Workforce Readiness as the Pacing Dimension of Strategic Readiness in Digital Transformation

The Pacing Claim

Our July argument held that the pace an organization can sustain in a digital transformation is permitted by strategic readiness, not by ambition alone. Readiness sets the clock. But readiness is not a single thing, and saying it “sets the pace” is only useful once we can say which part of it binds first. This article resolves readiness into its human dimension and makes a specific claim: of all the conditions a transformation depends on, the readiness of the workforce to perform the work the transformation implies is the one that hiring alone cannot supply. It has to be built, and building is slow, because the current workforce must evolve to run the future operating model, because hiring the whole target state is rarely affordable or practical, and because new hires arrive without the undocumented knowledge current people hold. That is why workforce readiness sets the pace.

One word needs pinning down first, because it carries two incompatible meanings and the argument depends on the narrower one.

The dimension this article is concerned with is therefore workforce readiness: the readiness of the workforce to perform both the work of the transformation itself and the roles and tasks the target operating model will require. It has two faces the rest of the article keeps distinct. Capability is whether the workforce can do the new work, the distance between the skills it holds and the skills the work demands. Capacity is whether the workforce has the time to do the transformation work and build toward the new roles while daily operations continue. Both are buildable, both are measurable, and both move slower than decisions do, which is why they, rather than technology or budget, tend to bind first.

The argument rests on two elements that run through everything that follows. Neither is the conclusion; both are the premise.

The first is the operating model, understood not as a finished blueprint but as what the transformation work produces and the organization adopts. How much workforce readiness a transformation requires is not set by how much technology it deploys. It is set by what the transformation and its target operating model demand: which roles must change, how far, and therefore which skills the workforce must come to hold. This sizes the readiness requirement. Until it is understood, “how ready do our people need to be” has no defensible answer.

The second is ownership, which comes in two forms. The transformation workforce plan, the artifact carrying the required roles, headcount, and skills into a sequenced plan, is owned by the CHRO, who is accountable for the plan and its execution. That is ownership defined by role. Separately, each benefit the transformation exists to deliver has its own owner, defined not by position but by a test: the benefit owner is whoever can sustain the thesis of the benefit and trace it to an organizational objective. That owner may be a business unit, end users, a workstream owner, or anyone who meets the test. A senior title does not make someone a benefit owner; the ability to keep the benefit tethered to an objective does.

Together these set up the claim the article defends:

Understand the Current Operating Model

Leaders are more confident about their readiness than their operating models warrant. In its 2025 Target Operating Model study of nearly 400 C-level executives across Europe, BearingPoint found that while 70 percent rated themselves well-prepared for future demands, only 4 percent said their operating model is fully aligned to support their strategic goals. The same study named talent and skills gaps among the top barriers to operating-model performance, alongside insufficient data and insights. This article takes up the talent side because it sets the pace. Closing the gap between feeling ready and having an operating model that actually supports the strategy starts with an honest reading of how the work is done today.

That reading has a discipline behind it. McKinsey’s Organize to Value research offers the most complete current account of what an operating model actually is, and it is worth using as the frame. It updates the classic 7-S model into a system of twelve interacting elements: purpose, value agenda, structure, ecosystem, leadership, governance, processes, technology, behaviors, rewards, footprint, and talent. The central finding is that an operating model is not the org chart; structure is one element among twelve, and redesigning it while leaving the others untouched is how organizations spend money and recover none of it. Even high-performing companies, McKinsey finds, realize only about 70 percent of their strategy’s full potential, and the shortfall is attributable to operating-model shortcomings. The prescribed starting point is not redesign but diagnosis: identify why the strategy has not translated into performance, then decide which elements must change.

This article inherits that method and departs from it on one point. The inheritance is the frame: the current-versus-target reading, diagnosis before redesign, and the twelve-element vocabulary are McKinsey’s, applied here rather than reinvented. The departure is granularity. In the twelve-element system, the McKinsey talent element sits at the level of the whole organization’s approach to its people, which is correct but too coarse to build a transformation workforce plan from. The plan is built on roles, and roles resolve into tasks, and tasks demand skills. This article takes that single element down through that chain to where readiness becomes concrete. It also resolves a vocabulary hazard: McKinsey uses “talent” for the people element and “skills” as its outcome, looser than the precise senses fixed earlier.

How much of the current operating model to map is a fair question, because reading current-state processes, roles, and tasks in full is part of the strategy-development phase, which our July argument identified as the first thing compressed under time pressure. The answer is that the mapping is not enterprise-wide. It is bounded to the workstreams the prioritized initiatives reach. The initiatives, which come out of the diagnosis and are anchored to organizational objectives rather than to a technology, define the scope: a narrow transformation touches few workstreams and warrants a light reading, an enterprise-wide one touches many and warrants a deep one. Within that scope, begin with the workstreams whose experimentation and scaling are least complex and move toward the more complex as understanding accumulates. Progress becomes visible early, and the readiness gap is read first in the workstreams already being experimented with and scaled, so the pace forecast that later sections depend on is built on results rather than assumption.

