Predictive Analytics Times
Exclusive Highlights
Wise Practitioner – Predictive Analytics Interview Series: Edward Shihadeh at Auspice Analytics, LLC
 In anticipation of his upcoming conference presentation, How to...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Emily Pelosi at CenturyLink
 In anticipation of her upcoming Predictive Analytics World for Workforce conference...
Wise Practitioner – Predictive Analytics Interview Series: Holly Lyke-Ho-Gland and Michael Sims at APQC
 In anticipation of their upcoming conference co-presentation, Change Management...
Wise Practitioner – Predictive Analytics Interview Series: Natasha Balac at Data Insight Discovery, Inc.
 In anticipation of her upcoming conference co-presentation, Identifying Unique...
Wise Practitioner – Predictive Analytics Interview Series: Bryan Bennett at Northwestern University
 In anticipation of his upcoming conference presentation, Cross-Enterprise Deployment: ...
Wise Practitioner – Predictive Analytics Interview Series: David Talby at Atigeo
 In anticipation of his upcoming conference presentation, Semantic Natural...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Haig Nalbantian at Mercer
 In anticipation of his upcoming Predictive Analytics World for...
Book Review: Weapons of Math Destruction by Cathy O’Neil
 Originally published in Analytics Magazine Book: Weapons of Math...
Wise Practitioner – Predictive Analytics Interview Series: Angel Evan at Angel Evan, Inc.
In anticipation of his upcoming conference co-presentation, Identifying Unique...
Wise Practitioner – Predictive Analytics Interview Series: Paul Speaker at The Dow Chemical Company
 In anticipation of his upcoming conference presentation, Creating an...
Wise Practitioner – Predictive Analytics Interview Series: George Iordanescu at Microsoft
 In anticipation of his upcoming conference presentation, Predictive Analytics...
Wise Practitioner – Predictive Analytics Interview Series: Afsheen Alam at Allstate Insurance
 In anticipation of her upcoming conference presentation, Our Success...
Wise Practitioner – Predictive Analytics Interview Series: Jennifer Bertero at CA Technologies
 In anticipation of her upcoming conference presentation, Redefining Analytics...
Wise Practitioner – Predictive Analytics Interview Series: Michael Dessauer at The Dow Chemical Company
 In anticipation of his upcoming conference presentation, Listening Down...
Wise Practitioner – Predictive Analytics Interview Series: Steven Ulinski at Health Care Service Corporation
 In anticipation of his upcoming conference presentation, Challenges of...
Wise Practitioner – Predictive Analytics Interview Series: Lauren Haynes at The University of Chicago
 In anticipation of her upcoming conference presentation, Data Science...
Wise Practitioner – Predictive Analytics Interview Series: Daqing Zhao at Macy’s
 In anticipation of his upcoming conference presentation, Macy’s Advanced...
Wise Practitioner – Predictive Analytics Interview Series: Thomas Schleicher at National Consumer Panel
 In anticipation of his upcoming conference presentation, Combining Inferential...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Kevin Zhan at The Advisory Board
 In anticipation of his upcoming Predictive Analytics World for Workforce conference...
Wise Practitioner – Predictive Analytics Interview Series: Halim Abbas at Cognoa
 In anticipation of his upcoming conference presentation, Early Screening...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Ben Taylor at HireVue
 In anticipation of his upcoming Predictive Analytics World for Workforce conference...
Employee Life Time Value and Cost Modeling
 Understanding the Most Expensive Asset Practically every business shares...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Andrew Marritt at OrganizationView GmbH
 In anticipation of his upcoming Predictive Analytics World for Workforce conference...
Interview with Eric Siegel: Popularizing Predictive Analytics with Song and Dance
  Originally published in l’ADN (in French) Hilarious consultant,...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Sue Lam at Shell
 In anticipation of her upcoming Predictive Analytics World for Workforce conference...
Case Study: Hotel Occupancy Forecasting’s Big Payoff
 This Predictive Analytics story started with a question as...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Mike Rosenbaum at Arena
  In anticipation of his upcoming Predictive Analytics World for...
Wise Practitioner – Predictive Analytics Interview Series: Darryl Humphrey at Alberta Blue Cross
  In anticipation of his upcoming conference presentation, Claim...
The Evolving State of Retail Analytics in CRM
  The Traditional State The world of retail has...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Feyzi Bagirov at 592 LLC and Harrisburg University of Science and Technology
 In anticipation of his upcoming Predictive Analytics World for Workforce conference...
Wise Practitioner – Predictive Analytics Interview Series: Craig Soules at Natero
  In anticipation of his upcoming conference presentation, Using...
Sound Data Science: Avoiding the Most Pernicious Prediction Pitfall
  In this excerpt from the updated edition of...
Wise Practitioner – Predictive Analytics Interview Series: Ashish Bansal and John Schlerf from Capital One
  In anticipation of their upcoming conference co-presentation, The...
Wise Practitioner – Predictive Analytics Interview Series: Kristina Pototska at TriggMine
  In anticipation of her upcoming conference presentation, 7...
Wise Practitioner – Predictive Analytics Interview Series: Frédérick Guillot at The Co-operators General Insurance Company
  In anticipation of his upcoming conference presentation, Defining...
