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835 keynote groberts

  1. 1. Making Predictive Analytics Work in Your Enterprise Greta Roberts, CEO Talent Analytics, Corp. PAW Workforce May 16th, 2017
  2. 2. ¡ Share some of our predictive experiences ¡ Both approaches that have worked --- and some that haven’t ¡ Help make predictive analytics work in your enterprise ©2017 Talent Analytics, Corp. www.talentanalytics.com 2 Goal with Presentation 15 May 2017
  3. 3. ¡  Predictive Workforce Platform – Advisor™ ¡  Predict probability of lasting in a role or performing in a role – pre-hire ¡  Advisor™ deploys predictions into talent acquisition process in minutes ¡  Turnover goes down ¡  Performance goes up ©2017 Talent Analytics, Corp. www.talentanalytics.com 3 Talent Analytics, Corp. 15 May 2017
  4. 4. 4©2017 Talent Analytics, Corp. www.talentanalytics.com “Do Something Predictive” 15 May 2017
  5. 5. ©2017 Talent Analytics, Corp. www.talentanalytics.com 5 Should Data Scientist Find the Predictive Project? HR Data Scientist Programmer Business Owner Data Owners Naysayers Implementers Implementers 15 May 2017
  6. 6. ©2017 Talent Analytics, Corp. www.talentanalytics.com 6 CRISP-DM Methodology “Start with a Specific Business Problem” 15 May 2017
  7. 7. ©2017 Talent Analytics, Corp. www.talentanalytics.com 7 Potential Extended Predictive Team HR Data Scientist Programmer Business Owner Data Owners Naysayers Visualizations Implementers IO Psychologist Project Manager 15 May 2017
  8. 8. ©2017 Talent Analytics, Corp. www.talentanalytics.com 8 Why Does Extended Team Matter? 15 May 2017
  9. 9. 9©2017 Talent Analytics, Corp. www.talentanalytics.com Identifying a Predictive Project 15 May 2017
  10. 10. ©2017 Talent Analytics, Corp. www.talentanalytics.com 10 2 Approaches to Predictive Projects Crunch all the data you have looking for insight ID a Business Problem to Solve 15 May 2017
  11. 11. ¡ 1st, pick projects with high probability of success, in easier and non-confrontational areas § Hiring and promotion vs. § Diversity, firing, or downsizing ¡ Then proceed to more delicate areas ©2017 Talent Analytics, Corp. www.talentanalytics.com 11 1st Projects? Force for Good 15 May 2017
  12. 12. HR Project Data from HR Solve HR Problem Line of Business Project Data from Line of Business + HR Solve Business Problem Predicting Trends Individual Prediction Types of Predictive Projects ©2017 Talent Analytics, Corp. www.talentanalytics.com 1215 May 2017
  13. 13. HR Project Data from HR Solve HR Problem Line of Business Project Data from Line of Business + HR Solve Business Problem Predicting Trends •  Staffing levels / WF Planning •  Best time to contact candidates, for hiring or for reviews •  Predict training attendance •  Predict when they will retire •  Which training delivers best business results Individual Prediction Types of Predictive Projects ©2017 Talent Analytics, Corp. www.talentanalytics.com 1315 May 2017
  14. 14. HR Project Data from HR Solve HR Problem Line of Business Project Data from Line of Business + HR Solve Business Problem Predicting Trends •  Staffing levels / WF Planning •  Best time to contact candidates, for hiring or for reviews •  Predict training attendance •  Predict when they will retire •  Which training delivers best business results Individual Prediction •  Flight risk of current employees •  Which candidate to hire •  Which employee to promote •  Best career path for a specific employee •  What and whom to invest in Types of Predictive Projects ©2017 Talent Analytics, Corp. www.talentanalytics.com 1415 May 2017
  15. 15. “Predictive Models – A mechanism that predicts the behavior of an individual, such as click, buy, lie, or die .… “ (or perform, or turnover) “The higher the score, the more likely it is the individual will exhibit the predicted behavior.” Dr. Eric Siegel, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, Die ©2017 Talent Analytics, Corp. www.talentanalytics.com 15 Individual Predictions Deliver Highest ROI 15 May 2017
  16. 16. 16©2017 Talent Analytics, Corp. www.talentanalytics.com Analytics Maturity, Spreadsheets, and Missing Data 15 May 2017
  17. 17. ¡ Shows different analytics approaches ¡ Not steps in a linear path ¡ No need to take Step 1 before Step 2 etc. ©2017 Talent Analytics, Corp. www.talentanalytics.com 17 Evangelize “Analytics Approach” not “Steps” The Bersin by Deloitte Talent Analytics Framework describes all of the elements of talent analytics 15 May 2017
  18. 18. Everybody Has Spreadsheets and Old Systems ©2017 Talent Analytics, Corp. www.talentanalytics.com 1815 May 2017
  19. 19. ©2017 Talent Analytics, Corp. www.talentanalytics.com 19 Expand Your Vision to Solve Workforce Issues in the Line of Business Dependent Variable Independent Variable Predictive Model Sales Quota Inputs Outputs Assessment Scores 16 May 2017
