Improving Measures to Improve Performance

A post from the zapaterismo blog is addressed to the need for trust and the need for change to improve talent management, however the focus on this post ends up to be centered on measurement. “Zap” says:

The sad reality in most organizations is:

1. Performance management processes don’t produce highly reliable data. They simply aren’t often helpful in reliably and objectively differentiating employee performance. The process that was once an “ass-covering exercise” has not been sufficiently adapted to the reality that most organizations (and the technology they leverage) are now relying heavily on performance data for making important talent decisions.

2. Other talent measures/processes, such as employee “potential” and promotion “readiness” ranking are most often based on gut, at best, and politics, at worst.

Any measure implies a theoretical rationale that links performance and measures and it can be tested validated and improved over time.  What “Zap” is having problems with are likely measures that come from common sense and maybe something that only made real sense a long time ago.  Now common sense is not a bad place to start from, but it can be followed up by research and thought to build a theoretical structure to turn common sense into theoretical understanding, which in turn facilitates the ability to validate your measures and to build in improvements over time.

Now, you might say; “hold on there” we business people, we can’t be blooming scientists too!  Yes I believe you can.  Science, validity, measurement and similar concepts can become very complex in many circumstances, but at heart, science is a simple concept and can be applied in many ways that are not always of the same complexity.  People who say otherwise are usually looking to specific complex examples and expect everything has to be like the example.  Instead, look at the core concept and what it suggests.  Some perfromance improvement may need new as-of-yet un-thought-of tools, but I believe that much can be accomplished by looking for tools just laying around un-used at present.

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  1. Pingback: Why Interpretation is the Cornerstone of Evidence-based Data Driven Practice | A Chronicle of a Learning Journey

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