Predictive Analytics vs. Prescriptive Analytics
  We have all heard and seen the diagrams...
Interview with Prof. Dr. Wil van der Aalst, Eindhoven University of Technology
  Exclusive interview with Prof. Wil van der Aalst...
Data Story Telling: Bringing Life to Your Data
  There is no doubt that a successful Data...
Contextual Experience Innovation
  [Title Image Abbreviations: CRM – Customer Relationship Management,...
Are Random Variables a Fact of Life in Predictive Models?
  In some of the more recent literature, discussion...
Managing Shifting Priorities in Exploratory Data Science Projects
  After working with a client’s data for over...
Breaking into Analytics: 5 “Musts” for your Career Transition
  In our data-rich society, corporations of all types...
How Predictive Analytics Can Fuel Innovation for Manufacturing
  Industry leaders like to use the term “culture”...
Rexer Analytics Data Science Survey – Highlights (New)
  White Paper with 2015 survey results available now....
How Can Predictive Analytics Help Your Bank or Fintech Company?
 Predictive analytics encompasses a powerful set of methods that...
The Role of Feature Engineering in a Machine Learning World
 Artificial Intelligence(AI) continues to be the next great topic...
The Expansive Deployment of Predictive Analytics: 22 Examples
  The future is the ultimate unknown. It’s everything...
Nine Bizarre and Surprising Predictive Insights from Data Science
  Data is the world’s most potent, flourishing unnatural...
The Trick to Predictive Analytics: How to Bridge the Quant/Business Culture Gap
  This article is excerpted from Eric Siegel’s foreword...
Wise Practitioner – Predictive Analytics Interview Series: Robin Thottungal at U.S. Environmental Protection Agency
 In anticipation of his upcoming conference keynote presentation, 21st...
How Hillary for America Is (Almost Certainly) Using Uplift Modeling
  In this article, I provide evidence that Hillary...
Wise Practitioner – Predictive Analytics Interview Series: Miguel Castillo at U.S. Commodity Futures Trading Commission
  In anticipation of his upcoming conference co-presentation, Words...
Wise Practitioner – Predictive Analytics Interview Series: Michael Berry of TripAdvisor Hotel Solutions
  In anticipation of his upcoming keynote co-presentation, Picking...
Exploring the Toolkits of Predictive Analytics Practitioners — Part 2
 Continuing on our discussion from last month on toolkits...
The Danger of Playing It Safe
  Research shows that people tend to be overly...
Manufacturing Operations: Machine Learning to Separate Actionable Trends from False Alarms
 Predictive analytics is increasingly becoming the object of value...
Predictive Analytics Basics: Six Introductory Terms and The Five Effects
  Here are six key definitions—and The Five Effects...
Wise Practitioner – Predictive Analytics Interview Series: Ken Yale at ActiveHealth Management
  In anticipation of his upcoming keynote co-presentation at...
Wise Practitioner – Predictive Analytics Interview Series: Frank Fiorille at Paychex, Inc.
  In anticipation of his upcoming conference presentation, Risk...
The Real Reason the NSA Wants Your Data: Predictive Law Enforcement
  The NSA can leverage bulk data collection with...
Wise Practitioner – Predictive Analytics Interview Series: Scott Zoldi at FICO
  In anticipation of his upcoming conference keynote presentation,...
Wise Practitioner – Predictive Analytics Interview Series: Thomas Klein at Miles & More GMbH
  In anticipation of his upcoming conference co-presentation, Using...
Book Review: Predictive Analytics for Newcomers and Nontechnical Readers
  The book reviewed in the article, Predictive Analytics:...
Wise Practitioner – Predictive Analytics Interview Series: Meina Zhou at Bitly
  In anticipation of her upcoming conference presentation, Predictive...
Wise Practitioner – Predictive Analytics Interview Series: Dr. Shantanu Agrawal at Centers for Medicare & Medicaid Services
  In anticipation of his upcoming conference keynote presentation,...
Infographic – Discover Predictive Analytics World for Business 2016
  Predictive Analytics World continues to grow – take...
Exploring the Tool kits of Predictive Analytics Practitioners — Part 1
 Tools, tools, and more tools continue to explode in...
The Power of Data Science for Predictive Maintenance is Only Just Being Tapped
 Future of Automotive Servicing and Preventive Maintenance Several months...
Wise Practitioner – Predictive Analytics Interview Series: Madhusudan Raman at Verizon
  In anticipation of his upcoming conference presentation, Best...
Need a Data Scientist? Try Building a ‘DataScienceStein’
 Organizations are finding that hiring qualified Data Scientists is...
Wise Practitioner – Predictive Analytics Interview Series: Sanjay Gupta at PNC Bank
  In anticipation of his upcoming conference co-presentation, Predictive...
Wise Practitioner – Predictive Analytics Interview Series: Brian Reich, Former Director at The Hive
  In anticipation of his upcoming conference presentation, The...
AnalyticOps: A New Organizational Role So Your Company Can Monetize Analytics
 There is no doubt that data science–and predictive analytics–...
Wise Practitioner – Predictive Analytics Interview Series: Gary Neights at Elemica
  In anticipation of his upcoming conference presentation, Predicting...
Getting Started with Predictive Analytics – an Interview with Eric Siegel
  Data science and predictive analytics are top of...
Wise Practitioner – Predictive Analytics Interview Series: Dr. Sarmila Basu at Microsoft Corporation
  In anticipation of her upcoming conference presentation, Predictive...
Are Pre-hire Talent Assessments Part of a Predictive Talent Acquisition Strategy?
  Over the past 30+ years, businesses have spent...
