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The share of employees at the start of a period who are still employed at its end. People hired during the period are left out, which is why retention and attrition calculated for the same period do not always add up to one hundred per cent.
Not simply the inverse of attrition. Attrition counts all leavers, including recent hires; retention follows only the starting group.
HR usually produces retention once a year for the management review, with a quarterly cut by department or manager. The work is in freezing the starting list: export the employee master as it stood on day one of the period and keep that file, because later corrections to joining or exit dates change the answer.
As an example, a plant starts April with 240 people. By March, 204 of those same 240 are still on the rolls, so retention is 204 / 240, or 85%. Forty people hired during the year and fifteen of them leaving does not move that figure at all.
The common mistake is treating transfers between group entities as exits. If one legal entity's master shows the person leaving and another shows a new joiner, retention drops for no real reason. Agree in advance whether retention is measured per entity or per group, and tag inter-company moves so they can be filtered out.
Take the number of employees at the start of the period who are still employed at the end, divide by the headcount at the start, and multiply by 100. People hired during the period are left out of both figures.
Not exactly. Attrition usually counts all leavers against average headcount, including people who joined and left within the period, while retention tracks only the starting group. The two can move differently in a year of heavy hiring.
No. Including them distorts the measure, because someone who joined in month ten has had little chance to leave. Track early leavers separately as new-hire retention, for example at 90 days or one year.
Annual retention is the standard comparison, with quarterly figures for monitoring. Whatever period you choose, keep it fixed so year-on-year comparisons are like for like.
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