A Path to Insights and Improved Decision Making: Predictive Analytics by GovLoop

A Path to Insights and Improved Decision Making:

Predictive Analytics Industry Perspective

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Predictive Analytics Overview Today, government is challenged like never before. In an era of budget cuts, increasing demands for services, and increasingly complex government transactions, government officials are pressed to think of new ways of thinking and innovative solutions to complex problems. Throughout this report, Nathan Greenhut, IBM Center of Competence Social Segment, identifies predictive analytics as a way forward to cut through governmentâ&#x20AC;&#x2122;s most pressing challenges. This report also highlights the use of predictive analytics by the Memphis Police Department to improve the public safety for the citizens of Memphis, Tennessee. Although government is becoming increasingly complex, and citizens and agencies are producing high volumes of data, predictive analytics can provide a path to insights and improved decision making for public sector entities.

Nathan Greenhut Government Center of Competence Social Segment IBM

A Path to Insights and Improved Decision Making:

Predictive Analytics

Everyday government officials are working to transform how government operates. In a time when budgets are rapidly shrinking, while there is also an increased demand on government services, government is challenged to find new models of thinking and reframe the traditional view of how government provides services. Recently Pat Fiorenza, GovLoop Research Analyst, had the chance to speak with Nathan Greenhut, IBM Government Center of Competence - Social Segment, about the power of predictive analytics and the ways agencies can use data to transform service delivery. Unquestionably, the state of public sector budgets has sculpted and impacted the public sector’s ability to provide services. Nathan and Pat discussed that budget deficits have slowed investment and increased pressures to stop fraud and errors. Government organizations are looking for solutions for lowering

their operational costs, while increasing ability to handle rising caseloads to deliver better and more effective services for the citizens. As the economy slowly recovers, there are increased pressures on government to provide much needed services to constituents. Although the budget is the core challenge, another challenge facing government is that as new forms of technology are being implemented, risks are becoming more pervasive. With increasing use of cloud services to store big data and facilitate collaboration across agencies, there is increased security risks to compromise government data. Nathan states, “Evasion schemes and scams appear more sophisticated and more global. Schemers are using technology to make evasion faster and easier. Fraud, waste, abuse and error drain resources and undermine public support. In addition, inconsistent decisions and strategies are creating serious risks.”

As Nathan identifies, there are dire consequences for the public sector if information is lost or stolen. With dozens of efforts by government to stop waste, fraud and abuse, securing government data is essential for any technological initiative. With the variety of data that is created, and with the use of predictive analytics, the core challenge for agencies is how to best drive decisions from data. Nathan states, “Government agencies are challenged to turn data into actionable information on a timely basis. The size of data of social industry is rapidly growing causing more time to decipher data into usable information.” Nathan continued, “There is pent up demand from operations for unified and timely information and predictions. Also, there is demand for improved processes to provide services with greater impact, consistency, transparency, reliability and effectiveness.”

Although now is a challenging time for government, there has been much room for innovation in government. As technology has rapidly evolved, there are now new, innovative technological solutions to help

44X

information is exploding

sOURCES OF INSIGHT ARE MULTIPLYING

DIGITAL DATA GROWTH THROUGH 2020

PERCENT OF INFORMATIONUNSTRUCTURED CONTENT

The chart above describes the current state of data and how much data is created by users, Nathan also provides a fanastic overview, stating, “The volume and variety of information (structured and unstructured) is exploding. Turning data into information and then into action is becoming more important than ever before.”

organizations meet their most pressing organizational challenges. Further, the multiple kinds of data that is created by customers through services, agencies are now challenged to turn various kinds of data into insights.

percent of mission leaders have more data than they can use effecitvely

percent increase in performance by organizations that apply analytics

technological infrastructure and a plan for how to use data, agencies will be lost in the tsunami of data that is being created.

This is where predictive analytics comes into play for government agencies, and holds great promise for the public sector to meet citizen demand. For government agencies, the power of analytics Nathan continues,“There is a larger rest in the agency’s ability to burden placed on organizations, transform data into knowledge. as the volume and variety of information grows. This makes Nathan stated, “Predictive analytics a larger inertia to go from data can be used for determining rich and information poor to events or outcomes before they information rich. Also, planning happen, simulation of a process to for the size and shape of data is determine bottlenecks and risks growing in importance to ensure as well as in “what-if ” scenarios the pipelines are built for the flow to determine the “best” course of of data, information and action.” action. For fraud, abuse, waste and error predictive analytics Without a plan of action, a strong can be used to ensure the proper

change outpacing the ability to keep up

Performace gap is widening Data Cited from: Fraud and Error Management in Social Security and Revenue Agencies

