MONTH 3 · SALES PLANNING & STRUCTURE

Territory Design Model (MSA-Based)

If I hired someone tomorrow, could I hand them a territory, a comp plan, and a clear definition of what success looks like in 90 days?

This model weights the 40 largest U.S. metropolitan statistical areas using public data, then maps where your first 10 sales hires would be most efficiently placed. The weighting formula is yours to set — the sliders below encode your own hypothesis about what drives a winning territory, using the best publicly available data as the substrate.

Data sources & methodology

Market size — Metropolitan Statistical Area population, U.S. Census Bureau CBSA population estimates (2023–2025 vintage, compiled from published Census-derived sources).
Physician density — Active physicians per 100,000 population, by state, AAMC 2024 State Physician Workforce Data. Applied at the state of each MSA's principal city; the Washington, D.C. metro uses a blended figure rather than the District's standalone number, since D.C.'s small resident population relative to its regional physician workforce would otherwise skew the model.
Cost of living — Regional Price Parity, all items, by metropolitan area, 2023. U.S. Bureau of Economic Analysis, Table 4, released December 2024. The national price level is 100; a metro at 112 has price levels 12% above the U.S. average. This is a true MSA-level measure, not a state figure applied downward.
Healthcare quality — Overall state health system performance rank (1–51), Commonwealth Fund 2025 Scorecard on State Health System Performance, across 50 measures of access, prevention and treatment, avoidable use and cost, outcomes, and equity. Applied at the state of each MSA's principal city.
Limited to the 40 largest U.S. metros and the continental United States (Alaska and Hawaii excluded from the map projection). All four inputs are min–max normalized across these 40 metros, so scores are relative to this set, not to the country.

Procedure-specific market data: no reliable public dataset reports procedure or CPT/HCPCS-code volume at the metro (MSA) level — CMS utilization data of this kind is only publicly available at the state level or coarser. That layer is excluded from the score rather than approximated. Use the field below to log the codes you care about for your own record; treat any state-level signal you find separately as directional, not metro-level fact.

Two limits worth naming before you weight these. RPP is a consumer price index, not a salary survey — it tells you what a dollar buys in a metro, which is a sound proxy for what a package has to be worth there, but it is not a published wage for medical device reps. BLS publishes those (SOC 41-4011) but not in a form that covers all 40 metros consistently. Healthcare quality here means population health system performance, not the presence of elite institutions. A high-ranking state is not automatically a better place to sell a device — sometimes the reverse, since avoidable utilization and unmet need can signal procedure volume. If your buyer is an academic referral center, this measure is the wrong proxy and you should weight it near zero.

Set your weighting formula

There's no single correct formula — decide what you believe actually predicts a productive territory, then defend it. Each slider is a raw weight; the model converts them to shares of 100%. Setting one to zero removes it entirely.

Market size —

Population. Higher = you believe sheer market size predicts opportunity.

Physician density —

A proxy for how target-rich the metro is with reachable decision-makers.

Healthcare quality —

State health system performance. Read the caveat above before weighting this heavily.

Cost efficiency —

Rewards lower-cost metros. Higher = payroll is the binding constraint on your first hires.

First-rep package you're budgeting (total on-target cost, USD)

Enter a package above and each metro shows what that package has to be worth locally to hold equal purchasing power — the Rochester-versus-Boston difference in dollars.

Procedure / HCPCS codes you're focused on

Why these codes / what you'd want to verify next

Logged. No public dataset lets this model differentiate metros by these specific codes — the ranking below still runs on population, physician density, healthcare quality and cost only. Treat these codes as a research flag for validating your top candidates with claims data, a KOL, or a distributor before committing a territory.

First 10 Hires — Territory Heat Map

Bubble size and color scale with score. The 10 highest-scoring metros under your current formula are numbered and outlined — your candidate order for sales hires 1 through 10.

Lower score

Higher score

Ranked metro key