One kind of value surfaces in this reading that documentation never captures. Much of how the current operating model works is undocumented, living in the current workforce as knowledge of how the process really runs, which exceptions are routine, and where the written procedure and the real one diverge. This is the tacit knowledge new hires cannot bring, and a second reason, beyond cost and beyond the need for the current workforce to evolve, that a transformation cannot simply hire its target state into existence. Reading the current operating model is partly an act of surfacing that knowledge before it is lost in the redesign, or lost with the people who hold it.

Define the Target Operating Model and Read the Delta

The current operating model tells how the work is done today. The target operating model is how that work will be done once the transformation has landed. It is the same McKinsey twelve-element system read forward: the structure, processes, technology, behaviors, and talent the strategy requires rather than the ones in place now. New tools and platforms may appear, but that is not what makes it the target. What makes it the target is that it specifies a different arrangement of the work, and therefore a different set of roles, tasks, and skills, than the organization holds today.

A target operating model is not handed down finished. It is realized through the transformation work, and that work is a scope of activities, discovery, assessment, data and infrastructure analysis, workforce planning, operating-model design, and experimentation among them. Experimentation is one activity within that scope, the one that pressure-tests and validates the design, not the whole of it. The target operating model is the implemented and adopted result of that work, which is why readiness for the operating model is inseparable from readiness to do the work that produces it.

That definition misleads if left there, because it implies the target model is known in full before the work begins. It is not. The target model for a specific prioritized initiative starts as a draft, derived from the outcomes and benefits that initiative is meant to produce. Drafting the target model is a joint effort: the transformation strategy team together with the teams whose work the initiative changes propose how the process should operate to deliver the benefit. That draft is a hypothesis, and experimentation is how it is tested. Running the initiative’s technology in a bounded scope and having participants work the process as the draft defines it pressure-tests whether it delivers the intended outcome, confirms what holds, and corrects what does not. What the organization eventually scales is the draft as corrected by that test. The target model is not discovered by experimentation; it is proposed from the benefit and hardened by it.

The experiment is only valid if participants work the roles as the draft operating model defines them. If they keep to the old process and merely use a new tool, the test measures the wrong thing and returns a false verdict on a sound draft or a flawed one. They are not yet fully evolved into the new roles; during experimentation they are performing them in earnest to test the draft, with full evolution coming once the evidence is in and the model is ready to scale. Two streams therefore run in parallel: the transformation work that hardens the draft model, and the workforce evolving to run it. Neither alone lets an organization scale. A proven model with no one ready to run it does not scale; a ready workforce with an unproven model has nothing to adopt.

A further constraint shapes pace from the first experiment, and it has nothing to do with skill. The people who run the experiments and evolve into the target roles are largely the same people who run daily operations. Their time is contested, because the business still has to run while it is being changed. This is the difference between the two faces of readiness. A perfectly capable workforce still paces slowly if its capacity is consumed by keeping the business running, and experimentation feels this immediately, because working the draft roles pulls exactly the experienced operators the line can least spare. How the workforce plan provides for both capability and capacity at once is the subject of a later section.

Reading the difference between current and target means pushing the change down a chain from role to task to skill: a change to the operating model changes roles, a changed role changes its tasks, and changed tasks demand different skills. Role progression, not replacement, is the usual shape of the change, though a role can be eliminated when technology fully absorbs it and the tacit knowledge it held is preserved rather than lost. The chain itself, and how talent sits at its head, is the subject of the next section. What matters here is the result: for any evolved role, the readiness question is the distance between the skills it held and the skills it now demands.

Differencing the two models at the task level sorts the required skills into two kinds. The first are needed to carry out the transformation work itself, the discovery, analysis, design, and experimentation that move the organization from current to target; these are transformation-participation skills, in heaviest demand while the change is underway. The second are the skills the target roles will require once the transformation has landed; these are role-evolution skills, durable, defining the workforce the organization must sustain afterward. Both are part of the readiness requirement, and reading the delta at the task level is what makes them separable.

Not every skill carries equal weight. The critical skills are the ones tied to the objectives the initiatives were anchored to, the skills the transformation cannot proceed without, and they are the ones a plan closes first, distinct from the skills an organization would merely like its workforce to have. The critical skill is the one whose absence would stall a benefit that someone owns.

Talent and Skills, and the Discipline of Telling Them Apart

Talent and skill are not two words for the same thing, and they are not rivals. Talent is innate aptitude, the capacity a person brings to a role, largely fixed on a transformation’s timeline; you identify it and select for it. Skill is the applied capability a task demands, and unlike talent it is built. Talent is the substrate; skill is what grows on it. The right aptitude lets the required skills develop at a workable speed, and the wrong aptitude does not stop skill-building but slows it, sometimes past the point the transformation’s pace can absorb. This is why talent, though not the thing being built, does not drop out of the pace question: it is the multiplier on how fast skills can be built.

The chain makes the relationship concrete. The operating-model change enters at the role level and propagates downward: a changed role changes its tasks, and changed tasks demand different skills. Talent sits at the head as the aptitude a person brings, the one link that is selected rather than built, while the skill at the foot of the chain is the buildable layer where the readiness gap sits.

