by LuminOneBook an introductory call ↗Measure preparation, review effort and output quality before and after deployment. Use comparable work and an agreed standard.
Use this framework to evaluate your own deployment. It contains no forecast of your results or claimed customer ROI.
Record preparation and review time, accepted work and corrections before deployment. Compare equivalent work afterward. Include implementation and ongoing costs, and separate capacity released from cash savings.
Use the measurement framework ↓Blank framework, not customer results. Compare the same kind of work, sample size and review standard before and after deployment.
| Measure | Before | After |
|---|---|---|
| Preparation minutes per output | To measure | To measure |
| Review minutes per output | To measure | To measure |
| Outputs accepted / outputs reviewed | To measure | To measure |
| Corrections per output | To measure | To measure |
Without a baseline taken before deployment, every number afterwards is a claim rather than a result.
Measure the current state first. How long does the work take, how much time goes into rebuilding context, and how much correction is needed before an output can be used? Without this you have nothing to compare against, and any later number is a claim rather than a result.
Measure the workflow you actually deployed. Attributing a quarter's commercial performance to one workflow is not measurement, and experienced buyers discount it immediately.
Decide with the reviewing team what an acceptable output is before the first one is produced. Approval rate only means something if the standard was set independently of the result.
Track execution and outcomes, approved volume, approval rate, turnaround, coverage and reviewer time.
Count prepared work, approved actions, completed execution and observed outcomes separately. Approval is not proof that an action completed, and a completed action is not proof of a commercial result.
How many pieces of prepared work your team approved in a period. This is the most direct measure, because approval is a person judging the output good enough to use.
The share of prepared work that gets approved rather than discarded or rewritten. A low rate means the workflow is producing volume rather than value. Track the reason for rejection, not only the count.
Track time from trigger to accepted output. For signals-to-leads this may be first useful contact; for proposal preparation it is a review-ready brief; for a handoff it is the receiving team having what it needs.
How much relevant work receives the agreed review standard: accounts prepared, meetings briefed or handoffs completed. Record the eligible volume as well as the work completed.
How long a person spends reviewing and correcting prepared work. If review takes as long as doing the work, the workflow has moved effort rather than reduced it.
Some figures look convincing in a deck and fail the first serious review.
A benchmark can provide context, but check its sample, baseline, method and relevance to your workflow. It is not evidence of the return your team will achieve.
Adoption metrics measure whether people opened the software. They do not measure whether the work it produced was good enough to use.
Commercial outcomes in life sciences have long cycles and many causes. Claiming a workflow produced a specific revenue figure is rarely defensible, and it damages credibility with the finance reviewer who checks it.
Measure preparation and review time before and after deployment. If you model financial value using an hourly rate, label the assumptions and distinguish capacity released from cash savings.
The platform proposition is that a new workflow improves the others. Test that proposition against a specific change, using comparable work and the same review standard.
Record how often an existing workflow needs someone to supply missing context, correct an outdated assumption or reconstruct an earlier decision.
Check those same outputs for completeness, correction effort and handoff delays. Record what changed and other factors that may have contributed.
For example, assess whether meeting preparation needs less manual correction after a debrief workflow begins contributing customer priorities. This is a measurement example, not a claim of observed results.
Baseline preparation, context rebuilding, review effort, turnaround, rework and quality before deployment. Compare the same workflow after launch. Include implementation and ongoing costs; distinguish time released from cash savings.
Preparation time, review effort, handoff delay, rework and the volume of work completed today. Agree what an acceptable output looks like before the first one is produced.
Commercial cycles in life sciences are long and have many contributing causes. Attributing revenue to one workflow is rarely defensible under scrutiny, and a claim that does not survive the finance review costs more credibility than it gains.
This page provides a measurement method, not a benchmark or promised return. Assess a proposed workflow against your own baseline, costs and acceptance criteria.
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A useful plan names the owner, review standard and baseline before work begins. See how these fit into the relationship.
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