TOP TEN BENEFITS OF PREDICTIVE ANALYTICS : 1. Smarter detection 2. Prioritize workloads 3. Monitor progress and KPI’s 4. Detect patterns to initiate action 5. Aggregate and correlate information 6. Optimize processes and performance 7. Identity insights and relationships insights 8. Catch suspicious trends before loss occurs 9. Achieve improved collaboration and control 10. Embed logic into case management systems

hurdles are placed for schemers and scamers to have to climb over.” Armed with these kinds of insights, government agencies can make smarter business decisions and redefine business operations. One of the best case studies about predictive analytics comes from the Memphis, Tennessee Police Department. Larry Godwin, Director of Police Services, Memphis Police Department, recently was profiled in an IBM Smarter Planet Leadership Series Report, highlighting the “Blue CRUSH” (Criminal Reduction Utilizing Statistical History) program. GovLoop also recently hosted a webinar, speaking with Dr. Janikowski, another key player in the development of the Blue CRUSH program. Under Larry’s direction, the Memphis Police Department has started to try and tackle crime through innovative strategies, predominantly focusing on predictive crime prevention practices. Larry called together colleagues and began to explain the dire situation facing the police department. As with many local governments, Memphis faced shrinking budgets,

disillusioned citizens, and was challenged to think of new ways to curb trends of rising crime. With Larry setting the stage and explaining the situation facing the city, representatives from the Organized Crime Unit, District Attorney General Bill Gibbons, and Dr. Richard Janikowski, a professor of Criminology at the University of Memphis, started to think through innovative solutions to curtail rising crime in a time of fiscal austerity. Professor Janikowski had worked on a variety of analytical initiatives to understand crime data. At the University of Memphis, Professor Janikowski also served as the Director of the Center for Community Criminology and Research. An IBM report states, “Now, with the MPD requesting his input, Janikowski saw the opportunity to put into practice the simple yet powerful principle that “If you focus police resources intelligently by putting them in the right place, on the right day, at the right time good things are going to happen,” says Janikowski.

“by Ifputting you focus police resources intelligently them in the right place, on the right day, at the right time good things are going to happen,” says Dr. Richard Janikowski, Associate Professor of Criminal Justice, Memphis University.

”

“

Godwin’s aim was to show how the intelligent alignment of police resources would effectively enable the department to close the manpower gap now—a must in the eyes of Memphis’s citizens.

” After some initial success, Larry decided to again go against the grain, and share crime data with Professor Janikowski’s team. Using this preliminary data, Professor Janikowski was able to build a pilot program to look into ways to reduce crime in the city. The results in the initial pilot were through the roof. The IBM report states: “A few months later, that effort materialized into a three-day operation that proved to be one of the most effective ever. By identifying hot spots at a granular level, MPD made some 70 arrests in just the first two hours—a number usually made on an average weekend—and went on to make a total of 1,200, with crimes ranging from drugs to weapons charges to prostitutionand other “quality-of-life” offenses.” After the initial results, Larry realized the potential of the program, but knew that the success would require operational support from each department. To keep the program moving forward, Larry developed a business case for the mayor, highlighting the dire state of the budget, and the need to find solutions to complex problems in new and innovative ways.

“Godwin’s aim was to show how the intelligent alignment of police resources would effectively enable the department to close the manpower gap now—a must in the eyes of Memphis’s citizens. Under the plan Godwin proposed, each precinct commander in the MPD would be given the resources (in the form of overtime funding) and flexibility to make

their own deployment decisions based on intelligence provided by the solution. Most importantly, results would be rigorously measured and commanders held accountable for their performance. It didn’t take much selling, because a few hours later, Godwin and the mayor were standing in front of the press touting the newly approved program—which came to be known as Blue CRUSH—as a way to intelligently reduce crime.” Since Blue CRUSH has been implemented, there has been a decline in crime in Memphis. The City reports a decrease of 30% reduction of serious crime, and a 15% reduction in violent crime. Blue CRUSH allows the police department to be more productive and efficient how they use their crime data. The IBM report does a great job identifying how the system works, as the report mentions, the goal is to

“police smarter, not harder.”