The discipline that follows is a division of decisions. For each role the target model requires, decide first what aptitude it demands and select for it, by placing people whose aptitude fits or acquiring it; then decide what critical skills its evolved tasks require and build them. Select for talent, build for skill, and build the critical skills first. Reverse the order, building skills before establishing whether the aptitude beneath them fits, and an organization produces trained people who still cannot perform the evolved role, then mistakes a selection failure for a training one.

The Workforce Plan, Where Demand and Supply Become a Pace

If the operating model sizes the readiness requirement, the transformation workforce plan is where that requirement becomes a plan someone can execute. And here the discipline is rare. McKinsey’s HR Monitor 2026 finds that only about 11 percent of organizations plan their workforce on a long-term, capability-based footing; most remain fixed on near-term headcount. Headcount planning answers how many bodies the budget holds. Workforce planning answers which capabilities the strategy requires, at what time, in which roles. In our definition, a modern transformation workforce plan works over an 18-to-36-month horizon, runs several scenarios, integrates skills data, and is refreshed on a regular cadence rather than set once a year.

The plan is not built by HR alone, and it is not built once. It is the reconciliation of two readings that must be produced together. The transformation strategy team brings the demand: the roles the target operating model implies and the critical skills those roles require, at each initiative’s pace. The CHRO brings the supply: what the current workforce holds, how fast it can evolve, and how much of its capacity daily operations already claim. Where demand meets supply, the plan forecasts the pace the transformation can actually sustain, initiative by initiative, and that forecast is only credible if both readings are honest. A demand model that ignores capacity will promise a pace the workforce cannot hold; a supply model that ignores the operating model will train for skills the target roles never needed.

This is why the CHRO is not a downstream recipient of the strategy but an active stakeholder in the transformation’s strategic readiness, working alongside the executive and strategy teams as the plan is built rather than after. Korn Ferry’s research on strategic workforce planning makes the same point from the other side: planning delivers its best results when business leaders are active participants and HR guides the process, not when HR builds it alone. The CHRO owns the workforce plan as an artifact and is accountable for its execution. But ownership of the plan is not ownership of the benefit. An executed workforce plan is not a realized outcome, any more than a launched pilot is. The plan closes the readiness gap; the benefit owner, whoever can trace the outcome to an objective, remains accountable for the outcome the closed gap was meant to enable. Keeping those two accountabilities distinct is what stops a transformation from reporting a completed plan as though it were a delivered result.

Why the Real Pace Runs Slower Than the Forecast

Even an honest forecast overstates the pace, because two forces drain the capacity the plan assumed. The first is technical debt. The senior people most needed to design the target model, run the experiments, and mentor the evolving workforce are the same people holding the existing systems together. McKinsey’s work on technical debt describes one board that added a standing capacity review of how much of its key people’s time was going to debt removal versus new work, precisely because the contest for those hours is invisible until someone counts it. Every hour the best people spend keeping the business running is an hour not spent building readiness, and the workforce plan that ignored this will always forecast a pace the organization cannot reach.

The second force is change fatigue, which caps how much readiness a workforce can absorb at once. The load has risen sharply. Gartner research reported in the Harvard Business Review found that the average employee faced ten planned enterprise changes in 2022, up from two in 2016, and that willingness to support enterprise change fell to 43 percent from 74 percent over the same period. Readiness is finite and depletable, and a plan that schedules more change than the workforce can hold will see its pace slip regardless of how well the skills were scoped. Underlying both forces is the same misallocation: transformation budgets tend to flow overwhelmingly to technology and only marginally to building the human capability the transformation actually runs on.

This is not a marginal effect. BearingPoint’s Target Operating Model study names it directly as a “Talent Paradox”: while a significant share of C-level leaders identify talent and skills gaps as a major obstacle to their operating model, more than half do not prioritize the initiatives needed to close them. Operating models, in other words, are being redesigned faster than workforces are being prepared to run them. That is the readiness gap this article has described, observed in the field, and it is precisely the gap that a scoped, owned, honestly paced workforce plan exists to close.

Energy makes the whole argument concrete. As an oil and gas operation moves to remote operations centers and data-driven decisions, a control-room operator’s role does not disappear; it changes what it requires, from reading gauges to interpreting a data stream. The technology deploys quickly. The readiness does not, because the operator must evolve while the asset keeps running, and much of what makes that operator effective is undocumented knowledge of the plant that no new hire arrives with. EY research has found that nearly half of oil and gas companies lack the skills within their current workforce to realize the return on their technology investments. In an industry where roughly half the workforce is over 45 and a wave of retirements is underway, that undocumented knowledge is leaving on a fixed timeline, which makes the capacity to evolve people, not the capability to deploy technology, the true pace of the transformation.

The organizations that accelerate most successfully are not the ones that deployed the fastest. They are the ones that scoped what their transformation and its target operating model would demand of their people, made someone accountable for closing it, and paced the change to the speed their workforce could actually sustain. Workforce readiness is not the constraint that slows a transformation down. It is the dimension that tells a transformation how fast it can honestly go.