USING DATA TO ENHANCE PAY FOR PERFORMANCE
As we head into the year-end, most organizations are putting the finishing touches on their plans for the upcoming performance and salary review cycle. A key step that many companies use to enhance the quality of their process is to build in time for a calibration of both ratings and pay recommendation before they finalize and start the communications with employees.
The actual process for calibration can take many forms, but usually there is a roll-up of the performance ratings and pay recommendations spanning across a large population. Individuals who conducted the initial evaluations and pay recommendations gather to hash out the assessments. There’s usually much discussion about performance outliers (high and low) to ensure as a group, the rating managers have applied performance standards consistently. There’s also validation of assessments across all other performance categories.
The Compensation team can also help to fine tune the calibration of ratings and awards by bringing data analytics to the discussion. Similar to the data results in our newest report product, Total Compensation by Demographics, the Compensation team can analyze proposed ratings and pay recommendations across multiple dimensions.
To illustrate how you can use data analytics to enhance your pay for performance objectives, here are three types of analyses we ran using the new Total Compensation by Demographics results.
Pay Variations by Tenure
We frequently need to assess pay across large segments of employees by looking at the pay of newly hired employees to others in the same job with more tenure. The traditional practice in compensation policies has been to hire closer to range minimums, but rarely hire new employees above the range midpoint so as not to disrupt internal equity by hiring in new employees above existing employees. While there still may be good value in adhering to those policies, when we compared the median base salary of new hires (i.e., defined as less than one year of service) to more tenured counterparts, the average difference in pay was only -1.2% lower. In fact, for 39% of the 446 benchmark jobs where we have both tenure groups, the new hires were actually paid higher.
Within your organization, you may find it helpful to look at more tenure groupings than just new hires compared to more than one year of service.
Pay Variations by Performance Rating
Even more powerful analysis comes into play when we start to analyze pay across the different performance rating categories. In the Total Compensation by Demographics report, we first had to normalize the different variations companies have to their rating scales, but then we are able to report pay data out based on a common framework. The assumption is that pay is going to be higher for the higher performance categories.
Based on our analysis, the majority of jobs (69%) do report higher median base salaries for the incumbents with the highest performance ratings compared to middle tier performance ratings. On average, the median base salary is 3.3% higher.
But there are so many other factors that go into determining base salary, such as sustained performance over long periods of time. Maybe we should be comparing total cash compensation (base salary plus short-term incentives) instead of just base salary. Surprisingly, when we use total cash compensation, we see a slight dip in those results.
Variable Pay Awards by Job Level and Performance
Drilling a little deeper on the correlation between performance and variable pay, we wanted to analyze if there is any difference in the performance ratings and incentive awards based on job levels. We’ve limited our analysis to just JobLink levels 4 – 8 to ensure adequate sample sizes across all performance rating categories.
With only one exception at Level 4, we do see a strong correlation between variable pay and the performance rating. On average incentive amount as a percent of target is 13.8% higher for those with the highest performance ratings compared to the middle ratings. For those incumbents in the lowest performance ratings, the average incentive award is just over 20% lower than counterparts who are rated in the middle category.
These three examples of the types of analysis you can do with the new Total Compensation by Demographics report are similar to the types of data anlytics you can bring to your organization's salary planning calibration process. By inserting compensation analytics into calibration, you can help sharpen your pay for performance goals. Contact us to learn more about how you can access the Total Compensation by Demographics data.