30% Reduction in Serious Crime

15%

Reduction in violent Crime

With BlueCRUSH being a successful case study – where can other agencies start with a predictive analytics strategy? At the heart of predictive analytics is data. Nathan states, “Overall, there is a major drive for big data in government. The main challenge on this end of the data spectrum is that most government agencies have trouble managing their data yet alone, performing predictive analytics on the data that they have.” Nathan keenly observed, “There is not only a need for big data to open up analysis possibilities tomorrow, but also a need for the right data and information for action today.” During the interview, Nathan acknowledged that a predictive analytics program cannot happen without the right skill set and employees. Nathan states, “My recommendation is to have someone who has done a number of predictive analytics assignments and knows a variety of data sources as well as agency subject matter experts (SME’s) team up to determine what the most valuable data is for the agency. This will help to keep the scope in check on a particular project and get results and payback much quicker.” Nathan provides more insights as to the type of workforce needed for predictive analytics, “For predictive analytics to run smoothly a range of skillsets are needed. There is a need for technical, process SMEs, subject area SMEs, analysts, project managers and decision makers for a predictive analytics project to be run well. Smaller projects may use as little as an analyst to get started. If the work going into turning data into actionable information

will have a great impact, usually many of the folks listed above as well as some others (trainers, documenters, etc.) are needed as well.” Once the workforce is set and the data is understood, Nathan advises the following for agencies to get started with predictive analytics. Nathan believes that most government agencies already have in place at least some approaches to manage predictive analytics, to mitigate risky events or increase rewarding events, some examples that Nathan identified were audit and sampling processes, rules based interventions, ad hoc reports and analyses and full investigations. Nathan also provides some targeted and important questions that should be asked while working on a predictive analytics plan, some questions that Nathan posed included: What is the key business problem to solve? What existing capabilities does the organization have? What is the state of my data the data I want to predict from? As part of the mission of GovLoop is facilitating knowledge sharing and information around core topics facing government professionals, Nathan was sure to provide some best practices for those already engaged or about to engage in a predictive analytics campaigns recommended:

• Make sure there is a document with major system/process changes for the agency. When pulling together predictive analytics you will want to know when these events occur. • Determine the “just right data” upfront. If you place all the data you have into predictive analytics right away, you may get jammed up. It is best to start small and think strategically about how to integrate predictive analytics into the right processes or even the right process step. • Using technology tools to prioritize the benefits, claims, and payments allows smart people to do their jobs better. • Start projects small but think about the longer term strategically • False positives need to be handled with greater care. For example, do not identify an error as fraud and fraud as an error. Both of these have a very high cost • Prioritize your output, since you do not want too much information to read through, but want the right information.

Predictive analytics holds great of other analytics in the future, such promise for government agencies, as entity, social network and content Nathan states: analytics to give a more rich picture of the predictions and a higher “Generally speaking, analytics will degree of precision and accuracy.” be used in more processes to predict outcomes with a greater degree of Nathan also believes that new groups accuracy and less false positives. of professionals, such as human Additionally, predictive analytics resources workers, politicians, will become more real time and and judges, will use predictive involve more datasets (internal analytics for a larger set of use cases and external to the government and to make informed decisions. agency) and go more mobile.” Finally, Nathan states, “Government He continued, “The main drivers of workers in the future will have more this is the decreasing cost of units access to predictive analytics “at of storage, computing speed and their finger tips” and the analyst role displays. In addition, predictive will be more pervasive and useranalytics will incorporate more forms friendly. At a certain point there will

be predictive analytics incorporated into processes and tasks that we are not actively aware of.” Predictive analytics certainly holds great promise for government agencies. As government agencies are challenged to think of new and innovative ways to deliver on services, predictive analytics offers a way forward to transform agency wide service delivery. If you are interested in learning more about predictive analytics, be sure to check out some of the following resources that GovLoop and IBM offer surrounding predictive analytics.

IBM Resources: • Miami Dade - Improving Government Systems with Cognos on z - IBM Client Reference Video • How Big Data is Changing the World :Jeff Jonas IBM • New York State Tax: Smarter Planet Leadership Series Video • IBM LS NY state Tax • IBM Government Industry Framework for Social Services Demo • Alameda County Social Services - IBM Smarter Planet Leadership Series Video

GovLoop Resources: • IBM Report Highlights the Power of Predictive Analytics • Understanding Customers Through Predictive Analytics • IBM’s Charles Prow Discusses Strategies to Enhance National Competitiveness • Analytics to Outcomes

About IBM

The world isn’t just getting smaller and flatter, it is also becoming more instrumented, inter- connected and intelligent. As we move toward a globally integrated economy, all types of governments are also getting smarter. IBM provides a broad range of citizen centered solutions to help governments at all levels become more responsive to constituents, improve operational efficiencies, transform processes, manage costs and collaborate with internal and external partners in a safe and secure environment. Governments can leverage the unparalleled resources of IBM through IBM Research, the Center for the Business of Government, the Institute for Electronic Government and a far-reaching ecosystem of strategic relationships. To learn more, visit ibm.com/government.