Can they hire 180 machinists at $26 an hour? That’s the question.
Your materials say you have 45,000 people in the labor force, a strong manufacturing tradition, and a community college partner committed to workforce development. All true. None of it answers anything.
The HR director evaluating your community is asking something much narrower. Can I fill 180 positions in one occupation, at a wage that doesn’t make me the highest payer in the market, inside a commute people will actually drive, starting on a date eighteen months from now — and will I still be able to staff shift three in year two?
Workforce is the factor most often cited as decisive in location decisions. It is also, in most community profiles, the weakest section — because the standard data is county-shaped, aggregate, and lagged, and the question is occupation-shaped, net, and forward-looking.
Available is not the same as hireable
Most workforce sections are built from three numbers: total labor force, unemployment rate, and industry employment share. Every one of those describes a stock of people. None of them describes whether a specific employer can hire a specific occupation at a specific wage — which is the only thing being decided. Four gaps do most of the damage.
The geography is wrong
County lines are an administrative fact that labor markets ignore. People commute across them in patterns that are measurable and rarely measured, and a labor market defined by a boundary rather than by drive time is describing a place that doesn't exist.
The number is gross, not net
Your shed has 2,100 people in the target occupation. So does your competitor's, because the sheds overlap — and nearly all 2,100 already have jobs. The relevant figure is how many are realistically recruitable, net of who else is hiring them, what those employers pay, and which announced projects will absorb the same pool before your prospect opens the doors.
The wage is a historical average, not a hiring reality
Published occupational wage data is lagged, smeared across a geography larger than your shed, and reports a mean that no one is actually offered. What an employer needs is the percentile picture and the real number people are being hired at right now — which employers know and published sources don't.
The pipeline is described rather than measured
"We have a community college with a strong advanced manufacturing program" is not a pipeline claim. Completions last year, how many of those completers stayed in-market, and whether the program can flex from 40 seats to 90 — those are pipeline claims, and they're checkable.
When a consultant tests your workforce section and it doesn’t hold, they don’t just discount that section. They start verifying everything else you wrote.
A low wage is not automatically good news
The instinct is to present low prevailing wages as a cost advantage, and sometimes they are. But an HR director reads a low published wage in a target occupation two ways, and only one of them is favorable. The other reading: the skill isn’t really here, and I’ll have to pay a premium above local market to pull people out of adjacent jobs — plus absorb the wage disruption that creates with the employers already here.
Which reading applies depends on evidence you either have or don’t: employment concentration in the occupation, posting volume and time-to-fill, employer-reported actual hiring wages, and what happened the last time somebody tried to hire 150 of these people in your market.
The same logic applies to the occupations where you’re genuinely thin. Naming a thin occupation with the number, the mitigation, the training partner’s committed response, and the wage premium a new entrant should expect to pay is a stronger position than omitting it — because the consultant will find it, and finding it themselves converts a gap into a credibility problem.
What defensible actually means
A net availability estimate with its assumptions on the page. A wage figure sourced to an employer interview with a date. A pipeline claim built on last year’s completions, not this year’s ambitions.
Not numbers a consultant can’t check — numbers they can check and will find correct.
Define the shed. Test the occupations. Validate. Translate.
Four to eight weeks from kickoff to a pitch-ready workforce package. The rule: every figure carries a source, a vintage, and a geography definition. Sourced, derived, and pending data stay distinguished throughout.
The geography, from commuting behavior rather than from a map
We build the shed from actual origin-destination commuting data and drive-time isochrones, at multiple rings, so the analysis describes the market an employer would actually recruit from. Then the baseline: population and age structure, labor force participation and the gap between it and the national rate, in- and out-commuting flows, educational attainment, and — critically — where your shed overlaps with a neighboring metro competing for the same people.
A defined and mapped labor shed with drive-time rings, a sourced baseline profile, and an explicit statement of who else draws from the same pool.
Occupation by occupation, not industry by industry
Target occupations selected from your recruitment roster — if you've done target industry work, that's the input. For each: current employment and concentration in the shed, wage distribution at percentiles rather than a mean, age structure and replacement demand, job posting volume and fill-time signals, and related-occupation adjacency — the pools an employer could realistically retrain from. Then the netting: from gross employment to a documented estimate of realistically recruitable supply, with the assumptions stated so the figure can be argued with rather than merely believed.
An occupation profile set, a net availability estimate per target occupation with its method written down, and a candid thin-occupation list.
The phase that separates this from a dashboard
Who else hires these occupations inside your shed, at what scale, and at what wage — including announced projects not yet hiring, which is the competition your published data cannot see. Employer interviews to validate what people are actually being hired at, which roles genuinely can't be filled, and what turnover looks like in practice. Then the training pipeline tested rather than described: program completions by year, in-market retention of completers, capacity to expand and on what timeline, and what the institution will actually commit to in writing for a prospect.
