Your Deal Was Moving. Then You Asked Your Health Plan Buyer for Data.
The data you need to close the deal is the same data that derails it when you ask for it too soon.
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I was at RISE National in Orlando last week, and kept hearing the same story from different vendors.
The first one asked a regional MA plan for claims data to build a plan-specific ROI model. That was six weeks ago, and the plan hasn't responded since. The second got further with a large multi-state MA plan: their buyer verbally agreed to share data, then the plan's IT team came back and said the extract would take 90 days. The third was told flat out by a single-state Blues plan, "We don't share data with prospective vendors," even though the plan's own clinical team was championing the deal internally.
Three different responses, same result. The moment the vendor introduced a data request, the deal lost momentum.
This isn’t limited to health tech vendors, either. The same dynamic plays out when provider-side companies sell to health plans. A care delivery organization trying to win a Medicaid managed care contract faces the same paradox: the MCO wants to see outcomes data before committing, but the provider can’t generate plan-specific outcomes without the contract. A value-based care company pitching a single-state Blues plan runs into it when the plan asks for population-level impact data that only exists inside the plan’s own systems. The data trust problem is baked into how health plans evaluate anyone who wants to work with them.
Here’s what’s happening: you’re asking the plan to do work before they believe the payoff is worth doing. The data request feels like a reasonable next step to you. To the plan, it feels like a commitment they haven’t agreed to make.
And the timing couldn't be worse. Plans are fielding more vendor requests than ever, each carrying an operational burden their teams didn't face even three years ago, and the internal bandwidth to evaluate external partners is shrinking even as the volume of those requests keeps growing. Most vendors haven't adjusted their sales process to account for that shift.
This article breaks down what this pattern actually is, why vendors keep falling into it, how to restructure the conversation so the data ask lands differently, and what the vendors who consistently earn plan data are doing that most aren’t.
Why the Data Ask Stalls Deals (Even When the Buyer Is Interested)
You need plan-specific data to build a credible ROI case, but the plan won’t give you data until the ROI case is already compelling enough to justify the effort. That’s the paradox, and most vendors don’t realize they’re stuck in it until the deal has already stopped moving.
Consider what the plan actually hears when you ask for claims data or utilization files: “This vendor is going to create work for my team, and I’m not sure yet whether the outcome is worth it.” You think you’re signaling seriousness and analytical rigor. They’re hearing a commitment request before they’ve committed. You need plan data to prove value, but you need to prove value to earn the data. That’s the core tension, and most sales processes don’t account for it.
What makes this worse is what happens on the plan's side after you ask. Your buyer often can't just hand over data even if they want to. The request may need to route through IT to scope the extract, data governance to review what fields can be shared externally, and legal to confirm whether the existing NDA covers the use or whether a BAA needs to be executed. And the people who work with claims data every day inside the plan's risk adjustment or quality improvement platforms, the ones who could probably pull what you need in an afternoon, often aren't the ones with the authority to share it outside the organization. Even when the data is technically accessible, getting it out the door requires approvals, coordination, and bandwidth that your buyer may not control.
Plans are fielding a growing volume of vendor evaluations every year. The market keeps producing new entrants, and every one of those evaluations comes with its own data request. Your ask isn't evaluated in isolation. It's weighed against every other vendor asking for the same thing from the same internal teams. And when a premature data request fails, it burns goodwill with the people who manage external data sharing, making the next ask harder (and that next ask might be yours, six months later, with a different product or a renewed pitch).
Do the math on your own pipeline. If you have 15 active health plan opportunities, six of which are frozen at the data request stage, and the average deal is worth $500K annually, that’s $3M in pipeline that stopped moving because of a sequencing mistake, not a product problem.
You need plan data to prove value. But you need to prove value to earn the data.
MA plans are under sustained margin pressure, payer retrenchment is accelerating across every line of business, and nearly half of health plan C-suite executives now feel uncertain about the near-term outlook. Plans are consolidating vendor relationships and reducing the number of external partners they manage. In this environment, asking the right question at the wrong moment is one of the fastest ways to get filtered out.
But the paradox has a structural fix, and it starts with understanding what data you actually need and how to build the case without it.
What Data You Actually Need (And How to Build the Case Without It)
Before talking about how to build a case without health plan data, it’s worth getting clear on what data you actually need in the first place. For clarity, let’s define two categories.
Evaluation data is what you need to build the business case and win the deal: it typically includes claims history, utilization patterns, quality measure performance, member demographics, and/or risk score distributions. This is the data that helps you show the plan what your solution could do for their specific book of business.
Operational data is what you need to configure, launch, and run the solution after the contract is signed: eligibility files, provider directory feeds, system integration specs, care management platform configurations, and real-time data exchange protocols.
Vendors routinely ask for more data than they need at this stage, and in many cases, the request includes operational data that has little bearing on the business case. The result is a bigger lift than necessary for the plan and lower odds of getting what you actually need to advance the deal. Separating evaluation data from operational data reduces the size of the ask at the point in the relationship when the plan is least willing to invest effort, and it signals that you understand the difference between building a case and executing a contract.