Wise Practitioner – Predictive Analytics Interview Series: Dae Park and Vijay D’Souza at Government Accountability Office (GAO)
  In anticipation of their upcoming conference co-presentation, Characteristics...
Wise Practitioner – Predictive Analytics Interview Series: Dean Abbott of SmarterHQ
 In anticipation of his upcoming conference presentation, The Revolution...
Opportunities and Challenges: Predictive Analytics for IoT
 There is a clear sense in the marketplace today...
Feature Engineering Within the Predictive Analytics Process — Part Two
 In the last article, I discussed the concept of...
HBO Teaches You How to Avoid Bad Science
  Do you know what p-hacking is? John Oliver...
Jim Sterne’s Book Review of “Predictive Analytics” by Eric Siegel
  Book review originally published in the journal Applied...
The Big Picture: Today’s Data Analytics Stack
 Enterprises are inundated with data from social, mobile, IoT...
Taking Action on Technical Success: A Fable of Data Science and Consequences
 Note: This story is fiction, but it is based...
Analytics is (often) a Faith-Based Business
 If you follow data science topics in various social...
Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Chris Labbe at Seagate Technology
  In anticipation of his upcoming Predictive Analytics World for...
Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Peter Frankwicz at Elmet Technologies
  In anticipation of his upcoming Predictive Analytics World for...
Wise Practitioner – Text Analytics Interview Series: Dirk Van Hyfte at InterSystems Corporation
  In anticipation of his upcoming conference co-presentation, Personalized...
Wise Practitioner – Text Analytics Interview Series: Michael Dessauer and Justin Kauhl at The Dow Chemical Company
  In anticipation of their upcoming conference co-presentation, Understanding...
Women in Data Science
 The field of Data Science is booming, yet comparatively...
Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Edward Crowley at The Photizo Group, Inc.
  In anticipation of his upcoming Predictive Analytics World for...
Boosting Performance of Machine Learning Models
  People often get stuck when they are asked...
Wise Practitioner – Predictive Analytics Interview Series: Tanay Chowdhury at Zurich North America
  In anticipation of his upcoming conference presentation, Deep...
Feature Engineering within the Predictive Analytics Process — Part One
  What is Feature Engineering One of the growing...
The Executive’s Guide to Employee Attrition
 Much has been written about customer churn – predicting...
Wise Practitioner – Predictive Analytics Interview Series: Lawrence Cowan at Cicero Group
  In anticipation of his upcoming conference presentation, Data...
Wise Practitioner – Text Analytics Interview Series: John Herzer and Pengchu Zhang at Sandia National Laboratories
  In anticipation of their upcoming conference co-presentation, Enhancing...
Wise Practitioner – Text Analytics Interview Series: Emrah Budur at Garanti Technology
  In anticipation of his upcoming conference presentation, Tips...
Wise Practitioner – Predictive Analytics Interview Series: Thomas Schleicher at National Consumer Panel
  In anticipation of his upcoming conference presentation, Using...
Ghosts in the Data, Constructing Data Entities
 Data Entities are seldom discussed concepts that primarily hide...
Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Dr. Matteo Bellucci at General Electric
  In anticipation of his upcoming Predictive Analytics World for...
HR’s First Predictive Project? Pre-hire Candidate Screening
  Corp recruiters have a very important and difficult...
Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Gary Neights at Elemica
  In anticipation of his upcoming Predictive Analytics World for...
Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Jeffrey Banks at The Applied Research Laboratory at The Pennsylvania State University
  In anticipation of his upcoming Predictive Analytics World for...
Wise Practitioner – Text Analytics Interview Series: Frédérick Guillot at Co-operators General Insurance Company
  In anticipation of his upcoming conference presentation, Leveraging...
Wise Practitioner – Predictive Analytics Interview Series: Alice Chung at Genentech
  In anticipation of her upcoming conference co-presentation, Utilizing...
Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Carlos Cunha at Robert Bosch, LLC
  In anticipation of his upcoming Predictive Analytics World for...
5 Common Mistakes Multi-Channel Retailers Make, and How to Avoid Them
  Multi-channel retailers are often finding themselves stuck in...
Three Critical Definitions You Need Before Building Your First Predictive Model
 Portions excerpted from Chapter 2 of his book Applied...
Measurement and Validation: An Often Underrated Aspect within the Predictive Analytics Discipline
 In our Big Data world, software applications and programming...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Haig Nalbantian at Mercer
  In anticipation of his upcoming Predictive Analytics World for...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Pasha Roberts at Talent Analytics, Corp.
  In anticipation of his upcoming Predictive Analytics World for...
Improving Word Clouds as Tool for Text Analytics Data Visualization
  Rich Lanza will present Using Letter Analytic Techniques...
Dr. Data’s Music Video: The Predictive Analytics Rap
  With today’s release of “Predict This!” – the...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Geetanjali Gamel from MasterCard
  In anticipation of her upcoming Predictive Analytics World for...
Mid-Life Journey to Data Science
  Data Science has been hailed as the sexiest...