A competitive labor picture, employer-validated wage and fill findings, and a pipeline assessment built on completions, retention, and stated expansion capacity.
Into the format the audience requests
The workforce section of an RFI response, written to the structure consultants expect. Occupation availability and wage tables at percentiles. Drive-time maps. A training partner commitment page. Gap treatments for the thin occupations — the number, the context, the mitigation, and the honest wage implication, stated in your own materials before anyone else states it for you. Plus the refresh protocol, because every figure here has an expiration date and a confidently stated stale wage does more damage than no wage at all.
A pitch-ready workforce package, an RFI-ready workforce response, the underlying workbooks, and a refresh calendar with owners and expiration dates per data point.
A dashboard is not an assessment
Anyone can license the same labor data you can. The subscription products are genuinely useful and we use them — but a dashboard hands you gross figures inside a geography you selected, with no netting, no primary validation, and no judgment about which occupation is the binding constraint. That last part is the whole job.
We’re also not selling you the remedy. We don’t run training programs, we’re not a staffing firm, and we don’t have a curriculum to place. When the finding is that an occupation cannot be supplied at the scale your target requires, that answer costs us nothing to deliver.
The netting is the product
Gross occupational employment is a starting point. A defensible estimate of recruitable supply — with assumptions on the page — is what a consultant can actually use.
We validate against employers
Published wage data tells you what was paid across a smeared geography two years ago. Employers tell you what it takes to get someone in the door this quarter, and where they're failing.
We read it the way the decision-maker will
Years spent as the consultant eliminating regions on workforce findings — the most common reason regions get eliminated and the least often explained to them.
We'll tell you the target is unstaffable
More useful before you build a recruitment strategy around it than after you've spent two years pursuing it.
Structured for the way EDOs actually operate
Fixed fee, never hourly
You know the number before we start, and it doesn't move when scope clarifies.
Weeks, not quarters
Four to eight weeks. Workforce findings tend to be needed for a live pitch or a budget cycle, not for a shelf.
Phase gates, not a black box
Each phase ends with a deliverable and a decision. Phase One and Two alone give you a defensible occupation picture if that's all you need.
You get the workbooks and the assumptions
The shed definitions, the occupation models, the netting logic, the source registry. You can recreate any figure from first principles and argue with any assumption — which is what defensible actually means.
Built for boards, funders, and training partners
We'll help you present findings to your board and package them for the state, the workforce board, or the college being asked to expand a program.
We work with your team, not around it
Your staff learns the method as we build it. When the engagement ends, they can answer an occupation question in an afternoon instead of forwarding it.
Good fit
- EDOs whose workforce section hasn't been rebuilt since the labor market changed.
- Communities pursuing target industries they've never tested for staffability.
- Regional partnerships where the shed crosses jurisdictions and nobody owns the analysis.
- Organizations that keep losing at the same stage and suspect workforce is the reason.
- Anyone being asked by a live prospect for occupation-level data they don't have.
- Existing-industry retention work — your current employers are already losing the labor competition this analysis measures.
Typically 3 to 25 staff. Based in Indiana, working nationally.
If leadership needs the assessment to support a workforce claim already in a press release or a target already announced, we’re the wrong firm — this methodology produces net figures and named thin occupations, and sometimes the finding is that the target isn’t staffable here.
And if what you need is a training program built or seats filled, that’s a workforce development provider’s job; we’ll scope the ask and hand it to your college, but we’re not that.
We’re direct about fit during the discovery conversation. If this isn’t the right engagement, we’ll say so.
Often paired with
Workforce findings rarely stand alone. The pairs below reflect where the analysis feeds directly into the next decision.
Target Industry Study
The target roster is the input to occupation selection. Workforce is frequently the constraint that eliminates a target, so the two together answer a question neither answers alone.
Community Profile & Marketing
The workforce section is the part of your collateral most likely to be tested. This work is what makes that section survive testing.
Certified Site & Economic Development Strategy
Labor documentation is standard in certification programs and RFI packages.
Business Recruitment Support
Occupation-level answers are what your team gets asked for in the room and can rarely produce on the spot.
What the data actually tells you
What 4,000 Live Job Postings Tell Me That Your Workforce Study Can’t
BLS wage data is 12–18 months old by the time it reaches a conference room. Here’s how live job posting intelligence fills that gap — and what it reveals about wage competition, hiring velocity, and labor market direction.
The Site Selector’s Playbook
The validation-first methodology used to advise $50M–$3B+ industrial location decisions — including how workforce is screened, what eliminates a region, and where communities consistently miss.
Start with a conversation
Tell us the occupations your target industries actually need and what your current materials claim about them. We’ll tell you honestly whether you need a full assessment, a single-occupation read before a live pitch, or a different target list.
20 minutes, no cost.
Schedule a Fit CallOr email [email protected]