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1 Integrating Research to Create Retention Intelligence at Microsoft Presented by L. Allen Slade, Lisa Sandora, Laura Hamill, and Kate Suckow Microsoft.

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Presentation on theme: "1 Integrating Research to Create Retention Intelligence at Microsoft Presented by L. Allen Slade, Lisa Sandora, Laura Hamill, and Kate Suckow Microsoft."— Presentation transcript:

1 1 Integrating Research to Create Retention Intelligence at Microsoft Presented by L. Allen Slade, Lisa Sandora, Laura Hamill, and Kate Suckow Microsoft People Research at the 17 th Annual Conference of the Society for Industrial and Organizational Psychology Contact: L. Allen Slade One Microsoft Way Redmond WA,

2 2 Initial Attrition Research: A Flurry of Activity The Context Activity The Deal Research Terminator Study Exit Research Monthly Attrition Report Retention Initiative Team

3 3 The Need for Retention Intelligence Lack of Integration in Research Maturation of Internal Consumers Change in Labor Market

4 4 Retention Intelligence: The Quarterly Pulse Report The Quarterly Pulse Report Employee opinion survey Internal and external attrition data Exit survey data Special studies Impact: Mixed HR found it very useful. Trouble getting in front of senior leadership. Lessons Timing is everything. Push vs. pull marketing for different audiences. Pulling the plug

5 5 Retention Intelligence: Reconciling Attrition Data The problem of reconciliation Extending the monthly report Revising the one size fits all summary report Adding a drill down report Marketing strategy Push summary report with explanatory note Encourage users to pull detailed report Refine distribution list Single source for attrition data, Impact Well received Seems to have solved the reconciliation problem.

6 6 Retention Intelligence: Total Rewards Optimization Research Forced trade-offs among traditional and non-traditional rewards Criterion: intention to remain at Microsoft for 4 or more years

7 7 Retention Intelligence: Total Rewards Optimization Research Retention as an outcome to drive compensation strategy. Merging costs and employee preferences through portfolio optimization Collected costs, created set of assumptions for 12 conjoint reward elements, and 20 pick list items Evaluated programs on basis of incremental cost vs. projected savings from increased retention Real time modeling of different programs Impact Drove changes in employee stock purchase plan Validated planned changes in internal staffing and management training

8 8 Retention Intelligence: Refining Our Metrics Exit Survey Simplification Addition of global terminations Searching for the Good Quit From Minimize Attrition to Manage Retention Lifetime average performance review scores Stock class rating (potential) Non-regretted attrition (the good quit) Differentiation between employees: Review, potential, time in level Termination for cause Management Accountability–Move em up or move em out


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