Wise Practitioner – Predictive Analytics Interview Series: Dr. Patrick Surry of Hopper
  In anticipation of his upcoming keynote conference presentation,...
What are you Predicting in Customer Retention?
  Customer Retention models are arguably the most valuable...
Wise Practitioner – Predictive Analytics Interview Series: Ken Elliott at Hewlett Packard Enterprise
  In anticipation of his upcoming conference presentation, Operationalizing...
Wise Practitioner – Workforce Predictive Analytics Interview Series: Holger Mueller at Constellation Research
  In anticipation of his upcoming Predictive Analytics World for...
Wise Practitioner – Predictive Analytics Interview Series: Lawrence Cowan at Cicero Group
  In anticipation of his upcoming conference presentation, Predicting...
Hey FinTech, What’s Your Strategy for Leveraging Unstructured Data?
  Financial technology has sparked a global wave of...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Raffael Devigus at F. Hoffmann-La Roche AG
  In anticipation of his upcoming Predictive Analytics World for...
Wise Practitioner – Predictive Analytics Interview Series: Rebecca Pang at CIBC
  In anticipation of her upcoming conference presentation, Driving...
Employee Engagement – a Tricky Metric for Predictive Analytics
 Our work focuses on using predictive analytics to decrease...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Daniil Shash at Eleks
  In anticipation of his upcoming Predictive Analytics World...
The Information Age’s Latest Move: Four Predictive Analytics Developments for 2016
  Originally published in Big Think Prediction is in...
Why Do We Stop Asking Why?
 I’ve lived through this phenomenon first hand. The environment...
Predictive Analytics and the Internet of Things
 As technology continues to empower our ability to conduct...
Wise Practitioner – Predictive Analytics Interview Series: Mario Vinasco at Facebook
  In anticipation of his upcoming conference presentation, Advanced...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Vishwa Kolla at John Hancock Insurance
  In anticipation of his upcoming Predictive Analytics World for...
In Predictive Analytics, Coefficients are Not the Same as Variable Influence, Part II
 In my last post, “Coefficients are not the same...
Wise Practitioner – Predictive Workforce Analytics Interview Series: John Lee at Equifax Workforce Solutions
  In anticipation of his upcoming Predictive Analytics World for...
Wise Practitioner – Predictive Analytics Interview Series: Peter Bull at DrivenData
  In anticipation of his upcoming conference presentation, Predicting...
The “Predictive Analytics” FAQ — What’s New in the Updated Edition and Who’s The Book for?
  This is the preface to Eric Siegel’s newly-released...
Wise Practitioner – Predictive Analytics Interview Series: Matt Bentley at CanIRank.com
  In anticipation of his upcoming conference presentation, Predicting...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Lisa Disselkamp and Tristan Aubert at Deloitte
  In anticipation of their upcoming Predictive Analytics World for...
The Data Scientist’s Dilemma: Does Skipping Breakfast Kill You?
  Would skipping breakfast kill you? Not necessarily—but confusing correlation and...
Predictive Analytics Can Help with the Challenges Facing Manufacturing in the 21st Century
  Historically, data and analytics have been key to...
Wise Practitioner – Predictive Analytics Interview Series: Nate Watson at Contemporary Analysis
  In anticipation of his upcoming conference presentation, Predictive...
Customer Experience Predictions for 2016
 As we look ahead and see 2016 unfurling in...
Predictive Analytics Book Excerpt: Hands-On Guide—Resources for Further Learning
 Here is the Hands-On Guide that appears at the...
Wise Practitioner – Predictive Analytics Interview Series: Hans Wolters at Microsoft
  In anticipation of his upcoming conference presentation, Predicting...
Machine Learning: Not Necessarily a New Phenomenon in Predictive Analytics
  One of the more recent topics gaining traction...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Frank Fiorille at Paychex, Inc.
  In anticipation of his upcoming Predictive Analytics World for...
Netflix, Dark Knowledge, and Why Simpler Can Be Better
 Weary from an all-night coding effort, and rushed by...
The Case Against Quick Wins in Predictive Analytics Projects
 When beginning a new predictive analytics project, the client...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Jason Noriega at Chevron
 In anticipation of his upcoming Predictive Analytics World for Workforce conference...
Wise Practitioner – Predictive Analytics Interview Series: Matthew Pietrzykowski at General Electric
  In anticipation of his upcoming conference co- presentation, Advanced...
B2B Predictive Analytics: An Untapped Sector
 Much work in predictive analytics and data science has...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Greg Tanaka at Percolata
 In anticipation of his upcoming Predictive Analytics World for Workforce conference...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Michael Li at The Data Incubator
  In anticipation of his upcoming Predictive Analytics World for...
Four Ways Data Science Goes Wrong and How Test-Driven Data Analysis Can Help
  If, as Niels Bohr maintained, an expert is...
In Predictive Analytics, Coefficients are Not the Same as Variable Influence
 When we build predictive models, we often want to...
Oracle’s Ten Enterprise Big Data Predictions for 2016
 Companies big and small are finding new ways to...
Personalities That Are Barriers to Model Deployment (And How to Partner With Them) Part III: The Expert
 So you have gathered your data and completed your...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Kathy Doan at Wells Fargo Bank
