” have been changed for CPLEX 12.6 and higher. By default, CPLEX will now use the deterministic mode and all available threads for solving MIP problems and LP problems if the barrier algorithm is used. This can lead to significant performance improvements when solving MIP or LP problems.

Improved identifier selection for widgets. Selecting identifiers to determine the contents of a new widget, or editing an existing widget, have been improved by offering a more extended wizard. These new features make life easier for the app developer and for the end user who is changing widget contents.

‘No Changes Allowed’ feature for WebUI Apps. We added a “No Changes Allowed” feature for AIMMS WebUI Apps, preventing the end user from making changes to the setup of widgets or pages (end users can of course still change data). This feature is set through AIMMS PRO roles and thus can be differentiated per user.

Improved line up widgets. AIMMS improved the way widgets and items, such as buttons, line up to help achieve higher data densities and make Apps look better.

Shift-Click in Multi-Select Widget. Users can now use shift-click in the Multi-Select Widget to select a range of elements shown, at once.

Control save/restore WebUI State. By default an AIMMS WebUI App will save its user state (i.e., view) upon closing, and restore its state upon starting the App. As a developer, you can now have more control of this behavior, e.g., override it to not save any user state, or only save part of the user state.

Download table to .csv file. The Table widget now offers users the possibility to download its current contents to a .csv file on your local machine. This allows you to further process your data in Excel. ORMS ormstoday.informs.org

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SPECIAL ADVERTISING SECTION | View Classifieds Online at: http://www.orms-today.org

advertiser index Page #

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Gurobi Optimization

Weatherhead School of Management Visiting Faculty Position in Operations The Department of Operations invites applications for a Visiting Faculty position to begin August 2016. This is a one semester or one year appointment with the possibility of an extension for an additional year.

Although this is a full-time teaching position, we seek a faculty member with a research focus in Operations and Supply Chain Management (broadly construed). All candidates should have a Ph.D. or expect to complete a Ph.D. in the near future in Operations Management, Supply Chain Management or a related field. The candidate should be able to teach and communicate effectively to undergraduates and students in our MBA program and our master’s program (MSM) in Operations Research and Supply Chain Management. Having business experience, coursework, or other appropriate background to which business students would relate would be a plus.

Applications are accepted until the position is filled and the applicants should e-mail a c.v., copies of written research, evidence of teaching effectiveness (course evaluations, for example), and should also arrange for at least three letters of reference to be sent electronically to Ms. Tedda Nathan at oprerecruit@case.edu.

“In employment as in education, Case Western Reserve University is committed to Equal Opportunity and Diversity. Women, veterans, members of underrepresented minority groups, and individuals with disabilities are encouraged to apply.”

Case Western Reserve University provides reasonable accommodations to applicants with disabilities. Applicants requiring a reasonable accommodation for any part of the application and hiring process should contact the Office of Inclusion, Diversity and Equal Opportunity at 216-368-8877 to request a reasonable accommodation. Determinations as to granting reasonable accommodations for any applicant will be made on a case-by-case basis.

E-mail & Web Page

(Paragon Decision Technology)

info@aimms.com www.aimms.com

5, info@solver.com 7 www.solver.com

sales@gams.com www.gams.com

713.87.9341 info@gurobi.com www.gurobi.com

11, 15, 17, INFORMS 19, 21, 22, informs@informs.org 23, 27, 31, meetings@informs.org 33, 48 www.informs.org 1

LINDO Systems, Inc.

