Why Should I Age Market Data?

Salaries in the market, as well as in your own organization, rapidly change due to merit and promotion increases, new hires and terminations.  However, the surveys you use may have been conducted at different times in the year, resulting in data that is current for different dates.

Time adjusting or aging is the process of taking different survey data, which can be accurate at different points in time, and adjusting the data to some common point in time.  To make your data sources consistent with one another, you need to “age” the data.

If you want to answer the question, “Where are we now, in terms of pay competitiveness?” you age the data from the surveys (using the effective dates of the data) to the current date and compare the results to your own current salaries.  If, on the other hand, you want to estimate competitive pay levels for next year in order to establish competitive new salary ranges for the coming year, you would age the data to the beginning, middle, or end of the coming year.

The actual date you choose to target will depend on whether you adopt a lead, lead-lag, or lag strategy for your salary structure.  If you age the data to the beginning of the year, your ranges will be competitive at that point, but will lag the market for the remainder of the year.  Aging the data to the end of the year will result in your leading the market all year.  As a compromise, most companies adopt a lead-lag strategy, aging the data to midyear–thereby leading the market for the first six months and lagging the market for the final six months.

Given that you know the effective dates of the surveys and have determined the point in time to which your data will be aged, you next need to determine the percentage to use in approximating competitive salary movement during that time. Numerous sources can be used to identify actual and projected salary movement. (Mercer’s annual CPS: Compensation Planning Survey, for example, shows past, present, and projected pay and structure increases by industry, employee group, and geographic region.)

Once you determine the annual salary movement percentage you want to use (e.g., 5%) Mercer WIN will calculate how to age the data. For example, to adjust the data by 9 months using an adjustment rate of 5%, the system will first divide the number of days remaining in the year by the total number of days in a year (275/365 = .7534). The system then multiplies this amount by the adjustment rate ((.7534 X .05) + 1 = 1.038) to determine the adjustment factor. The adjustment factor is then multiplied by the market rate (1.038 X 5220 = 5418) to obtain the aged data amount.

 


Example:

You want to age the 2011 Mercer Benchmark Database   (Effective Date - 1 Mar 2011) to June 1, 2012. Additionally, the Publication Year is to be aged by 4% and the Next Year(s) by 3%.

Enter the percentages in the appropriate text boxes and click . Mercer WIN uses the following method to compute the aging factor:

Click to have these percentages applied to the market data.

 

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