Headcount & FTE Trend

The report every executive asks for first, and the one where two dashboards most often disagree. The fix is one set of definitions and one snapshot table, and both fit on this page.

RuleDefine the population once, count from the snapshot, and every report inherits the same answerNevercompute headcount live from worker lists. Retro changes and population choices make each run a different number.

◆ What Workday gives, and where it stops— good current-state lists, weak history: the daily snapshot does not exist until you build it.

Delivered	What it does	Where it stops
Worker reports	Current lists on the worker data sources, filtered and prompted. See Worker.	Current state. History means re-running as-of dates one at a time.
Trending reports	The Trending report type shows period-over-period worker movement.	Fixed shape, in-tenant, and not a table you can join to payroll or finance.
People Analytics	Delivered workforce insights inside Workday.	Workday's walls: no cross-system joins, and you rent it. See the extraction pattern.

None of these keeps a daily record of who was employed on each date. That table, the snapshot, is the whole answer to trend reporting, and you build it once in your warehouse.

◆ The definitions— fix these four once, in the model, and dashboards stop disagreeing.

Metric	The definition to fix
Headcount	Workers with an active primary assignment on the date. State whether contingent workers count; the delivered data sources differ on exactly this.
FTE	The sum of FTE percentages, not a count of people. Two half-time workers are one FTE and two headcount.
Point-in-time vs average	Headcount on March 31 and average headcount for March are different numbers. Boards usually want both; label each.
Who counts when	Primary position only, or additional jobs too. Hired-not-started and terminated-with-future-date decided once. See the traps on Worker.

◆ The owned model, and the SQL— one query on the snapshot star answers the trend, by any dimension.

The report reads the snapshot star: fct_worker_snapshot joined to dim_org, dim_job, dim_cost_center, and dim_date. The trend by organization:

-- month-end headcount and FTE by level-2 org, employees on primary assignment
SELECT d.month_end_date,
       o.level_2                    AS organization,
       COUNT(DISTINCT f.worker_key) AS headcount,
       ROUND(SUM(f.fte_pct) / 100.0, 1) AS fte
FROM fct_worker_snapshot f
JOIN dim_date d ON f.date_key = d.date_key AND d.is_month_end
JOIN dim_org  o ON f.org_key  = o.org_key
WHERE f.worker_type = 'Employee'
  AND f.is_primary
GROUP BY 1, 2
ORDER BY 1, 2

Sample output. FTE runs below headcount where part-time workers sit, and the reorg from the dim_org sample shows up as the org label changing between March and April while the people stay counted:

month_end_date	organization	headcount	fte
2026-03-31	Sales	142	139.5
2026-04-30	Revenue Org	145	142.5
2026-05-31	Revenue Org	147	144.0

Swap dim_org for dim_job and the same query is level mix; swap in dim_cost_center and it is headcount by budget, ready to join payroll cost. One table, every axis. Sample values are illustrative, never client data.

Want the headcount trend live on your cloud in 10 days?

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Terms on this page

headcount: Workers with an active primary assignment on a date, per the fixed population definition.
FTE: Full-time equivalent: the sum of FTE percentages, not a count of people.
snapshot fact: One row per worker per day or month. The history table Workday does not keep.
point-in-time: The number on a specific date, as opposed to a period average.
primary assignment: A worker's main position, as opposed to additional jobs.
Trending report: Workday's report type for period-over-period worker movement, in-tenant.
People Analytics: Workday's delivered workforce insights, inside Workday.
as-of join: Joining a fact to the dimension row valid on the fact's date, so reorgs do not rewrite old months.