25

Northwestern University

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Optimization Direct, Inc.

info@lindo.com www.lindo.com

877.664.3347 www.predictive-analytics.northwestern.edu/info

alkis@industrialgorithms.com www.optimizationdirect.com

H T T P : / / W W W. A N A LY T I C S - M A G A Z I N E . O R G

DRIVING BETTER BUSINESS DECISIONS

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ALSO INSIDE: • Get smart: digital business innovation • Customer lifetime value: new insights • Corporate profile: BNSF Railway • What ISIS fears most: stability

Executive Edge Ernst & Young CAO Chris Mazzei on data analytics’ better half: the human element

Check out the January/February 2016 Issue of ANALYTICS Now Available at: www.analytics-magazine.org

February 2016

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ORMS Today

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ORacle

Doug Samuelson

samuelsondoug@yahoo.com

Ben-Gurion’s Parable The group gathered to watch the Super Bowl dived into the snacks and drinks as the pregame commentators chattered on. Mostly the partygoers ignored the commentators, but then Jim, an OR/MS analyst who had done quite a bit of work on healthcare, noticed a sidebar story about the Zika virus outbreak in Brazil. The commentator was explaining how this new disease outbreak could jeopardize the Olympics, as people were reluctant to make reservations to attend or were canceling reservations already made.

“Well, at least they’re paying some attention to disease threats now,” Jim growled. “Now if only we could get them to pay attention to the right one!”

His friends Jane and Fred, sitting nearest to him, acknowledged his comment with raised eyebrows.“This one sounds bad enough to me,” Jane offered,“even though that Brazilian health official they just quoted said it would turn out to be no big deal because the disease is mosquito-borne, and the Olympics will be during winter in the Southern Hemisphere, when the mosquitoes aren’t very active.”

“Yeah, right,” Jim snorted scornfully.

“Except Rio is tropical, so it never gets cold enough to squelch the mosquitoes.

But what that time of year also is, is the height of flu season, and flu is a much bigger threat.”

“Flu? Just flu?” Fred asked skeptically.

“Yeah, just flu, and that’s the point,” Jim responded.“The deadliest pandemic in history was the 1918 flu – Spanish flu, they called it, although historians’ opinions nowadays point to an origin in Kansas. It killed somewhere upward of 50 million people, worldwide, in four months – more than World War I had killed in four years.

Jim continued, “And part of the problem was that people took a while to take it seriously. Something like Ebola is dramatic, and scary, and people respond to it right away, from individuals avoiding the sick patient to public health officials taking prompt action. But just flu? People react more 64 | ORMS Today

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February 2016

there aren’t nearly enough medical facilities locally to treat them, the U.S. political candidates are screaming not to let them come back until they’re disease-free, and

If that flu had had about 7 percent lethality, like the 1918 strain, we’d have had about 5 million dead in the U.S. alone. You couldn’t do that with one H-bomb!

slowly, and by the time you know it’s bad, you can have a lot of spread.

“Remember the swine flu epidemic, as they called it, in 2011?” Jim went on.

“CDC estimated somewhere between 65 million and 82 million infected in the United States alone. Just that variation in their estimate tells you a lot about how well anyone knew how and where it spread.

Obviously all our containment strategies failed! But it was a strain that didn’t kill people it infected, so no big deal, right? Well, actually, no.We should be taking it as a warning.

If that flu had had about 7 percent lethality, like the 1918 strain, we’d have had about 5 million dead in the U.S. alone.You couldn’t do that with one H-bomb!”

“OK,” Jane nodded, “Now you’re starting to get me worried.”

“You ain’t heard nothin’ yet,” Jim continued grimly.“What if it had 50 percent lethality, like that Asian bird flu we were hearing about around the same time? Fortunately, that one wasn’t very infectious. Human-to-human spread almost never happened. But there were a couple of bright fellows who figured out how to modify it to make it highly infectious and sent their results to a major medical journal.Thank heaven one of the editors recognized why we don’t want that published and got them to modify the article! How’s that for a close call?”

“Sounds like a good plot for a scary sci-fi movie,” Ann, who had just joined the conversation, suggested.