 In anticipation of her upcoming Predictive Analytics World for Workforce conference...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Jonathon Frampton at Baylor Scott & White Health
 In anticipation of his upcoming Predictive Analytics World for Workforce conference...
Mobile Analytics-Mining the Visit Experience of the Customer
 Mobile technology as part of the Big Data discussion...
The Devil’s Data Dictionary – Making Fun of Big Data
  Buy it on Amazon When Stéphane Hamel coined...
Wise Practitioner – Predictive Workforce Analytics Interview Series: Ben Waber of Humanyze
 In anticipation of his upcoming Predictive Analytics World for Workforce conference...
The Quest for Unicorns
 Will there be enough data scientists in the future?...
Most Swans are White: Living in a Predictive Society
 In anticipation of the forthcoming Revised and Updated, paperback...
Hiring? Approving Mortgages? It’s the Same Thing
  Imagine that Chris wants to buy a house...
Personalities That Are Barriers to Model Deployment (And How to Partner With Them) Part II: The Skeptic
 So you have gathered your data and completed your...
5 Types of Analytics in Business: One to Go After and One to Avoid
 I have been lucky enough to work in some...
The Beginner’s Guide to Predictive Workforce Analytics
 Human Resources Feels Pressure to Begin Using Predictive Analytics...
Predictive Modeling Forensics: Identifying Data Problems
 Excerpted and modified from Chapters 3 and 4 of...
Five Wins for Retail with Predictive Analytics
 We’ve heard a lot about how big data is...
Faster Credit Scoring Dev With Specialized Binning Code – R Package
 Introduction One of the main concerns in a credit...
Good Predictions != Good Decisions
 A Fateful Tale Ted is having a rough week...
Using Predictive Analytics to Bring Retailers Closer to Their Customers
 Based on the amount of retailers that have been...
Visualization: Panacea for Building Analytics Solutions?
  Data,data,data everywhere and what do I do with...
Five Challenges in Using Predictive Analytics to Improve Patient Outcomes
 In the increasingly patient-centric world of healthcare, predictive analytics...
Personalities That Are Barriers to Model Deployment (And How to Partner With Them) Part I: The Early Adopter
 So you have gathered your data and completed your...
Five Ways Predictive Analytics Will Shape the Future of Advertising
 Predictive analytics sounds almost mystical, and in a way,...
Five Ways Predictive Analytics Can Improve Patient Outcomes
 The use of analytics in healthcare is gaining momentum...
Wise Practitioner – Predictive Analytics Interview Series: Scott Lancaster at State Street Corp.
  In anticipation of his upcoming conference presentation, Predictive...
Can Employee Development Lead to Business Mediocrity?
 Our predictive workforce assignments yield staggering results; saving /...
Empathy and Data Science: A Fable of Near-Success
 Editor’s Note: While the story is fiction, the events...
Wise Practitioner – Predictive Analytics Interview Series: Jeff Butler at IRS Research, Analysis, and Statistics organization
  In anticipation of his upcoming conference presentation, The...
A Look at How Big Data is Changing Sports on the Field and in the Press Box
 While major rules rarely change, everything else about professional...
Wise Practitioner – Predictive Analytics Interview Series: Dr. Satyam Priyadarshy at Halliburton
  In anticipation of his upcoming conference presentation, Challenges...
Automation: Friend or Foe to the Predictive Analytics Practitioner
  Technologies and Big Data continue to bombard our...
Winning Roles: Moneyball 2.0, for your Hiring and Succession Planning Processes
 Business can learn a lot from sports in terms...
Wise Practitioner – Predictive Analytics Interview Series: Werner Britz at RCS Group
 In anticipation of his upcoming conference presentation, Recoveries: External...
Wise Practitioner – Predictive Analytics Interview Series: Dr. Michael Dulin, Carolinas Healthcare System
  In anticipation of his upcoming keynote conference presentation...
Wise Practitioner – Predictive Analytics Interview Series: Benjamin Uminsky, Los Angeles County
  In anticipation of his upcoming conference presentation, Mining...
Wise Practitioner – Predictive Analytics Interview Series: Jessica Taylor of St. Joseph Healthcare
 In anticipation of her upcoming conference co-presentation at Predictive...
Wise Practitioner – Predictive Analytics Interview Series: COL William Saxon, Department of the Army
 In anticipation of his upcoming conference presentation, From Wisdom...
Defensive Data Science: What we can Learn from Software Engineers
  To view this content OR subscribe for free...
Wise Practitioner – Predictive Analytics Interview Series: Patty Larsen, Co-Director, National Insider Threat Task Force
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Wise Practitioner – Predictive Analytics Interview Series: Bin Mu at MetLife
  In anticipation of his upcoming conference presentation, Establishing...
Wise Practitioner – Predictive Analytics Interview Series: Michael Berry of TripAdvisor
  In anticipation of his upcoming conference presentation, Picking...
Wise Practitioner – Predictive Analytics Interview Series: Catherine Templeton, PAWGOV Keynote Speaker
 In anticipation of her upcoming keynote conference presentation, Reforming...
Wise Practitioner – Predictive Analytics Interview Series: William Wood of St. Joseph Healthcare
  In anticipation of his upcoming conference co-presentation at...
The Key to Modelling Success-The Variable Selection Process (Part 2)
 Last month, I discussed the importance of variable selection...
Wise Practitioner – Predictive Analytics Interview Series: Madhusudan Raman at Verizon
