Run Charts and Statistical Process Control in Human Resources workforce analytics

1. Really Cool Analytical Tools Mike Harmer & Shelley Browning

2. Agenda Introduction: SPC & CQI Run Charts Case Study: Training Outcomes Case Study: Time To Fill v1.0 Control Charts Case Study: Time To Fill v2.0 Operational Example Case Study: Internal Benchmarking of Apples & Oranges Advanced SPC Theory Case Study: Analyzing HR Excellence

4. Real world vs. Lab world

7. Not “good” or “bad”Variation type determines management strategy

8. Case Study: Training Outcomes Run Chart Steps… Draw the median Test the variation Special Cause Tests Too much or too little variability? Shift in the Process? Trends in the Process?

9. Run Chart Probability Table

10. Case Study: Time To Fill v1.0 40. Wow. That looks high… Increasing for the last 6 weeks… What’s going on? Steps… Draw the median Test the variation Special Cause Tests Too much or too little variability? Shift in the Process? Trends in the Process?

11. Case Study: Time To Fill v2.0 Control Chart Steps: Calculate the mean Add Control Limits Test the variation Special Cause Tests Exceed Control Limits? 2 of 3 in Zone C? Shift in the Process? Trends in the Process?

15. Questions / Discussion Questions? Contact Information Mike Harmer: mike.harmer @ ThinkTroop.com Shelley Browning: shelleybrowning@ comcast.net

16. SPC: Analyzing HR Excellence Scenario 4 Regions: North, South, East, West Weekly HR Excellence Customer Survey 60 Respondents 30 Employees 20 Managers 10 Leaders 9 Questions Excellent, Very Good, Good, Fair, Poor Unfavorable Responses: all but ‘Excellent’ Table of Results

17. SPC: Questions Questions Is North above or below average? Is North experiencing special cause variation? Has satisfaction improved over the 20 weeks? What next? Table 1

18. SPC: First Look Chart 1: All Customers with 1 or more unfavorable responses Findings North is above the average (bad) No special cause variation – no expected change North is a special cause compared to other regions What next? Disaggregate data by customer groups – is the problem in one of the groups?

19. SPC: Second Look Chart 2: Graph by respondent group (Employee, Manager, Leader) with 1 or more unfavorable responses Findings Employees and Leaders are positive special cause Managers are negative special cause What next? Calculate control limits separately for each group to determine if each group is stable and to provide a baseline for comparison

20. SPC: Third Look Chart 3: Graph by respondent group with own control limits Findings Each group is stable within its own control limits Continue to monitor employee and leader groups Manager group needs an improvement plan What next? Assess results from managers – where are the problems? Develop intervention and monitor process.

21. SPC: Improvement Plan Chart 4: Graph Manager responses with separate control limits before and after intervention. Graph Region pre- and post- improvement Findings Improvement Plan worked, Region now meeting goals. Manager group can still improve What Next? Best Practice suggestions to other regions