“I’m thinking of writing it,” Jim smiled. “It could also be a good scenario for a wargame, but I’m getting frustrated trying to get the right people to host that game. I’ve been turned down already by a couple of organizations, Defense Department-connected of course, because those people just can’t see how this scenario would have anything to do with Defense operations and resources! Can you believe that? Just think about what happens when people from 250 countries are exposed,

of course half the countries in the world are blaming each other. And that’s just for a natural outbreak.What a great opportunity for a terrorist group! But the biowarfare experts I’ve talked to are still stuck thinking about people spreading diseases they consider much more damaging, like smallpox or anthrax, in a way that doesn’t involve sacrificing the people who carry the disease. Didn’t we learn from 9/11 that some of our adversaries don’t mind having a few of them get killed carrying out an attack?”

“Amazing,” Fred agreed, shaking his head in wonderment. “I hope you find a receptive audience soon.”

“I’m not optimistic,” Jim said. “I mentioned this a few weeks ago to someone who had been one of the top security planners in the last administration. She told me, ‘Oh, yes, we developed a pandemic response plan, led by the CDC, that addresses this sort of threat very well.

Take a look at that.’ So I did, and the first thing I noticed was that the most recent version of this plan that I could find was dated 2005. We already know how well that plan worked in 2011, right? So ....” “ B e t t e r g e t t o wo r k o n t h a t screenplay,” Jane laughed.

“Yeah,” Jim shrugged, “and I think the first thing in it will be one of my favorite quotes, from David Ben-Gurion in his last ‘seminar’ with his senior military commanders: ‘The greatest danger to our security is inertia in the thinking of those responsible for security.’ Nailed it, didn’t he?” ORMS Doug Samuelson is president and chief scientist of InfoLogix, Inc., in Annandale, Va. For more information, see “Can OR/MS Detect ‘The Coming Plague’?” OR/MS Today, June 2008, which cites several other sources.

ormstoday.informs.org

CPLEX Optimization Studio®.

Still the best optimizer and modeler for the energy industry.

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CPLEX Optimization Studio is well established as the leading, complete optimization software. For years it has proven effective in the energy industry for developing and deploying models and optimizing business decisions.

Now there’s a new way to get CPLEX – direct from the optimization industry experts.

Find out more at optimizationdirect.com The IBM logo and the IBM Member Business Partner mark are trademarks of International Business Machines Corporation, registered in many jurisdictions worldwide. *IBM ILOG CPLEX Optimization Studio is trademark of International Business Machines Corporation and used with permission.

OPTIMIZATION GENERAL ALGEBRAIC MODELING SYSTEM High-Level Modeling The General Algebraic Modeling System (GAMS) is a high-level modeling system for mathematical programming problems. GAMS is tailored for complex, large-scale modeling applications, and allows you to build large maintainable models that can be adapted quickly to new situations. Models are fully portable from one computer platform to another.

State-of-the-Art Solvers GAMS incorporates all major commercial and academic state-of-the-art solution technologies for a broad range of problem types.

GAMS Integrated Developer Environment for editing, debugging, solving models, and viewing data.

Optimizing to combat Climate Change: CO2 Capture, Utilization, Transport, and Storage The electricity generation sector in the U.S. is a major contributor of CO2 emissions. Thus reductions from this sector will play a central role in any coordinated CO2 emission reduction effort aimed at combating climate change. One technology option that may help the electricity generation sector meet this challenge is Carbon Capture and Storage (CCS).

The U.S. Department of Energy uses GAMS to analyze potential CO2 emission reduction scenar-

Graphical representation of the NETL CO2 CTUS model and NEMS integration

ios in which CCS may play a role in meeting emission goals. The NETL CO2 CTUS model developed

When integrated into the National Energy Mod-

by the DOE National Energy Technology Labora-

eling System (NEMS) a detailed portrayal of

tory is written in GAMS. It optimizes on a least

CCS in energy economy projections is ren-

cost basis potential networks of CO2 pipelines and

dered. A version of CTUS has been modified

storage infrastructure amenable to handling the

and incorporated into the U.S. Energy Informa-

transport and storage of captured CO2 from CCS

tion Administration's (EIA's) version of NEMS,

systems.

and is in turn used to produce the Annual Energy Outlook.

For detailed information please contact Charles A. Zelek - Charles.Zelek@netl.doe.gov.

www.gams.com