plan the workforce your strategy demands

demand modelled, supply measured, gaps priced, and every gap answered four ways: build, buy, borrow, or bot. workforce planning that reruns itself when your strategy moves.

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the challenge today

your headcount plan expired the day the strategy changed

the annual plan answers one question: how many people. strategy keeps asking harder ones: which capabilities, ready when, at what cost, against which risk. those need an engine, not a spreadsheet.

demand projection with role evolution supply, from skills and performance together skill half-life and obsolescence risk AI readiness by role capacity & capability index scenario simulation

the signals the planning engine watches continuously, all read from axon and the live market graph.

every gap has four answers, all of them priced

a worked example of the build–buy–borrow–bot decision, the way it lands in the platform.

scenario: generative AI reshapes underwriting. 40 roles change profile inside 18 months. the simulation agent prices four routes for the gap:

build22 roles

current adjusters within one skill tier of the new profile. reskilling paths generated from their measured gaps; cheapest route, longest lead time, highest retention payoff.

buy6 roles

net-new capabilities with no internal bench and a hot external market. benchmarked against live demand data so offers land right the first time.

borrow8 roles

peak-load and transition work suited to contractors and partners; capacity without permanent cost, flagged for later build-or-buy review.

bot4 roles

rules-based workload the same AI wave automates. planned as automation with redeployment paths for the people, not as quiet attrition.

from annual exercise to standing capability

the annual exercisedemand guessed from last year's org chart plus growth percent

the standing enginedemand modelled from strategy, with role evolution read from the market graph

the annual exercisesupply counted as headcount in seats

the standing enginesupply measured as capability: assessed skills and performance, per role

the annual exerciseone plan, frozen in the budget deck

the standing enginescenarios simulated on demand: the reorg, the acquisition, the AI wave

the annual exercisegaps become requisitions by default

the standing enginegaps become build, buy, borrow, or bot decisions with costs attached

10%lower overall labor cost where strategic workforce planning is done well, per industry research

20%year-one productivity gain reported by the same research

4Bevery gap answered as a decision, not a default requisition

what planning teams pressure-test

where does the demand signal come from?

Two places: your strategy, translated into capability demand per unit, and the market graph, which reads role evolution from 3 billion+ job postings and 1.2 billion career profiles, anchored to the Lightcast taxonomy and refreshed monthly. Plans reflect where roles are heading, not where they've been.

what makes the supply side credible?

It's measured, not asserted. Supply comes from axon: assessed proficiencies, performance history, and aspirations, so "we have 30 people who can do this" means thirty people who demonstrably can. see workforce assessments →

can finance work with the output?

Yes. Every 4B route carries cost and timeline, so the workforce plan lands in budget language: what build saves versus buy, what borrow defers, what bot retires. The argument moves from opinion to arithmetic.

how often should the plan rerun?

Whenever something moves. Because demand, supply, and risk are live signals, a rerun is a simulation, not a project. Most clients hold a quarterly planning rhythm with ad-hoc scenarios for big decisions.

plan capabilities, not just headcount

the planning engine runs on the platform behind millions of users, Forrester-validated at the platform level.

run your first scenario →