Health plan growth strategy: The state looks flat. The counties aren’t.

You’ve sized the market, set next year’s targets, and shown leadership where growth will come from. Underneath your plan sits one read: the statewide one. It’s flat and mature, and growth is hard to find. It’s reasonable, and you can defend it. But a state is an average, and an average is the one number in your plan guaranteed not to describe where you actually compete: the counties.

Inside it, some counties are growing while others shrink, some are aging into Medicare while others fill with working families, and some are wide open while a single competitor already owns them. The state figure shows none of that. It shows the net: you don’t sell to the net.

Key points

Plans that win their markets plan against the county, not the state: a statewide average is the one number guaranteed not to describe where you compete.

• Counties within the same state can move in opposite directions at the same time. A growing state can hide a shrinking market, and a shrinking state can hide a growing one.
• Granular visibility is only useful if you have up-to-date data. Last year’s county rankings and a live read of where counties are moving now are two different things, and the first won’t get you the second.
• Before you set a county target, read three signals against your own footprint: demand, demographics, and competitor presence. Rank alone won’t separate real opportunity from a market you already own.

Two ways the state number sets a trap

So, where does the state number go wrong? Not in existing, and not in being the first thing you reach for. It goes wrong when it becomes the last word instead of the first.

As a first read, it earns its place. It’s the level public data arrives in, and for a quick take on whether a market is expanding or flat, it does the job. It becomes an issue when it’s the number you plan against, because it misleads in two specific ways. The first is divergence: within one state, counties grow and shrink in the same year. The second is timing: the counties that grew last year often reverse the next. Neither shows up in the statewide figure.

The first trap: how far counties diverge inside one state

Texas shows the trap in one direction. In a single year, the state added about 391,000 residents, a 1.2% gain that led the country. From this perspective, Texas looks like an obvious place to grow. However, if you look at the state’s most populous counties in the same year, you’ll see two different stories. Harris County, home to Houston and the state’s most populous, grew by 48,695 residents, whereas Dallas County, the state’s second most populous, lost about 2,616 residents. Work from the state average and you’d never see that one of your biggest urban markets was contracting while another showed healthy growth.

California shows the trap in the other direction. It was one of only five states to lose population in 2025, a number that can completely write a state out of a growth plan. However, if you look more closely, you can see that Riverside County added about 15,800 residents, a county you’d want to weigh for resources. The statewide decline hides a growing market, not just a shrinking one.

Texas and California aren’t special cases; the same averaging applies at every level, including the metro level. And the divergence isn’t random. Census attributes most of the recent slowdown to a decline in net international migration, which never landed evenly across the state to begin with. For a health plan, the lesson runs both ways: within a single state, some markets expand while others contract, and the state figure reports only the difference between them. Plan against that net, and you’re planning for a market that doesn’t exist in any county you actually sell in.

The second trap: last year’s fastest-growing counties aren’t a safe bet for next year

Say you do drop to the county level. The safe move is to target the counties that grew the most last year, right? Not necessarily. Of the 2,066 counties that grew between 2023 and 2024, nearly four in five slowed or reversed the very next year.

The reversals aren’t always marginal. Miami-Dade lost 10,115 residents after gaining 18,633 the year before. A target list built on last year’s rankings isn’t just a little stale; it can point at counties that have already turned over, while the counties now worth pursuing sit off the list because their prior year was unremarkable.

This is why the input to your plan must be current, not just granular. A ranking of last year’s growth is a snapshot of a year that’s already over, and by the time a county reaches the top of it, the growth that earned the spot may have already faded. Setting next year’s targets means seeing where counties are moving now, not where they moved a year ago.

The three signals that matter at the county level

Reading a market at the county level comes down to three signals, each read twice: demand, demographics, and competitor presence. First, you compare a county against other counties: where does it rank on this signal? Then you compare it against your own position there: does that ranking actually represent opportunity for you? The second comparison is the one that turns a data point into a decision.

