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The traditional approach to the interpretation of employee survey results is based on means. In its simplest expression, the traditional approach goes as follows: 'your lowest scores represent your biggest issues, and these issues are what you should focus on.' More recently, approaches based on correlations have become popular. These approaches look at results differently; more like: 'you should focus your efforts on those issues that have the most impact on the outcomes you are interested in having an impact on.' Importantly, the means-based and the correlation-based approaches will usually lead to different interpretations of the same data.
This paper will start by taking a closer look at key driver analysis for a couple of reasons. For one, key driver analysis represents an attempt to integrate both mean-based and correlation-based approaches to the interpretation of employee survey results. As well, the points made using key driver analysis to other correlation-based techniques, such as causal modeling or path analysis.
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