Problems › The Team Is Not Executing the Plan › HealthTech & Digital Health
When a good plan is not being executed, the usual cause is that the organisation is rationally doing something else. This page works through it for digital health companies specifically — including an unedited excerpt from a real analysis of a digital health company.
When a good plan is not being executed, the usual cause is that the organisation is rationally doing something else. Digital health companies carry a specific bind here — outcomes risk is being signed faster than the company can learn whether it can carry it — a 12-month measurement window against an 11-month sales cycle. Until that is priced, at-risk revenue share will keep moving for reasons nobody can attribute, and the debate about decision latency will stay a matter of opinion.
Execution failure is rarely unwillingness. It is normally that the plan asks for behaviour the structure, the incentives or the capacity actively discourage — and people resolve that conflict the way the system pays them to.
The diagnostic question is not "why is nobody doing this" but "what is the person being asked to give up, and who compensates them for it". A plan that requires a team to sacrifice their own numbers for someone else's will not run, however well communicated.
The second common cause is arithmetic: the plan requires more capacity than exists, and rather than saying so, the organisation quietly does the subset it can and the rest simply never happens.
These three together are the signature. One on its own usually points somewhere else.
✓ The plan is understood and agreed and still nothing changes
✓ Progress is reported as activity rather than as outcome
✓ The people asked to change are measured on something the change hurts
The move that usually makes it worse. Communicating harder, which addresses a comprehension problem that does not exist and delays finding the incentive that does.
It is for you if you run or finance a digital health company and the plan is understood and agreed and still nothing changes. It is the situation where the numbers are available but nobody has put them in an order that produces a decision.
It is not for you if Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.
Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.
Below is an excerpt from a real run of this analysis on a digital health company. It is a sample profile rather than a customer, and it is unedited engine output — this is the format you get, on your own numbers.
The subject is Vantabridge Health, a sample company profile used for testing rather than a customer — $62M ARR, 340,000 enrolled members.
Excerpt from a real Percision run · Cost Reduction & Efficiency · sample company profile
The move. Convert 2.9M contracted lives into Medicare Advantage outcomes contracts using existing payer integrations and outcomes proof points.
The leak it closes. Prevents value leakage to in-house payer solutions by demonstrating superior 12-month cohort outcomes data
The assumption it rests on. At least 4 of 34 existing health plans will sign MA outcomes contracts within 24 months — the engine put the probability at 0.75.
| Investment required | $1.8-2.4M total over 24 months |
| Expected return | 250-580% over 36 months on $62M base revenue |
| Revenue, year 1 | $2-4M incremental ARR (2-3 MA contracts) |
| Revenue, year 2 | $6-14M incremental ARR (4-7 MA contracts) |
| Revenue, year 3 | $12-25M incremental ARR (8-12 MA contracts) |
| Exit criteria | Abandon if fewer than 2 MA contracts signed by month 18 OR if engagement rate in MA pilot cohort falls below 30% OR if NCQA certification denied |
This is one move out of a full analysis. Read a complete report — every page, no email required.
This question routes to Organizational Alignment Model, one of 29 engagements the platform runs. For digital health companies it works through at-risk revenue share, engagement rate, gross margin and logo churn, then produces the sequence rather than a list of options — which move first, what it funds, and the observation that would say the sequence is wrong.
You watch the analysis get built before paying anything. Read a complete report here if you would rather see the depth first.
Change what people are measured on before asking them to behave differently. Buy-in follows the incentive far more reliably than it follows the explanation.
Occasionally. Far more often it is a structure problem that looks like a people problem, which is worth testing first because replacing people does not fix a structure and is expensive to discover.
Usually yes, but for capacity reasons rather than comprehension. A plan with three priorities that fit the capacity available beats one with twelve that do not.
Materially, yes. Outcomes risk is being signed faster than the company can learn whether it can carry it — a 12-month measurement window against an 11-month sales cycle — which changes both the diagnosis and the order of the fixes. The metrics that decide it here are at-risk revenue share, engagement rate, gross margin, and an answer built on industry-general benchmarks will usually point at the wrong one first.
Less than most people expect. Your last twelve months of revenue and cost split the way you already split it, plus whatever you hold on at-risk revenue share and engagement rate. The analysis is explicit about what it is assuming where your data stops, which is more useful than waiting for numbers you may never have.
Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.
Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.
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