  In anticipation of his upcoming conference presentation, Predicting...
Wise Practitioner – Predictive Analytics Interview Series: Scott Jelinsky of Pfizer, Inc.
  In anticipation of his upcoming conference presentation at...
Wise Practitioner – Predictive Analytics Interview Series: Chris Franciskovich at OSF Healthcare System
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Wise Practitioner – Predictive Analytics Interview Series: Philip O’Brien at Paychex
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Wise Practitioner – Predictive Analytics for Healthcare Interview Series: Daniel Chertok at NorthShore University HealthSystem
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Wise Practitioner – Predictive Analytics Interview Series: Herman Jopia of American Savings Bank
  In anticipation of his upcoming conference presentation, Driving...
Stop Hiring Data Scientists Until You’re Ready for Data Science
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How to manage projects in Predictive Analytics
  In the previous five years, the analytical scene...
Wise Practitioner – Predictive Analytics Interview Series: Lawrence Cowan of Cicero Group
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Defining Measures of Success for Cluster Models
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Good luck placing Analytics in an org chart
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Retail Predictive Analytics Solves the Missing Link in Cross Selling, Up Selling, and Suggestive Selling
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Sameer Chopra’s Hotlist of Training Resources for Predictive Analytics
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Wise Practitioner – Predictive Analytics Interview Series: John Smits of EMC
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Be a Data Detective
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Predicting Employee Flight Risk: My Take
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The Key to Modelling Success -The Variable Selection Process (Part 1)
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Predictive Analytics World in Color [Infographic]
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Space Alien Eager to Convey Thoughts on Data Science
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Defining Measures of Success for Predictive Models
  Excerpted from Chapters 2 and 9 of his...
Overstatement of Results in Predictive Analytics
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The Biggest Lever to Success in Predictive Analytics
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Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Field Cady at Think Big Analytics
  In anticipation of his upcoming Predictive Analytics World for...
Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Jeffrey Thompson of Robert Bosch, LLC
 In anticipation of his upcoming Predictive Analytics World for Manufacturing conference...
Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Kumar Satyam of PricewaterhouseCoopers, LLP
 In anticipation of his upcoming Predictive Analytics World for Manufacturing conference...
White Paper – Immediate Access
Thank you for your interest in the white paper,...
Predicting Rare Events In Insurance
  As we all know, predictive analytics is a...
Python, Predictive Analytics & Big Data oh my!
 Python has seen significant growth in utilization in the...
Wise Practitioner – Predictive Analytics Interview Series: Thomas Schleicher of National Consumer Panel
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Leveraging Open Data: Improve Customer Experience and Drive New Market Opportunities
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From Code to Reports with knitr & Markdown
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Predictive Analytics Optimizes Prices and Markdowns for Retail
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Wise Practitioner – Predictive Analytics Interview Series: Delena D. Spann of US Government
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Infographic – PAW SF
5-Minute Recap
  In San Francisco this past March and April,...
Wise Practitioner – Predictive Analytics Interview Series: Dr. Patrick Surry of Hopper
 In anticipation of his upcoming conference presentation, Buy or...
Wise Practitioner – Predictive Analytics Interview Series: Viswanath Srikanth of Cisco
 In anticipation of his upcoming conference co-presentation, Building a...
Wise Practitioner – Predictive Analytics Interview Series: Jack Levis of UPS
 In anticipation of his upcoming conference keynote presentation, UPS Analytics...
Trust in Analytics Work: Why it’s Needed and How to Build It
 Much has been written about data-driven decision making. Someone...
Guiding Principles to Build a Demand Forecast
 Demand forecasting is one of the most challenging fields...
Wise Practitioner – Predictive Analytics Interview Series: Arcangelo Di Balsamo of IBM
 In anticipation of his upcoming conference presentation, Applied Predictive...
Wise Practitioner – Predictive Analytics Interview Series: Dean Abbott of Smarter Remarketer
 In anticipation of his upcoming conference presentation, The Revolution...
Predictive Analytics in Sports
 The world of sports has seen exponential increases in...
5 Things I Learned at Predictive Analytics World for Workforce
  As a trained researcher, I’ve always been fascinated...
Predictive Analytics as a Strategic HR Solution
 This interview is the second in a series on...
Visualizations Get Some Snap from R Shiny
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1 year ago
Wise Practitioner – Predictive Workforce Analytics Interview Series: Lisa Disselkamp and Tristan Aubert at Deloitte

