According to our State of Skills-Based Workresearch, 90% of organizations now use skills data in HR decisions.
That number suggests that skills-based work has become part of how companies manage talent. Skills appear in workforce planning, learning programs, internal mobility platforms, compensation discussions, and leadership dashboards.
However, the outcome data shows that adoption has not translated evenly into business results.
Those numbers point to a specific problem: Many organizations have added skills data to HR processes without changing the decisions those processes produce.
A company can have a skills inventory and still rely on external hiring as the default. It can launch a talent marketplace and still let internal moves get slowed by approvals, backfill concerns, and manager resistance. It can include skills in pay reviews and still allow each manager to apply the data differently. It can monitor skills gaps and still leave employees unsure which skills will lead to real opportunities.
This is the skills activity-outcome gap.
Organizations are doing more skills-based work, but many are still running it through the same operating model they had before. The skills data has improved visibility. It has not always changed who gets hired, who gets developed, who gets paid, or who gets moved.
According to our internal research:
These are meaningful signs of adoption. They show that skills-based work has moved beyond early pilots and isolated HR experiments. Most organizations now understand that job titles alone are too limited for workforce planning, mobility, learning, and retention.
The maturity data reinforces that point. Twenty-five percent of organizations are piloting skills-based work. Thirty percent are operational in some functions. Twenty-five percent have scaled skills-based work across the enterprise. Another 10% describe their skills ecosystem as future-ready, with skills embedded as core workforce infrastructure.
The market has moved, but the first layer of movement is also the easiest one to achieve.
It is easier to build a skills inventory than to change how hiring managers make decisions. It is easier to launch a talent marketplace than to change how managers release talent from their teams. It is easier to add skills to a compensation conversation than to create a formal pay policy that managers must follow. It is easier to monitor skills gaps than to redesign learning, mobility, and workforce planning around closing them.
That is why adoption numbers can rise before outcomes change. The organization can add skills to the surface of the process while the process underneath continues to behave the same way.
Internal hiring is one of the clearest places to see the difference between skills visibility and skills impact.
If organizations have better visibility into employee skills, they should be able to identify more internal candidates for open roles. They should be able to see adjacent skills, transferable experience, and employees who could grow into roles with the right support. Over time, that visibility should reduce the need to search externally for every capability gap.
Yet only 25% of organizations fill more than half of their open roles internally.
That does not mean skills data has no value. It means visibility is only one part of internal mobility. The harder work starts after the match is made.
For an internal move to happen, several decisions have to line up. A hiring manager has to consider internal candidates before defaulting to the external market. The employee’s current manager has to release talent, even when losing that person creates short-term pressure. HR has to manage the transition. Finance may need to approve a backfill. The receiving team has to trust internal capability, even when an external candidate appears to have more direct experience.
A talent marketplace can support those decisions, but it cannot make them alone.
External hiring remains the easier path in many companies because the process is familiar. Recruiters know what to do. Hiring managers know how to open a requisition. Agencies, job boards, applicant tracking systems, interview loops, and approval workflows are already built around bringing in external candidates.
Internal mobility often has less operating support. The company may know who has the right skills, but the move still depends on manager behavior, budget approval, backfill planning, and timing. Each step creates friction. When the internal process feels slower or more complicated, managers return to the path they already know.
This is how a company can believe in promoting from within and still fill most roles externally. The belief has changed faster than the workflow.
Compensation is another place where skills activity can look stronger than skills impact.
Seventy-four percent of organizations say they connect skills to compensation. On the surface, that sounds like a major shift in how companies reward employees. It suggests pay is becoming more closely tied to capability, proficiency, and the skills the business needs most.
The implementation data makes the picture more complicated. Only 39% of organizations have documented policies for how skills affect pay. Another 35% handle the connection case by case during normal review cycles.
Both groups can accurately say skills influence compensation. But employees experience those two models very differently.
In a documented model, the organization defines which skills matter, how proficiency is assessed, which skills command premiums, and how managers should apply the policy. The rules do not remove every judgment call, but they reduce the chance that two managers apply the same skills data in completely different ways.
