Problems › Small Business Consulting Services › HealthTech & Digital Health
The market for advice to digital health operators is unregulated and the quality range is wide, so choosing the right adviser is most of the work, yet the common method of a referral selects for personal fit rather than for skill at reading at-risk share and engagement rate. 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 contribution by product or job will stay a matter of opinion.
The market for advice to digital health operators is unregulated and the quality range is wide, so choosing the right adviser is most of the work, yet the common method of a referral selects for personal fit rather than for skill at reading at-risk share and engagement rate. 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 contribution by product or job will stay a matter of opinion.
The structural problem is that operators must commit to outcomes risk before they can observe whether their own engagement rate and attributed outcomes will support the share they signed, and no standard credential shows whether an adviser has diagnosed that gap correctly.
The second thing worth knowing is that the decisive variables sit in the existing figures: whether at-risk share is covered once gross margin and PMPM are applied, whether logo churn is driven by delivery capacity or by demand, and whether the measurement window is closing faster than the sales cycle can adjust.
The failure mode to watch for is the fixed sequence of moves applied to every operator regardless of the numbers, typically some combination of lifting at-risk share, adding outcome tracking, and tightening engagement targets, each of which produces the opposite result when the constraint is actually logo churn or margin compression.
A diagnostic review works through the operator's own at-risk share, engagement rate, and logo churn first and shows which lever is blocked before any larger commitment is considered, including the case where the figures indicate that further analysis will not change the need for on-site capacity.
These three together are the signature. One on its own usually points somewhere else.
✓ The proposal outlines a fixed sequence of interventions before the operator's at-risk share or current engagement rate has been examined.
✓ The adviser states the recommended change in PMPM or outcome attribution before the measurement window and logo churn data have been reviewed.
✓ The adviser cannot point to a prior client where the engagement rate turned out lower than projected and the at-risk share had to be renegotiated.
The move that usually makes it worse. Selecting on rapport and referral, which is a good filter for whether the meetings will feel useful and a poor one for whether the advice matches the constraint visible in the operator's own at-risk share and logo churn.
It is for you if you run or finance a digital health company and the proposal describes a programme rather than a diagnosis. 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. Monetize the largest three-condition outcomes dataset to subsidize outcomes risk and generate 13% growth without increasing at-risk share.
The leak it closes. Reduces dependence on 38% at-risk PMPM revenue by adding non-at-risk, high-margin revenue stream
The assumption it rests on. State privacy laws do not mandate patient-level consent for de-identified data before 2029 — the engine put the probability at 0.7.
| Investment required | $1.8–2.4M over 18 months |
| Expected return | 2.3–3.8× on $2.1M midpoint investment within 36 months |
| Revenue, year 1 | $0.8–1.2M ARR (3–4 deals) |
| Revenue, year 2 | $2.4–3.6M ARR (9–12 deals) |
| Revenue, year 3 | $4.2–6.8M ARR (15–20 deals) |
| Exit criteria | Kill move if fewer than 2 deals ≥$150k ACV close by Month 12 OR if any state privacy statute requiring patient-level consent for de-identified data is enacted before Month 18; reallocate remaining budget to Clinical Coaching Capacity Marketplace node |
This is one move out of a full analysis. Read a complete report — every page, no email required.
This question routes to Growth Strategy, 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.
For a defined piece of work — a pricing review, a profitability analysis, a growth diagnosis — £3k–£15k is the normal mid-market range and is usually enough. Open-ended monthly retainers of £1,500–£5,000 are common and are worth it only when there is ongoing delivery, not ongoing advice. If you are paying monthly for meetings, the meetings should be producing decisions you can name.
More often the latter than the market admits. A large share of small-business strategy questions are answered by disaggregating figures the business already produces but only ever looks at in total. If nobody has ever shown you contribution by product, by customer and by channel, that analysis is the first purchase and it is not expensive.
A coach works on the owner; a consultant works on the business. Coaching is about decisions you are avoiding, habits and accountability, and it genuinely helps some owners. Consulting is about what the right decision is. Confusing them is common, and paying consulting fees for accountability is the more expensive direction of the mistake.
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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