The core idea
Trend analysis examines how a measure changes over time. A time-ordered plot helps reveal shifts, unusual observations and patterns that a single period hides. In people analytics, the definition and denominator must remain comparable. A rising count may reflect workforce growth rather than a higher rate, and a seasonal pattern should not be mistaken for a lasting deterioration.
Source and attribution [1]Using it in practice
Choose an appropriate interval and show enough history to understand variation. Mark known process changes and breaks in data collection. Plot counts and rates when both matter. Distinguish a descriptive chart from a forecast, and avoid drawing a confident conclusion from one unusual month. Ask whether the apparent pattern survives a change in the display scale or aggregation period.
An example, not a reported case
Worked example · illustrative
A fictional employer records 20 leavers from an average workforce of 200 in one year and 24 from 300 in the next. The count rises, but the comparable annual turnover rate falls from 10% to 8%. A monthly chart also shows recurring departures at the end of seasonal contracts. The review separates those events from voluntary departures before proposing a retention intervention.
What to watch for
Rolling averages can smooth noise but also delay or obscure a real change. Different periods may have different exposure and composition. A chart cannot establish why a shift happened. Do not compare a partial month with a completed month without an explicit adjustment and explanation.
Keep the series reproducible
Record the metric definition, extraction date and any revisions. If a system change alters what is recorded, mark a break rather than pretending the whole series is uniform. Retain the underlying counts so a rate can be checked.
Choose a review trigger
Agree what pattern merits investigation before repeatedly scanning for an alarming result. Use appropriate statistical advice for formal control limits or time-series models. A useful chart supports a proportionate question, not a reflex response to every fluctuation.
Take it into your next conversation
Three useful questions.
- What question can this method answer, and what can it not establish?
- Are the comparison, observation period and assumptions defensible?
- What decision follows, and how will its consequences be reviewed?
Go to the evidence
Sources & attribution
[1] NIST: Run-sequence plots ↗
The core idea is an original summary of the cited work. Application notes, examples and sketches are our interpretations, not quotations or reproductions of the authors’ figures. Publisher records may require access to read the full original work.
Published 2026-09-20 · Reviewed 2026-09-20. Editorial approach