A county can top the list on growth and still be one you already serve to saturation; another can sit mid-table while demand is arriving faster than you’re meeting it. Rank alone won’t tell them apart: rank read against your own footprint will.

Demand: Where are population and employer base growing?

The first comparison is straightforward: which counties are adding residents and businesses fastest? For a payer, demand comes from two sources that don’t always move together: population, which feeds your individual and Medicare lines, and employers, whose hiring feeds your commercial group. A county can be adding retirees while its business base flattens, or filling with young workers while established firms move out, so ranking a county on demand means reading both at once.

The second comparison is against your own presence, and it’s the one that turns growth into opportunity. New business formation climbing in a county where your small-group book has stayed flat is a different, more actionable finding than a county simply growing. The first is a market moving toward you; the second is a market moving away from you. That gap, between where demand is rising and where you’re actually capturing it, is where the demand signal earns its place.

Demographics: Who lives here, and how is the mix shifting?

Demographics follows the same two-comparison logic, and the first comparison ranks counties by who lives there: how the population splits among older adults, working-age adults, and children. That mix is exactly what a state average flattens, and nationally, it’s tilting older, unevenly.

From 2020 to 2024, the population aged 65 and older grew by 13.0%, far outpacing the 1.4% growth of working-age adults (ages 18 to 64), while the number of children fell by 1.7%. Additionally, older adults now outnumber children in nearly half of all U.S. counties (1,411 of 3,144 in 2024, up from 983 in 2020), and in 11 states, including Maine, Vermont, Florida, and West Virginia. So, “Who lives here?” has a real answer, and it differs sharply county to county.

The second comparison is against your own product mix, which is what makes that range matter to you. A county aging into Medicare and a county filled with working families are different businesses, and a plan weighted toward Medicare Advantage will rank them in the opposite order from a plan weighted toward commercial group, reading the same data. The demographic signal isn’t “this county is old.” It’s “this county is becoming the kind of market you sell to, or the kind you don’t.”

Competitor presence: How much of the market is already spoken for?

Competitor presence works the same way, and here the first comparison is against the national baseline because you can’t tell whether a county is crowded until you know what normal looks like. According to the American Medical Association, normal is crowded. In nearly half of metro areas (47%), a single insurer already holds at least half of commercial enrollment, and in 91% of metros, at least one insurer holds 30% or more. So, a dominant carrier isn’t a red flag on its own; it’s the default condition.

The second comparison is against demand in that same county, which is what turns a share figure into a decision. Take two counties in your footprint: one is growing fast, but a single carrier holds 60% of commercial lives; the other is growing slowly but splits evenly between two mid-size plans. The faster-growing county is the harder, slower entry. You’d be prying share from an entrenched incumbent, while the slower one may be the more winnable. In most of the country, a growth plan isn’t entering an open market; it’s choosing which incumbent to take share from, and the county view is where that choice gets specific.

Of course, none of these signals hold up if the inputs don’t. Every one of these signals (migration, employer formation, enrollment) comes from public sources that carry gaps in coverage, timing, and access, and those gaps don’t announce themselves once the numbers reach a planning deck. Reading at the county level and trusting what you’re reading are the same discipline from two directions, which is the subject of Part 1 of this series.

Plan against the county before you set your targets

A state is a reporting unit, not a market. The plans that grow efficiently aren’t working harder; they’re working from the county, because that’s where two markets in the same state can be a clear opportunity and a clear trap at once.

This isn’t news to the largest national carriers, which have data-science teams that work at this level of detail as a matter of course. If you run a regional or mid-market plan, the gap isn’t skill or will: it’s that pulling demand, demographics, and competitor presence into one current, county-level read takes the people, time, and tooling that most lean teams have never had. So the state number stayed the default, not because anyone chose it, but because assembling anything better wasn’t realistic.

That’s what Data Axle for Healthcare is for: one current, aggregate, de-identified view that holds demand, demographics, and competitor presence for every county in your footprint, not a stack of mismatched state files. So, the next time you defend a growth number, it points at the county you compete in, not the average you don’t.