2016 American Water Works Association AWWA ACE16 Conference Proceedings All Rights Reserved

Transcription

1 A Data-Driven Response to Turnover: Creating a Strategic Workforce Plan Based on the Kaplan-Meier Estimator Aaron Chan and Stanley Lam City of Houston Public Utilities Division

2 TURNOVER QUESTIONS We sought to understand: What are the patterns of turnover at our utility? Which employees should we pay particular attention to? What targeted steps can our utility take to reduce that turnover?

3 First Step: AWWA Benchmarking Organization Turnover Nationwide (Utilities) 9.0% AWWA South Region 8.0% Large Utility 6.5% Houston Public Utilities 9.07%

4 A New Way to Measure Turnover Kaplan-Meier KM Curve

5 A Simple Utilities Example Employee Hire Date Termination Greg 1/1/2008 1/1/2012 Christina 1/1/2007 1/1/2016 Eric 1/1/2012 1/1/2015 Don 1/1/2009 1/1/2010

6 A Simple Utilities Example Greg 4 years Christina Eric Don 9 years 3 years 1 year

7 A Simple Utilities Example Greg 4 years Christina Eric Don 9 years 3 years 1 year

8 A Simple Utilities Example Don Eric Greg Christina 1 year 3 years 4 years 9 years

9 A Simple Utilities Example Don Eric Greg Christina 1 year 3 years 4 years 9 years

10 A Simple Utilities Example Don Eric Greg Christina 1 year 3 years 4 years 9 years Years of Service

11 A Simple Utilities Example 100% Percent of Employees 0 Years of Service 9 years

12 KM Curve for Houston Public Utilities Percent of Employees Years of Service 2016 American Water Works Association AWWA ACE16 Conference Proceedings All Rights Reserved

13 KM Curve for Houston Public Utilities Percent of Employees Years of Service 2016 American Water Works Association AWWA ACE16 Conference Proceedings All Rights Reserved

14 KM Curve for Houston Public Utilities Percent of Employees Years of Service 2016 American Water Works Association AWWA ACE16 Conference Proceedings All Rights Reserved

15 Reducing Turnover Collaborate with human resources Retention strategy for Millennials Retention strategy for older/experienced employees

16 Age at Departure Over 65 8% Under 25 7% % % % % Under Over 65

17 Update Policies Flexible work schedules Expedite hiring processes Performance based reward system

18 Retention Strategy: Millennials Career mapping, leadership development Cross training Exit interviews

19 Retention Strategy: Older Employees Analyze retirement Training/education Mentorship

20 PUD by Age Group Comparison of PUD Ages in FY Age Group Age Group Other 50 or older Per or younger

21 Average Retirement Age Mean: 61 Std. Dev: 5.65 Frequency Age at Retirement 2016 American Water Works Association AWWA ACE16 Conference Proceedings All Rights Reserved

22 Retention Strategy: Older Employees Analyze retirement Training/education Mentorship

23 Lessons Learned & Our Recommended Best Practices Make sure data drives decision making Applying specific strategies based on your workforce Collaboration with HR and operations Big data doesn t have to be big budget today s numbers were run on free software

24 Questions?