In a case-by-case model, skills may still be discussed. A manager may reference an employee’s skill profile during a review. A compensation partner may consider proficiency when making a recommendation. A business leader may approve an exception for a scarce capability.
Those actions may be useful, but they do not create a consistent system. One manager may treat a skill as central to pay progression. Another may treat the same skill as useful background information. One employee may see a clear connection between capability and reward. Another may build similar skills and see no change.
Over time, that inconsistency weakens trust. Employees are less likely to believe skills matter if the organization cannot explain how skills influence pay decisions.
The issue is not whether skills appear in the compensation conversation. The issue is whether skills have enough structure to produce fair, repeatable decisions.
The compensation data is part of a wider pattern.
Fifty-three percent of organizations track skills-related outcomes with defined metrics, while 40% track informally. Eighty-three percent monitor skills obsolescence, but many still rely on manager observation rather than stronger data and analytics.
Informal approaches are common because they are easier to introduce. They require less upfront policy work. They create less resistance from managers. They allow HR teams to start using skills data without redesigning the processes around it.
But informal approaches also limit the impact of skills-based work.
If outcome tracking is informal, leaders may see activity without knowing whether the activity improved retention, internal hiring, productivity, or workforce readiness. If skills monitoring depends heavily on manager observation, the organization may miss gaps that are emerging across teams or functions. If compensation depends on case-by-case interpretation, employees may not understand how skill development changes their future.
This is where the activity-outcome gap becomes structural. The organization is doing the work, but the work is not governed tightly enough to change outcomes at scale.
Skills-based work needs room for judgment because talent decisions are complex. But it also needs enough formal structure to make decisions consistent across managers, functions, and business units. Without that structure, skills data becomes another input people can choose to use differently.
The ownership data helps explain why informal practices persist.
Skills strategy is usually spread across several parts of the organization. HR generalists and centers of excellence own it in 29% of organizations. People analytics and workforce planning own it in 28%. Business units own it in 17%. Learning and development owns it in 16%. Shared ownership models account for the rest.
That distribution makes sense because skills-based work touches almost every part of the talent system. Workforce planning needs skills data to understand future capability needs. Learning and development needs it to shape programs. Talent acquisition needs it to rethink role requirements. HR business partners need it to advise managers. Business leaders need it to make better workforce decisions.
The challenge is that involvement can create the appearance of ownership without creating accountability.
Each function can move its part forward. People analytics can build dashboards. Learning and development can create pathways. Talent acquisition can adjust job requirements. HR business partners can coach managers. Business units can name priority skills.
Those efforts matter, but they do not automatically add up to a changed talent system.
If the goal is to increase internal hiring, someone has to own the full path from identifying internal candidates to placing them in roles. If the goal is to connect skills to pay, someone has to own the policy, the manager guidance, the employee communication, and the audit process. If the goal is to reduce skills obsolescence risk, someone has to connect workforce planning, learning, mobility, and redeployment.
When ownership is too fragmented, each team can point to progress while the outcome stays flat. The dashboard improves. The program launches. The policy gets discussed. But the decision flow remains unclear.
That is why skills strategy needs an accountable owner or a governance model with real authority. The work can remain cross-functional, but the outcomes cannot belong to everyone in the abstract.
The need to close this gap is becoming more urgent because skills are changing quickly.
More than half of respondents say critical skills become obsolete within three years. Fifteen percent say the window is under one year. This pressure is not limited to technology roles. Healthcare, manufacturing, financial services, energy, and other sectors are also seeing shorter skill cycles.
When skills changed more slowly, organizations could respond with slower systems. They could hire externally when a gap appeared. They could update learning programs periodically. They could depend on managers to identify emerging needs during normal planning cycles.
Shorter skill cycles make that approach harder to sustain.
If a critical skill may lose value within three years, the organization cannot rely only on external hiring to close every gap. By the time the role is approved, sourced, filled, and ramped, the business need may already have shifted. The company needs a faster way to identify adjacent skills internally, develop employees into priority areas, and move talent before gaps become urgent.
That requires a stronger connection between skills data and action.
Monitoring skills obsolescence is useful only if the organization can respond. Employees need to know which skills are becoming more important, which opportunities those skills open, and how the company will support them in making the transition.