Even within evaluation data, the ask can usually be far smaller than most vendors realize. More plan-specific information is publicly available than most vendors use, and the best health tech vendors have figured out how to build directionally accurate ROI cases using proxy data, public sources, and their own client benchmarks. They use the plan-specific data request as a trust-building step later rather than an early hurdle.
Start with what’s already public. There’s more plan-specific information sitting in public data sources than most vendors realize, and almost none of it requires the plan to share anything. CMS publishes Star Ratings by contract, MA enrollment and market share data down to the county level, and plan-level financial indicators like medical loss ratios. NCQA publishes HEDIS benchmarks that let you compare a plan’s quality performance against national and regional peers. State Medicaid agencies report managed care enrollment by plan. ACA marketplace data (premiums, metal tier mix, geographic footprint) is available through CMS and state exchanges. Census and American Community Survey data can map SDoH risk concentration across a plan’s service area.
None of this produces the precision of actual claims data, and assembling it into something useful takes real work. But that work is what separates a vendor who shows up with a credible, plan-specific estimate from one who shows up touting great product features and benefits. A risk adjustment vendor can use publicly reported enrollment and county-level demographics to estimate HCC capture opportunity. A Stars vendor can model what a one-Star improvement would mean in bonus revenue based on the plan’s published quality scores. A utilization management company can benchmark a plan’s ED visit and readmission rates against peers. The data, while imperfect, is there. And so, the legwork falls entirely on you, which is exactly why so few vendors do it and exactly why plans notice the ones who do.
Build a “plans like yours” model using your own client data. Your existing customers are your most underused asset in the sales process. If you’ve delivered results for plans of similar size, LOB mix, and geographic profile, that experience is worth more than any industry benchmark, but only if you present it with specificity. Name the cohort size. Name the timeframe. Name the lines of business. Buyers can tell when numbers are grounded in real client experience versus assembled from industry averages. A general case study PDF that could apply to any health plan, but it is rarely going to move them to action. However, a model where the plan can see your assumptions, test different scenarios, and adjust the inputs based on what they know about their own business just might. Transparency about what you know and what you’re estimating is what earns trust at this stage.
Make the data request feel optional, not required. After presenting what you've built with public data and client benchmarks, the strongest move is framing plan-specific data as a refinement rather than a prerequisite. In practice, that sounds something like: "Here's what we're seeing for plans your size in this region. If you want to sharpen this with your actual numbers, we can build a custom model. But even at the benchmark level, the math is pretty compelling." That framing changes the dynamic, as now the plan is deciding whether to give you more data rather than being asked to justify giving you anything at all.
This approach works across every health tech category: risk adjustment, care management, utilization management, behavioral health, SDoH, and provider network optimization. The vendors that plans proactively invite back for expanded scope showed they could do something credible with limited information. They demonstrated pattern recognition, delivered a proxy analysis worth discussing, and made the plan think: imagine what they could do with our actual data. Building that financial credibility before you need the plan’s internal data is what separates ROI models that survive CFO scrutiny from ones that get filed away.
Everything above is written for vendors and provider-side organizations, but there’s another side to this conversation (looking at you, health plans) worth addressing directly.
A Note for the Health Plans on the Other Side of This Conversation
If you’re a health plan executive reading this (and I know a growing number of you are - welcome!), everything above probably confirms what you already feel: vendors ask for too much, too early, with too little consideration for what it takes on your end.
You’re right. And there’s something you can do about it that benefits both sides.
Without a clear standard for what vendors need to demonstrate before earning access to plan data, every request becomes a one-off decision that wastes time. Implementing a tiered data request framework can give your compliance and data governance teams a repeatable process, filter out vendors who haven't done their homework, and give the vendors you actually want to evaluate a clear path forward instead of ambiguity.
A few health plan colleagues I've spoken with have landed on variations of the same idea: a tiered framework for vendor data access:
Tier 1: Benchmarking (no plan data required). The vendor shows you what they can do with publicly available information and their own client data. If the analysis is credible and the use case is relevant, the vendor proceeds to the next tier.
Tier 2: Aggregate performance data. Plan-level metrics (not member-level, not claims-level) shared under a standard NDA. This includes enough info for the vendor to build a directionally accurate business case. If the case holds, the vendor proceeds to the final tier.
Tier 3: Scoped claims or member-level data. The specific data needed to finalize the ROI model is shared under a BAA with defined data handling, use, and destruction terms.
This framework does three things. It protects your team’s bandwidth by filtering out vendors who can’t demonstrate value without your data. If a vendor can’t build a credible case using public information and their own benchmarks, they probably aren’t the right partner, regardless of what your claims data would show. Second, it gives your compliance and data governance teams a repeatable process instead of a new judgment call every time. And third, it gives vendors a clear path forward, so the vendors you actually want to evaluate spend less of your team’s time chasing approvals and more time building the analysis you need.
Giving vendors a clear standard for what you need to see before sharing data is more useful to both sides than a slow fade. The vendors worth working with will welcome the structure.
We’ve covered the paradox, the distinction between evaluation data and operational data, how to build a credible case before the plan shares anything, and what plans themselves can do to make the process work better. In the paid section below, we’ll discuss five specific moves that make plans more likely to share data, walk through scenarios where the data exchange has already gone wrong, and offer tips to help recover in each situation.
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