Calculator: age your pay data


Many organisations like to "age" pay data, adjusting published salary survey figures to take account of general movements in the economy since the date it was collected.

In times when the economy is growing in a controlled way and pay is rising rapidly, this can help reward professionals make informed decisions. There are, however, numerous caveats when making this kind of calculation, and XpertHR recommends that you read the notes below.

To use the calculator, input the salary as it was at the start of the "ageing" period (for example, the "as at" date in a salary survey). Choose the annual percentage increase that you wish to apply. Select your start and end dates (providing both a month and year in the format indicated), and press calculate.

The results will give you an "aged" salary as at your end date, and the total percentage increase (or factor) applied over the period. Note: do not use £ or % symbols or commas (30000, not £30,000).




Be cautious when ageing pay data

Although many employers do age pay data, it is important to be aware of a number of issues that are raised by the process and which can make the end results unreliable if not clearly understood.

There are two scenarios in which employers may wish to artificially age pay data:

  • To "update" published data - for example, if pay data was collected with an effective date of 1 April, and is being used to determine an appropriate level of reward at 1 October;
  • To model forecasts - for example, if pay data was collected with an effective date of 1 April, and is being used to help set the pay budget for the following 1 April.

In both instances, you will need to add a percentage increase to the figures in the most recent salary survey.

Doing so raises some important questions.

  • First, if you are ageing pay data within the current pay year, have there really been any significant changes in the market? Most employers carry out pay reviews annually, and in most industries the majority of employers do this at the same point of the year (see chart). Pay rises in steps once a year (eg by 3% on 1 April) not by tiny increments during the year (eg by 0.2% on the 1st of each month), so in reality there may have been no real increase in pay rates for the role.
  • Second, what measure provides an accurate benchmark against which to age the data?
    • XpertHR publishes monthly pay settlement figures and tracks movements in salaries in the Pay trends report for each XpertHR salary survey. Both provide accurate and reliable data, but are based on annual rather than monthly pay movements.
    • Inflation figures are also commonly used, but these measure changes in prices not in pay - and in any event there are many different measures (RPI, RPIX, CPI and CPIX, to give just the main measures) and these often differ by a substantial sum.
  • Finally, can you foresee the future? No set of data can accurately be used as a basis for forecasting what might happen over the coming months and beyond (for example, to age data to set next year's budget).

With these caveats in mind, the calculator can provide useful information to support your decisions as a reward practitioner. However, it cannot substitute for the exercise of professional knowledge and expertise.

Chart 1: Pay bargaining calendar 2012

Chart 1: Pay bargaining calendar

n = 1,554 pay reviews on the XpertHR pay databank with effective dates from 1 January 2012 to 31 December 2012.
Source: XpertHR.

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