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Example: Talent management metrics
Metrics mean nothing
Numbers, by themselves, are meaningless. Advanced statistics are rarely needed to give them meaning. What is most often missing is a clear model of the data, an understanding of where the data comes from, and a documented connection to business results.
Typical issues
- Who are the top performers and what are their best practices?
- What is the value of top performers vs. average performers?
- What is the cost-effectiveness of alternative performance development strategies?
- What is the cost-benefit of retaining high potentials?
- What is the relative contribution of managers vs. subordinates to team success?
- What is cost of turnover?
- What is the real cost of a new hire?
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