Problems › We Do Not Know Who Our Best Customers Are › Healthcare Providers
Best does not mean largest panel or most attributed lives. It means the attributed lives under value-based contracts that can be managed with known cost per episode, served within the contribution per provider margin, and retained across contract cycles. What makes this harder for healthcare providers is structural: downside risk has been accepted on 38,000 lives without the cost-per-episode data needed to price it. Any credible answer therefore has to hold cost per episode and payer mix in the same view, which is exactly where most internal analysis stops because the two live in different systems.
Best does not mean largest panel or most attributed lives. It means the attributed lives under value-based contracts that can be managed with known cost per episode, served within the contribution per provider margin, and retained across contract cycles. What makes this harder for healthcare providers is structural: downside risk has been accepted on 38,000 lives without the cost-per-episode data needed to price it. Any credible answer therefore has to hold cost per episode and payer mix in the same view, which is exactly where most internal analysis stops because the two live in different systems.
Most providers can name their largest panels by attributed lives and very few can name their best, because best requires combining three things that usually live in different systems: what they contribute through payer mix, what they cost per episode to manage, and how stable the panel size remains under the value-based contract.
The results are consistently surprising. The largest panels by attributed lives are frequently mid-ranked once cost per episode is included; the best segment is often one nobody targeted deliberately, discovered through a particular payer mix and never systematised around contribution per provider.
This matters because it decides everything downstream. Which value-based contracts to pursue, how to allocate panel size, where to set episode pricing, what clinical protocols to standardise. Getting it wrong means optimising the entire provider group for the wrong attributed lives.
These three together are the signature. One on its own usually points somewhere else.
✓ Best attributed lives means largest panel size in conversation between the CFO and medical director
✓ Cost per episode is not broken out by payer mix or panel segment
✓ The target profile for value-based contracts was written from internal assumptions rather than from the existing 38,000 attributed lives
The move that usually makes it worse. Defining the target attributed lives from the largest panels under value-based contracts, which selects for the ones with the most negotiating power rather than the best cost per episode economics.
It is for you if you run or finance a healthcare provider and best customer means largest by revenue in internal conversation. 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 healthcare provider. 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 Cedar Ridge Health Partners, a sample company profile used for testing rather than a customer — 38,000 attributed lives under value-based contracts.
Excerpt from a real Percision run · Competitive Positioning · sample company profile
The move. Turn $6.8 M downside-risk liability into a $22–35 M licensing platform within 36 months.
The leak it closes. Eliminates $6.8 M downside exposure by enabling proactive utilization management.
The assumption it rests on. Cost-measurement platform achieves <5 % variance versus manual abstraction within 12 months — the engine put the probability at 0.75.
| Investment required | $2.1–3.5 M over 36 months |
| Expected return | 6.3–16.7× cash-on-cash within 36 months based on $196 M current revenue base. |
| Revenue, year 1 | $0 licensing revenue; $1.8 M internal cost avoidance |
| Revenue, year 2 | $4.2 M licensing ARR (40 physicians × $120K + 5 external practices × $400K) |
| Revenue, year 3 | $13.5 M licensing ARR (90 physicians × $120K + 18 external practices × $400K) plus $4–8 M shared-savings upside |
| Exit criteria | Terminate platform investment if variance exceeds 8 % by Month 18 OR if fewer than 40 physicians sign licensing agreements by Month 24; redeploy remaining capital to ASC surgeon-retention track. |
This is one move out of a full analysis. Read a complete report — every page, no email required.
This question routes to Customer Value Architecture, one of 29 engagements the platform runs. For healthcare providers it works through cost per episode, payer mix, panel size and contribution per provider, 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.
Combine contribution, acquisition cost and retention at the segment level. Any one of the three alone produces a ranking that is confidently wrong.
That is usually good news — it is a targeting instruction. The relevant question is whether the segment is large enough to support your growth plan, which is answerable.
Reprice first; some become profitable and the rest leave with the decision made for you. Firing directly is faster and costs you the information about which were repriceable.
Materially, yes. Downside risk has been accepted on 38,000 lives without the cost-per-episode data needed to price it — which changes both the diagnosis and the order of the fixes. The metrics that decide it here are cost per episode, payer mix, panel size, 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 cost per episode and payer mix. 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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