  20. 20. 20©2017 Talent Analytics, Corp. www.talentanalytics.com “Selling” Your Project Internally 15 May 2017
  21. 21. HR Project Impact Process or Program ¡  Modify staffing process ¡  Modify retention process ¡  Modify retirement options ¡  Reduce time to hire Business Project Impact Business Results ¡  Increase sales ¡  Decrease returns or errors ¡  Decrease employee costs ¡  Increase “Employee Lifetime Value” ¡  Increase customer sat. ©2017 Talent Analytics, Corp. www.talentanalytics.com 21 Selling Your Proposition “So What” 15 May 2017
  22. 22. 15 May 2017 ©2017 Talent Analytics, Corp. www.talentanalytics.com 22 Insurance Sales Start High, Stay High / Start Low, Stay Low Training Helped Top, not Bottom, Performers Training Helps Top not Bottom Performers
  23. 23. Ex: Predictive Model Impact Higher Store KPIs ¡ Current Top 10% AGMs: §  Increased Customers/Week §  Increased Merch Sales/Week §  Increased Merch Net/Week §  Increased FSSA Score §  Decreased Terms/Month §  Increased Perf. Rating §  Decreased Overtime Hours/ Month ¡ Model can ID candidates likely to be orange ©2017 Talent Analytics, Corp. www.talentanalytics.com 23 12345 27649 27914 15 May 2017
  24. 24. 24©2017 Talent Analytics, Corp. www.talentanalytics.com Discussing Process and Results 15 May 2017
  25. 25. ¡  Give updates often – not only at the end of the project ¡  Complete Transparency § Even if you don’t like the results ©2017 Talent Analytics, Corp. www.talentanalytics.com 25 Discussing Process and Results 15 May 2017
  26. 26. 26©2017 Talent Analytics, Corp. www.talentanalytics.com When Senior Management Doesn’t “Get It” 15 May 2017
  27. 27. ¡  Model implemented to help reduce Bank Teller turnover. ¡  10 mos. later Teller turnover dropped from 84% to 64% ¡  Exec Concern – “I’m still having to train as many Tellers. What’s wrong??” ©2017 Talent Analytics, Corp. www.talentanalytics.com 27 The Beginning: Teller Turnover 15 May 2017
  28. 28. ¡ We solved Teller turnover ¡ Turnover went down – but hiring classes were still full ¡ More holistic problem than Teller Terminations only ¡ Many inputs into this challenge… ¡ Keep at it, put it into words they understand ©2017 Talent Analytics, Corp. www.talentanalytics.com 28 Their Problem Was Different Than What They Asked Us to Solve 15 May 2017
  29. 29. ¡ Goal: Fill to the line ¡ Problem: Water drains out at the same time ¡ Three things to watch: § The water level § Water flows In § Water flows out “Imagine a Tub…” Fill Tub Tub Draining Target Level ©2017 Talent Analytics, Corp. www.talentanalytics.com 2915 May 2017
  30. 30. ©2017 Talent Analytics, Corp. www.talentanalytics.com 30 Tub Multiple Fills - Hiring - Demotions - Rehires - Returned FMLA Multiple Drains - Termination - Promotions Start Headcount End Headcount 15 May 2017
  31. 31. Filling the Tub ¡  Hire & replace - cost to ramp someone up to role §  2016 Teller Replacement Cost $6,069 Draining the Tub Loss for Business ¡  Termination forces a hire ¡  FMLA - replacement cost Each Flow In and Out Has a Different Cost Benefit for Business ¡  Keeps employee value §  Promotion §  Lateral Transfer §  Location change ©2017 Talent Analytics, Corp. www.talentanalytics.com 3115 May 2017
  32. 32. ¡ Yes, you’re still hiring as many as you always hired ¡ But, employees are being recruited and promoted into new roles ¡ Which is good ¡ You need to remember the other drain – and it’s a good drain ©2017 Talent Analytics, Corp. www.talentanalytics.com 32 Why Am I Still Hiring the Same Number of Tellers? 15 May 2017
  33. 33. 33©2017 Talent Analytics, Corp. www.talentanalytics.com Legal Issues 15 May 2017
  34. 34. Concerns about Using Predictive Analytics ¡ People: Too unique to be Predicted? ¡ Machines making decisions ¡ Insufficient Sample ¡ Inputs too close to ethical boundaries ¡ Privacy: your company’s decision where you draw the line ¡ Management butterflies ©2017 Talent Analytics, Corp. www.talentanalytics.com 3415 May 2017
  35. 35. Concern about NOT Using Predictive Analytics ¡  Undocumented decisions ¡  Mystery factors ¡  Continuous and significant bias ¡  Lack of feedback loop about "what works” ¡  Inexperienced interviewers “How many jelly beans do you think are in this box" ¡  Continued favoritism moves company farther outside of compliance ¡  Less favorable business results – company falls behind their competitors ©2017 Talent Analytics, Corp. www.talentanalytics.com 3515 May 2017
  36. 36. ¡  Work with HR / corporate attorneys ¡  Help them understand predictive work and rigor associated with models ¡  Be responsible; Document your work ¡  Push back on baseless fears to help move forward ©2017 Talent Analytics, Corp. www.talentanalytics.com 36 Don’t Let Unfounded Legal Fears Stop Predictive Efforts 15 May 2017
  37. 37. Thanks for attending PAW Workforce 2017 Greta@TalentAnalytics.com ©2017 Talent Analytics, Corp. www.talentanalytics.com 37 Wrap Up 15 May 2017

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