From unicorns to race horses. Es el momento de Machine Learning para Excelencia Operacional

FROM UNICORNS TO RACEHORSES: Taking Predictive Analytics with Machine Learning from Myth to Business Reality

What Minitab offers PRODUCTS:

Powerful statistical software everyone can use.

Integrated project tools and reporting to manage Continuous Improvement.

Online learning solution to master statistics and MinitabÂŽ anytime, anywhere.

Powerful data mining with machine learning and predictive analytics.

SERVICES:

Training Public courses or onsite training matched to your requirements.

Statistical Consulting Personalized help with your statistical and analysis challenges from experts.

Support Assisting your use of the software, installation and implementation.

Meet the Presenter:

Gillian Groom Technical Training Specialist, Minitab

Throughout her career, Gillian has been applying statistical analysis to guide informed management decisions on business opportunities or problems.

Gillian has a Master's Degree in Probability and Statistics from Sheffield University.

Š 2019 Minitab, Inc.

The Digital Transformation Race

The Winning Post Fully Integrated Digital Transformation

Analytic talent Smart Factory

Machine Learning

Industry 4.0

Real-time data

IT Infrastructure

Internet of Things Predictive Analytics

Project management

Š 2019 Minitab, Inc.

How many years do you think it will take your overall industry to realize the potential of the Digital Transformation ?

Š 2019 Minitab, Inc.

Where Machine Learning Fits?

Data Information

Machine Learning

Actionable Decisions

Machine Learning is one of many Predictive Modelling Techniques

Š 2019 Minitab, Inc.

The majority of manufacturing operations do not currently use machine learning in operations, asset management or field operations.

Š 2019 Minitab, Inc.

Myth #1 : Machine Learning is new

Logistic Regression 1958

(selected methods)

K-nearest neighbors 1967

Decision Tree 1986

Random Forest 1995

Support Vector Machine 1963 Artificial Neural Networks 1975

Š 2019 Minitab, Inc.

Fact #1: Technology Delivers the Opportunity to use Machine Learning

Minitab 1972

(selected technology)

Windows PC 1985

Cloud Networks 2009

Google – 30 Trillion Pages 2018

SPM 1983 World Wide Web 1991

Š 2019 Minitab, Inc.

What changed is the volume of data available now due to digitalization

 Computer power and storage has become a commodity with faster access  More data is being collected  With the emergence of AI/AR use in commercial applications, the need to convert data into information & decisions is growing exponentially  This will continue to grow as more data is stored in digital form

© 2019 Minitab, Inc.

©Copyright Minitab® and Market Strategy Group, 2018

© 2019 Minitab, Inc.

©Copyright Minitab® and Market Strategy Group, 2018

Big Data, Talent, Cloud are Top Present Challenges

© 2019 Minitab, Inc.

Myth #2

Predictive Analytics Requires Big Data

Š 2019 Minitab, Inc.

Fact #2: Suitable Analytic Tools Exist for All Data Types & Sizes

Problem Definition + Data Available + Right Analytic Technique = Evidence based Decision Making

Š 2019 Minitab, Inc.

Data

Data

Myth #3:

Machine Learning is the Complete Tool for Quality Improvement

Š 2019 Minitab, Inc.

Fact #3: Analytics are Part of the Framework for Driving Improvement  As is true for all problem solving initiatives, teams benefit from structured methodology:  CRISP-DM  DMAIC  SEMMA These Frameworks define the problem, the data and analytics

© 2019 Minitab, Inc.

©Copyright Minitab® and Market Strategy Group, 2018

Big Data, Talent, Cloud are Top Present Challenges

© 2019 Minitab, Inc.

Myth #4: You Need a Data Scientist to Deliver Predictive Analytics Data science is a powerful combination of various disciplines.

Computer Science Skills  Programming  Big data technologies

Data Science

Math and Statistics Knowledge  Machine Learning  Ensemble models  Anomaly detection

Domain Expertise  Business knowledge  Expert systems  User testing

© 2019 Minitab, Inc.

Where to Find this Ideal Data Scientist

Š 2019 Minitab, Inc.

Fact #4: With the Right Process, Tools and Training

Data science is the process of extracting information, understanding and learning from raw data to inform decision making in a proactive and systematic fashion that can be generalized.

A key aspect of data science is the utilization of the scientific method to form and challenge hypotheses to validate conclusions about data.

You already have Racehorses to run the Digitalisation Race

Š 2019 Minitab, Inc.

Myth #5 : Data Scientists Can Quickly Acquire Domain Expertise Computer Science Skills  Programming  Big data technologies

Data Science

Math and Statistics Knowledge  Machine Learning  Ensemble models  Anomaly detection

Domain Expertise  Business knowledge  Expert systems  User testing

© 2019 Minitab, Inc.

Fact #5: Process Owners know the Problems that Need Resolving  Address in-field reliability for smart components  Automatic temperature adjustment in a production process  To understand which areas of an airline wing behave differently than the other parts in terms of vacuum levels to improve performance and to ultimately optimize the # of sensors needed  Root Cause Analysis for leakage in a pressure valve A data scientist, will require time to develop this process expertise

© 2019 Minitab, Inc.

Myth #6:

Predictive Analytics with Machine Learning Requires Programming Skills Š 2019 Minitab, Inc.

Fact #6: Minitab & SPM Designed For Business Users to Deliver Predictive Analytics

Focus Time & Effort on Interpreting Results not Number Crunching

Š 2019 Minitab, Inc.

What do these Digitalisation Winning Racehorses Look Like?

Brain – Logical, organised, computer literate, analytical problem solvers

Shoulders – Broad, good at taking responsibility and leading Muscles – Able to absorb new ideas and continually train and adapt to the changing environment

Feet – Steady, reliable but agile, taking sensible size steps to reach the goal

Heart – Passionate about improving the business performance

Legs – Tireless at getting to the root cause of problems and keeping projects moving

© 2019 Minitab, Inc.

Digitalisation Race Winners

• It will not be achieved solely with technology • It will not be done solely with predictive analytics and machine learning • It will not be addressed solely with trained resources Organisations need to determine the balance and cadence of these factors, within the strategy to execute.

© 2019 Minitab, Inc.

Take away – We are all at various stages of the digitalization race

 This truly is a journey, no one is there yet  Assess the current state, define goals and plan a series of well-placed projects to propel the journey forward  The Operations Excellence groups provide a head start for the digital industrial transformation because they are experts in project selection, project execution, data analysis and change management

© 2019 Minitab, Inc.

Taking Predictive Analytics with Machine Learning from Myth to Business Reality AN ORGANIZATION’S JOURNEY

Gillian Groom Racehorse Trainer, Minitab Ltd

More Resources:  TRAINING: Enhance your skills with Minitab’s industry training courses  FREE CONSULTATION: Which analysis software is right for you?  ONLINE RESOURCES:  Webinars & Videos  Ebooks  Articles on our blog

Learn more at Minitab.com

Insights Events:  Run across the globe, conferences and workshops  Find our next event near you!

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