 

In anticipation of their upcoming Predictive Analytics World for Lisa Disslekamp imageWorkforce conference co-presentation, Predictive Analytics Unlocks Sustainable Cost Reduction In Hourly Workforce, we interviewed Lisa Disselkamp, Director at Deloitte, and Tristan Aubert, Senior Consultant – Advanced Analytics & Modeling at Deloitte. View the Q-and-A below to see how Lisa and Tristan have incorporated predictive analytics into the workforce of Deloitte. Also, glimpse what’s in store for Tristan Aubert imagethe new PAW Workforce conference.

Q: How is a specific line of business / business unit using your predictive decisions?  How is your product deployed into operations?

A: [Lisa Disselkamp] Our tool is being used to evaluate operational and financial impact of regulatory changes to exempt labor status by finance, HR and operations. (this is really for 2016)

Our tool is being used by finance and HR to evaluate compensation policy costs based on operational issues of unique units in their business. They are looking at the necessity of pay programs based on what drives labor demand and employee supply. Based on the analysis, even high cost pay programs may be acceptable based on operational requirements, and low cost programs may stop being overlooked because operationally they are unnecessary.

Decision makers are leveraging the tool to evaluate when and what to make changes to job assignments to reduce cost and maintain necessary front line activities at an acceptable level given the specific situation.

In 2016 our tools will be instrumental in responding to changes in the salary threshold for exempt employees resulting from proposed changes from the Department of Labor. Employers of all types will need to predict the potential cost of converting employees to hourly and the capacity to provide adequate labor hours under more constrained conditions to run their business.

A: [Tristan Aubert] The businesses would use the tool to identify units/teams with higher than expected overtime, understand the drivers of overtime, and make use of this data to inform the actions they would like to take to address this issue before it occurs.

The tool itself does not provide recommendations, rather it provides additional clarity into the causes of overtime and predicts – based on past history – which units are most likely to be prone to overtime and why. For this tool to be used most effectively it needs to be paired with strong domain knowledge into how to best mitigate the drivers that cause the issue and with the business knowledge to determine what areas are in need of attention. Some units may naturally be more prone to overtime, though this does not necessarily mean the functioning should be changed.

Q: If HR were 100% ready and the data were available, what would your boldest data science creations do?

A: [Lisa Disselkamp] HR would be able to forecast how pay policies and schedules are driving labor cost, productivity and revenue. People drive the business and the bottom line and having a more clear picture of how compensation motivates workers and how schedules drive attendance, recruitment and retention would enable them to position workers based on schedule fit, worker skills and cost. They would also help managers influence the daily situations where pay policy and work opportunity converge and potentially inflate labor spending or upset employees.

