1. Workforce Optimization and Planning
Dr. James Kelly & Dr. Marco Better
© 2014 OptTek Systems
December 10, 2014

2. OptTek’s Vision of Workforce Planning
 OptForce® is a proven data-centric
system that utilizes advanced
statistics, simulation, and optimization
to create actionable people
analytics that improve
organizational performance,
reduce talent risk, and enrich the
work experience.

3.  Actionable People Analytics
 Organizational Performance - Productivity
 Reducing Talent Risk to Prepare for the
Future
 Enriched Work Experience through Talent
Alignment and Proactive Program Planning
 Simulation / Statistics/ Optimization /
Machine Learning Technology

4. Descriptive, Predictive, Prescriptive
Descriptive
Analytics
Predictive
Analytics
Prescriptive
Analytics
More Valuable
MoreActionable
What
happened?
Why?
What will
happen?
What if…?
How do we
make the best
happen?
Adapted from Rose Business Technologies www.rosebt.com

5. Question?
 In the next year, my organization plans to utilize
predictive analysis to support workforce
planning.
a. Strongly Agree
b. Agree
c. Disagree
d. Strongly Disagree
e. Not Sure

6. Workforce as a living, growing, changing
organism

7. Workforce as a living, growing, changing
organism
Recruitment

8. Workforce as a living, growing, changing
organism
Recruitment
Voluntary Attrition

9. Workforce as a living, growing, changing
organism
Recruitment
Voluntary Attrition
Involuntary Attrition

10. Workforce as a living, growing, changing
organism
Recruitment
Voluntary Attrition
Involuntary Attrition
Retirement

11. Workforce as a living, growing, organism
Recruitment
Involuntary Attrition
Voluntary Attrition
Retirement

12. Workforce as a living, growing, changing
organism
The Future

13. Simulation and Predictive Statistics
 Predictive Statistics use past data to predict the future.
– Usually in the form of an equation yt = f(t,x)
– Best when applied at a relatively high level
– Excellent for stable trends and predictable cycles
– Not appropriate for a changing system
 Simulation uses past data and system structure to
predict the future.
– Model the actions of individual people as impacted by their
attributes and environment
– Can provide insight at the individual level and/or high level
– Excellent for stable trends and predictable cycles
– Excellent for investigating the impact of system changes

14. Year 1 Year 2 Year 3
Recruitment Pool
Executives
Middle
ManagementNon-managerial
Personnel Personnel PersonnelJobs Jobs Jobs
HRPrograms,PoliciesandInitiatives
U.S. Patent 8.386.300

15. WorkForce Demand – What You Will Need
MetricsHistory Operational
Demand
Machine
Learning
Statistical/Math
Model

16. WorkForce Demand – What You Will Need
MetricsHistory Operational
Demand
Predictions
at the role
levels
Machine
Learning
Statistical/Math
Model

17. WorkForce Demand – What You Will Need
MetricsHistory Operational
Demand
How have roles tracked with
products & services in the past?
Machine
Learning
Statistical/Math
Model

18. WorkForce Demand – What You Will Need
MetricsHistory Operational
Demand
Revenue, projects, orders, …
Machine
Learning
Statistical/Math
Model

19. WorkForce Demand – What You Will Need
MetricsHistory Operational
Demand
Bottom – up planning
Machine
Learning
Statistical/Math
Model

20. Too Few, Too Many, Just Right …
Gap (Supply-Demand) Analysis
0
50
100
150
200
250
300
350
0 4 8 12 16 20 24
FTE
Month
Demand
Supply
0
50
100
150
200
250
300
350
0 4 8 12 16 20 24
FTE
Month
Demand
Supply
0
50
100
150
200
250
300
350
0 4 8 12 16 20 24
FTE
Month
Demand
Supply

21. Major Components
 Data Preparation
 Demand Analyses
 Attrition Analyses
 Recruitment Modeling
 Talent Flow Modeling
 Program/Policy Modeling
 Risk Analyses
 Scenario Simulations
 Reporting

22. Question?
 If today you had a operational workforce
planning system, which of the following areas
would you address first?
(a) Demand Planning
(b) Recruiting
(c) Retention
(d) Talent Flow
(e) Other

23. Quality Assurance
Develop
Action Plans &
Deploy
Assess NeedsCollect Data
Simulate Scenarios
Assess
Needs
Collect Data
Validation
against
History
Build Models
Support
monthly cycle
Implementation
2 weeks to 3 months
OptForce Process Model

24. Use Cases and Web Application
Dr. Marco Better
Vice President of Analytics Services

25. Use Case 1
 Engineers in Plants 1 and 2
 Demand growing in Plant 1
 Demand decreasing in Plant 2
 Certain roles in Plant 1 require special Expert
Systems certification
 WHAT IF: we invested in training of Plant 2
engineers to be able to re-deploy them to Plant 1?

26. Use Case 2
 Recently hired employees exhibit higher
turnover than more seasoned personnel
 We invest in new recruits only to lose them to
competition
 Talent shortage in the market is creating a
growing demand gap
 WHAT IF: we could improve onboarding to
increase retention of new engineers?

27. Cost Comparison
Base (Do
Nothing)
Base +
Training
Cummulative Workforce Gap 463 152
Lost Revenue Cost 64,357$ 21,128$
Cost of Turnover 2,058$ 801$
Salaries 255,448$ 259,894$
Recruitment 28,687$ 19,601$
Training Program -$ 10,708$
Total Direct Costs 284,135$ 290,203$
Opportunity Costs 64,357$ 21,128$
TOTAL COST 348,492$ 311,331$
Net Savings 37,161$

28. Thank You!
OptTek Systems, Inc.
2241 17th Street
Boulder, CO 80302
www.OptTek.com
www.OptForce.com
U.S. Patent 8.386.300
Optimizing Your Workforce
Dr. Marco Better
better@opttek.com
303.447.3255 x 109
Dr. James Kelly
kelly@opttek.com
303.447.3255 x 101