The upskilling data shows that many organizations still have work to do. Only 34% report strong participation in upskilling. Thirty-one percent say fewer than one in four employees actively engage in development.
Low participation is often treated as a learning problem, but it is also a credibility problem. Employees are more likely to build skills when they believe the effort will lead to opportunity. If development sits apart from roles, projects, pay, and mobility, employees may see it as extra work with no clear return.
Skills become valuable to employees when they change what the employee can do next. Without that connection, even a strong learning catalog can struggle to create sustained participation.
The organizations producing stronger outcomes are not simply collecting more skills data. They are changing what skills data is allowed to influence.
They formalize practices that other organizations leave informal. In compensation, that means documented rules instead of case-by-case interpretation. In outcome tracking, it means defined metrics instead of loose reporting. In skills monitoring, it means evidence the organization can review and act on, not only manager perception.
They clarify ownership. Skills-based work can involve many functions, but the outcome needs a clear owner. Someone has to be accountable for whether skills data improves internal hiring, development participation, redeployment, retention, and workforce readiness.
They make development credible. A course catalog can help employees learn, but it does not prove that learning will matter. Employees need visible career pathways, internal roles, gigs, projects, manager support, and rewards that show skills development is connected to movement.
They reduce friction around internal mobility. If an internal match takes months to clear approvals while an external recruiter can move faster, managers will keep choosing the easier path. Companies that improve internal hiring make internal movement operationally competitive with external hiring.
Lennox shows what that can look like. The company tracked 4,800 internal moves and found that each move added an average of five months of tenure. Across those moves, that represented more than 2,000 years of institutional knowledge retained inside the organization.
The lesson is practical. Skills data produces outcomes when it changes the next decision. It has to affect who managers consider, how employees move, how pay is determined, and how development connects to opportunity.
The right next step is not the same for every organization. It depends on where skills activity is already happening and where outcomes remain weak.
If internal hiring is the gap, start by mapping the full internal movement process. Look at what happens after an employee is matched to a role. Identify where approvals slow down, where managers block movement, where backfill planning creates friction, and where external hiring becomes easier than moving someone internally. The goal is to make the internal path operationally realistic, not just visible.
If compensation is the gap, look at how skills influence pay today. If the process depends mainly on manager interpretation, the next step is to document which skills matter, how proficiency is assessed, and how managers should apply that information. Employees do not need every pay decision to be automatic, but they do need the logic to be clear enough to trust.
If upskilling participation is the gap, examine whether development is connected to opportunity. Employees need to see which roles, projects, gigs, or pay outcomes are linked to the skills they are being asked to build. If the connection is weak, participation will likely remain weak too.
If skills obsolescence is the gap, look at whether monitoring leads to action. A dashboard that shows skills are aging does not solve the problem by itself. The organization needs a response plan that connects workforce planning, learning, mobility, and redeployment.
In each case, the work is less about adding another skills initiative and more about changing the decision pathway around the initiative already in place.
The 2026 data shows that most organizations have started the skills-based work journey. They have data, dashboards, programs, and leadership attention. That progress matters because it gives HR teams a better view of workforce capability than they had before.
But better visibility also creates a higher standard.
Once the organization can see skills more clearly, employees and leaders will expect that visibility to change something. They will expect better internal opportunities, clearer development paths, more consistent pay decisions, and faster responses to emerging skill gaps.
The organizations that meet that standard will be the ones that connect skills data to the decisions that shape workforce outcomes. They will define how skills affect hiring, mobility, compensation, development, and workforce planning. They will assign ownership. They will reduce friction. They will make the connection between capability and opportunity visible enough for employees to believe in it.
The organizations that do not make those changes may still report high adoption. They may still have dashboards, marketplaces, taxonomies, and skills profiles. But the same old operating model will continue to decide what happens next.
Skills-based work has moved far enough that adoption alone is no longer the useful measure. The more important question is whether skills data has enough authority to change decisions.
Until it does, organizations will continue to see the same gap: more skills activity, but fewer skills-based outcomes than the investment was meant to produce.