The coverage promise, checked

May promised 20,160 hours of coverage and got 19,875. The missing 285 have locations, and the more useful finding is the reverse one: the department with the best adherence is buying it with overtime. One number, read alone, would have called that team healthy.

RuleCompare worked hours to scheduled hours at day grain, by department and week. Coverage is a promise; adherence is whether it was kept.

Neverread high adherence as health on its own. A team that hits schedule by burning overtime is covering a staffing gap with money.

The promise, the reality, and the difference with a location. Which shifts broke, and who covered them, is the drill below.

◆ May, the adherence table120 hourly workers against their schedules.

Department	Workers	Scheduled	Worked	Gap	Adherence %
Sales	46	7,728	7,592	136	98.2
Technology Delivery	41	6,888	6,841	47	99.3
Support	33	5,544	5,442	102	98.2
Hourly population	120	20,160	19,875	285	98.6

The 120 are the same hourly population the completeness control expects timesheets from, scheduled at eight hours across May’s 21 working days. The company looks healthy at 98.6; the drill is where it stops being one number. Sample values are illustrative, never client data.

◆ Reading the gapadherence and overtime, side by side.

Technology Delivery runs the tightest adherence and the heaviest overtime. That combination is not health: it is a schedule being met by paying time-and-a-half, a staffing gap wearing a good number. Support misses schedule and runs lean on overtime, which usually means shifts simply went uncovered.

Adherence, overtime, and absence read together or they mislead separately. The unplanned absence rate is the third leg: most broken shifts start as a morning call-out.

◆ The owned answerday-grain schedule beside day-grain actuals.

The schedule is a fact at worker-day grain, the same grain the time entries land at, so the comparison is a join with no allocation logic. Both facts are drawn on the time-tracking star, and the model page is the reference.

Use case

Problem

Coverage is planned in one tool and worked in another: nobody sees which shifts actually broke, and schedule-hitting teams that burn overtime to do it look identical to healthy ones.

What we build

A schedule fact at worker-day grain joined to worked time at the same grain: adherence by department and week, read beside overtime and unplanned absence.

What you get

Coverage you can manage: the broken shifts located, the overtime-subsidized schedules exposed, and staffing decisions made on the pattern instead of the anecdote.

Is overtime quietly holding your schedule together?

We build the day-grain adherence model that reads coverage honestly.

Talk to us

Terms on this page

adherence: Worked hours over scheduled hours; the kept-promise rate.
coverage: The scheduled staffing a shift or period requires.
worker-day grain: One row per worker per day; where schedule meets actuals.
broken shift: Scheduled coverage that nobody worked.
overtime subsidy: Hitting schedule by paying premium hours; a gap in disguise.
call-out: An unplanned absence reported at shift start.