Work Output: Quality and outcomes
Objective. Read the quality view as the filter that makes output 'clean', and check coverage and basis before trusting a score - high coverage is not the same as accuracy.
Quality and outcomes answers 'was the completed work actually good, or just fast?' It is the filter that turns raw output into clean output, which is the only output that belongs in a value or cost-per-unit claim.
See it in the demo
What this screen answers
Sales uses quality to defend against the 'this just measures speed' objection - clean output per paid hour, not throughput, is the claim. CSMs use it to validate that the quality signal is real before any cost-per-clean-unit figure is trusted. The customer question is 'how much of our output met standard, and how do we know?'
The task
Scope to the team, process or period and read the quality signal alongside the output volume, not instead of it - the point is the pairing. Check how quality is determined: full check or sample, and against what rubric. Carry a quality dip to root cause and coaching. For a CSM, the task is to confirm the quality definition and coverage with the customer before 'clean output' appears in any review, because a weak quality signal makes every clean-output figure soft.
How to read it
Quality is what makes output 'clean', and clean output per paid hour is the honest value measure - raw output without this filter flatters a fast-but-wrong team. The classic misread is treating high quality coverage as proof of high quality: coverage is how much was checked, accuracy is whether the checks are right, and a sampled score carries uncertainty. Read volume and quality together, and never let a strong quality score stand in for the cost and outcome screens that complete the picture.
Honest limits
This screen does not prove the rubric is the customer's agreed standard, that sampling is representative, or that a score equals a real-world outcome. It is seeded demo data. Confirm the quality definition, sampling approach and coverage with product, and anchor any 'clean output' claim to the customer's agreed quality standard, not the demo's.
Interpretation check
Quality is the filter that makes output 'clean' - the only output a value or cost claim should use; high quality coverage means how much was checked, not that the scoring is accurate, so read volume and quality together and confirm the standard.
In the field
KnackGlobal's displacement case rests on clean claims, not worked claims - this screen is where 'clean' is defined, and a weak quality basis would undermine the whole cost-per-clean-claim argument.
Practical task
Pick a team and period, read output and quality together, and write a one-line finding that states the clean-output picture and whether the quality basis (coverage, sampling, rubric) is strong enough to trust it.
Self-check
'We measure quality on 95% of work, so our quality is high.' What is the confusion?
Coverage is not accuracy. 95% coverage means almost everything was checked, not that it met standard or that the checks are right. The quality score and the rubric, not the coverage, answer 'how good'.
Why does quality sit in the same app as output and cost?
So 'clean output per paid hour' and 'cost per clean unit' are the claims, not raw throughput. Without the quality filter, a fast-but-wrong team looks strong.
A team's quality score is from a sample. How does that change your reading?
A sampled score carries uncertainty and must be read as an estimate, not a census - and you confirm the sample is representative before trusting it.
Verified vs demo. Screen is live in the demo at https://work-output.demo.timechamp.io/#/quality; exact controls, labels and on-screen figures are SME-validation-pending.