A: [Tristan Aubert] The right data would mean finding the best approach to manage a person based on their skillset and place in their career to match them with the best opportunities within a firm. I think it’s fairly safe to say that if people enjoy what they do, they will be more productive, motivated and generate better long-term results for their employers. The right data would help define what employees do enjoy about their work situation – how many hours they work, when they work, the predictability and stability of the hours they work, work that includes the activities they want to perform and skills they want to build, all go into job satisfaction. So a comprehensive approach to aligning people to what they most enjoy and are suited for would be the boldest data-science creation.

Q: When do you think businesses will be ready for “black box” workforce predictive methods, such as Random Forests or Neural Networks?

A: [Tristan Aubert] When businesses have understood the implications of using black-box models and determine where it is appropriate to use and where it is not. There are no major technical hurdles to creating black-box models however, human resource challenges are not easily ‘optimized’ in the manner that engineering challenges are. Furthermore, it must be appreciated by end users that models are not infallible or necessarily fair –they tend to reflect pre-existing biases – and there is risk involved in this, doubly-so with black-box models where the mechanics are not well understood.

A: [Lisa Disselkamp] It’s going to take time and practice. Organizations are going to have to lay out a plan that includes incrementally changing the way organizations operate. It could take many rounds of change to build up to these methods. Readiness will come when they have developed the confidence and ability to incorporate predictive analytics into their decision making, not use it to replace human decision making. They also need to be skilled in modeling and testing to validate these intelligent systems are leading them to the proper conclusions. Readiness is not just about conversion but about using tools such as these to strengthen business processes and decision making. The decision making processes and the data must be sound before these tools are deployed. Readiness may involve developing or hiring for the right skill sets which include knowing how the business will be impacted by these predictive tools and managing the transformation to a data driven model.  

Q: Do you have suggestions for data scientists trying to explain the complexity of their work, to those solving workforce challenges?

A: [Lisa Disselkamp] Take the time to show them how using the wrong data or not asking the right questions can give a false answer; map out how visualizations are produced so that they are not fooled by charts and graphs and understand what must go on behind the scenes with the mathematical modeling.

A: [Tristan Aubert] If you can’t explain it simply, you don’t understand it well enough – Einstein’s maxim is extremely applicable in this case. A good starting point is to always try and establish a clear link between what you are doing as and the problem at hand. Usually, it is advisable not to dive into the technicalities of the work you are doing but rather to explain – in jargon-free terms – why a particular activity is necessary to arrive to the solution.

Q:  What is one specific way in which predictive analytics actively is driving decisions?

A: [Lisa Disselkamp] Making decisions based on data isn’t new. What is new is that predictive analytics gives leaders more confidence to make not only bold moves, but measured moves that are based on solid data and give leaders greater confidence in sustainability once a decision is made. Making a change to an outdated pay policy is easy, getting the outcome you desire and having that “stick” are where predictive analytics can refine and bolster decision making.

A: [Tristan Aubert] Workforce retention models are actively used by analytics-savvy firms to improve on their ability to retain their at-risk talent. As a result of being able identify which segments of the workforce are most at risk of departing, they are able to make informed decisions on how to pursue those individuals deemed critical to the workforce.

Q: How does business culture, including HR, need to evolve to accept the full promise of predictive workforce?

A: [Tristan Aubert] A few things need to happen. First, data generating systems need to be designed with analytics in mind – without good data no insights can be uncovered. Second, business culture needs to understand how to make use of the insights driven by analytics – this means both determining where analytics fits in their day-to-day decision process as well as understanding the nuances and limitations of analytics. Finally, businesses need to develop an imagination of the types of questions that can be addressed by analytics – this will mean going beyond known problems and starting to try to uncover unknown-unknowns.

A: [Lisa Disselkamp] To do that, HR leadership needs to be willing to go beyond superficial changes and have the courage to fundamentally change how their organization operates. Systems, processes and policies may need to be completely abandoned in the new world of work. HR needs to accept that behavior will be changed most effectively when predictive analytics are used to their full potential. Resist the temptation to do what you know, embrace disruption and recognize where you do not have sufficient skills.

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Don’t miss Lisa and Tristan’s conference co-presentation, Predictive Analytics Unlocks Sustainable Cost Reduction In Hourly Workforce, at PAW Workforce, on Tuesday, April 5, 2016 from 3:30 to 4:15 pm. Click here to register for attendance. USE CODE PATIMES16 for 15% off current prices (excludes workshops).

By: Greta Roberts, CEO, Talent Analytics, Corp. @gretaroberts and Conference Chair of Predictive Analytics World for Workforce.

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