--- title: "Survey aging" description: "What is Survey Aging?" canonical_url: "https://support.pave.com/articles/survey-aging-bWhcGvhax6" md_url: "https://support.pave.com/articles/survey-aging-bWhcGvhax6.md" --- # Survey aging ## **What is Survey Aging?** Aging allows customers to age their third party (non Pave) survey data by location to ensure their third party data stays competitive over time. ## **How it works -** Apply aging to a new survey You can age new surveys your uploading for the first time to Pave, or existing surveys that you’ve uploaded previously. This section describes how to set up aging for a new survey you are uploading. ### **1. Upload your survey** 1. Map the country or the reference column you want to use to create the aging rates to “Location.” **You must map a column in your survey to “Location” in order to be able to use the aging feature.** 2. Map data effective date in the survey to the survey details (you will have the ability to update this later) 3. Map the additional columns you want to upload and use in Pave. ![](https://support.pave.com/api/attachments.redirect?id=0dfc57df-edde-4726-b7a9-70265ab07e02 " =2950x1648") ### **2. Set up aging in survey details** 1. Edit survey effective date if necessary  2. Turn on “age survey data” 3. Add age to date, which is the date you want to age your survey data to. Many companies tend to take a lead/lag, lead, or lag approach which can be achieved by choosing different age to dates: * **Lead lag:** Most companies adopt a lead-lag strategy, aging the data to midyear– leading the market for the first six months and lagging the market for the final six months. * **Lead:** Aging the data to the end of the year will result in your leading the market all year. * **Lag:** 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 remainder of the year. 4. Add in your aging rates by location for all years between the survey effective year and the age to year. The aging rates represent the expected market movement for that year in that location (often from projected merit increase percentages by country) :::info * **Note:** If you include one aging rate for one year for a location, you will have to include all year’s aging rates for that location in order to proceed. ::: 5. Press “Update” to age your survey data ![](https://support.pave.com/api/attachments.redirect?id=b3149f79-d1cf-4dfa-88cf-c03a2bdfad99 " =1128x1532") ### **3. Add aging rates** 1. Add in your aging rates by location for all years between the survey effective year and the age to year. The aging rates represent the expected market movement for that year in that location (often from projected merit increase percentages by country) :::info * **Note:** If you include one aging rate for one year for a location, you will have to include all year’s aging rates for that location in order to proceed. ::: 2. Preview the aged data from the survey 3. Press “Update” to age your survey data :::info **Note: Aging rates will be applied to age data for identified locations and non-equity pay types. Aging rates will note be applied for equity pay types.** ::: ### **Set up aging or update aging for an existing survey** You can set up aging for an existing survey at any time. :::info **Note:** If you age a survey with benchmarks associated to bands in your band set, you will need to go to the individual band sets to accept the aged data for the benchmarks ::: 1. On your Benchmarking > Data Sources page in the band set, click on the upper right hand corner of your survey and click “Survey Details” ![](https://support.pave.com/api/attachments.redirect?id=25324ae4-827c-4a50-bbd5-f5daedb2ab0b " =1130x234") 2. Turn on “age survey data” and complete aging settings (see above “Set up aging in survey details”). 3. Click Save **-** aging applied immediately * Benchmarks regenerate with aged data * Note: Benchmarks will regenerate with aged data, overwriting any existing edits. ### **Remove aging** * Go to Data Sources → find survey → Edit * Toggle aging OFF, see warning that this will revert to original survey values * Click save * All aged values from this survey revert to original survey values * Benchmarks regenerate using raw data ### **Impact on Benchmarks** :::info When you add, update, or remove aging for an existing survey: 1. The system recalculates all slices values for that survey 2. Any composite benchmarks using that survey will update to reflect the updated aging, **reverting any manual edits made.** Note: Your bands remain as-is until you explicitly update them: ::: ### **View aged data in the Survey Explorer** 1. You can click into a specific market data slice to see the aging info and turn on/off the aged data to see how the aging factor impacts the market values. :::info * **Note:** This is only for reference and will not impact the data associated with your bands * **Note:** If data is not aged for a country, it will show as 1 in the aging factor column in the table. ::: ![](https://support.pave.com/api/attachments.redirect?id=c422987f-0ade-44db-a65a-1e9aabcdaef2 " =2601x1551") ## **FAQ** **How is the aging factor calculated?** The aging factor is calculated as a compounded (YOY calculation): * **Yearly Aging Factor** = (# of days to age/# of days in year) x (increase %) +1 * **Compounded Aging Factor** = Year 1 aging factor x Year 2 aging factor Example: Age 2020 US survey data with an effective date of March 1, 2020 and age to date - June 1, 2021. In 2020, the aging rate is 4% and in 2021 it’s 3%. * 2020 US Aging Factor : ((306/365) X (4.0/100) + 1) = 1.0335 * 2021 US Aging Factor: ((152/365) X (3.0/100) + 1) = 1.0125 * Compounded Aging Factor: (1.0335 X 1.0125) = 1.0464 * This compounded aging factor is applied to the market data to age it e.g. $100,000 x 1.0464 = $104,640