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Key Practices for Measuring Pay Data in Employee Reward Systems

This document explores essential practices for measuring pay data in employee reward systems. It highlights the importance of understanding pay data distributions, detailing the characteristics of normal and non-normal distributions typically observed in pay surveys. The measures of central tendency, such as median and mean, are explained alongside their applications. Additionally, it covers measures of variation, including range, quartiles, and standard deviation. The document emphasizes the relevance of current pay data, consistent statistical measures, and effective monitoring to ensure competitive market positions in employee compensation.

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Key Practices for Measuring Pay Data in Employee Reward Systems

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  1. Pay Survey Practices - Part II Measuring Pay Data • Distributions: • Normal - Bell shaped curve - rarely appropriate • Non-Normal - pay data is unevenly distributed; more typical of pay data collected from surveys • Measures of Central Tendency used to report Pay • Median - the middle value of an ordered sequence of data • Mean - sum of data divided by numberof observations • Unweighted - each company is an observation • Weighted - each employee is an observation MGMT 4030 - Managing Employee Reward Systems

  2. Pay Survey Practices - Part II • Measures of Variation used to Report Pay • Range of Pay Data • Minumum, Maximum, Midpoint • Quartertile - 1st , 2nd (above midpoint); 3rd, 4th (below ) • Standard Deviation - distance of data from mean in a normal distribution. • Typical Market positions • Lead the market • Lag the Market • Match the Market MGMT 4030 - Managing Employee Reward Systems

  3. Pay Practices - Part II(Gomez-Mejia & Balkin, 1992) Recommended Pay Survey Practices • Relevance • Match on Job Descriptions (not Titles) • Consistent Use of Same Statistical Measures • Keep Pay Data Current • Monitor Effectiveness Using HR Benchmarks MGMT 4030 - Managing Employee Reward Systems

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