What if job titles disappeared? The Reality of Paying for Skills

The modern workplace is built on a deceptively simple foundation: the job title.

“Senior Software Engineer.” “Vice President of Marketing.” “Recruiting Manager.” “Data Analyst.”

Titles do more than describe work. They anchor compensation, signal status, shape professional identity, and give organizations a shared map for who does what.

But what if that map disappeared?

What if organizations stopped paying people based on role labels and started paying them based on the skills they could actually demonstrate?

This is no longer a fringe thought experiment. Skills-based compensation sits at the center of a live debate in human resources, talent strategy, and labor economics. The idea is genuinely transformative. The reality is more complicated.

The case for paying people based on skills is strong. The risks are just as real. Whether the model works depends less on the philosophy and more on how the transition is designed, governed, measured, and sustained.

The history of paying for what people know

Paying people for skills instead of titles is not new.

In manufacturing and the skilled trades, skill-based pay has existed for decades. Workers are rewarded as they master additional competencies, such as operating specialized machinery, passing certification tests, or cross-training across production lines. Some practitioner literature and case examples suggest skill-based pay can improve flexibility and cross-training in manufacturing, although results depend heavily on implementation. Research on the success and survival of skill-based pay plans found that design features, support variables, and supervisor support were associated with greater workforce flexibility and plan survival, especially in manufacturing settings. (See Success and Survival of Skill-Based Pay Plans and Who Uses Skill-Based Pay, and Why.)

The model works best when skills are tangible and testable. A welder either passes a certification test or does not. A machine operator either demonstrates the ability to run the equipment safely or does not. Measurement is still imperfect, but it is concrete.

In the knowledge economy, the experiments have been more ambitious and more turbulent.

Valve Corporation, the video game developer behind Steam, is famous for its flat structure and lack of formal managers. Employees self-select into projects, and reporting confirms that peer stack ranking has influenced pay. However, claims about how well the model works rely heavily on former employee accounts and press reporting, not formal organizational research. Some former employees have criticized the structure. One described Valve as having “hidden layers of powerful management,” according to Wired.

Zappos pursued an even more radical path. The online retailer moved toward Holacracy and eliminating traditional job titles during its 2014 to 2015 transition. The shift proved disruptive. In March 2015, CEO Tony Hsieh offered severance to employees unwilling to embrace the new model. Ultimately, 18% of the workforce, approximately 260 employees, accepted and left, according to Time.

Spotify’s Squad Model represents a more moderate experiment. Rather than abolishing structure entirely, Spotify de-emphasized hierarchical titles in favor of cross-functional, autonomous squads and tribes. The model was widely celebrated in management circles, but former Spotify employees and outside observers later argued that it was more aspirational than fully implemented. Jeremiah Lee, a former Spotify employee, made that case in Spotify’s Failed #SquadGoals.

My inference from this history is simple: skill-based compensation works best when skills are measurable, the workforce is relatively small, and the organizational culture actively supports the change. The larger and more complex the organization, the harder the transition becomes.

What are we actually paying for?

Labor economists have long debated what wages actually measure.

Human capital theory holds that wages reflect the productive value of an individual’s accumulated knowledge, training, and ability. In principle, that theory supports skill-based pay. If wages should reflect productive capacity, then measuring skills directly is a logical improvement over relying on job titles as proxies.

Signaling theory offers a more skeptical view. It argues that education may function less as proof of productivity and more as a signal of pre-existing ability. Job titles often work the same way. They communicate a bundle of inferred competencies to employers, clients, recruiters, and the external labor market.

That creates a challenge. Eliminating titles destroys an existing signaling system. Unless organizations replace it with something more accurate and trusted, they may create more confusion than fairness.

A substantial body of labor-market research supports the existence of skill premiums, although the size and durability of those premiums vary by skill, occupation, and market. For example, PwC’s 2025 Global AI Jobs Barometer reports that workers with AI skills earned a 56% wage premium in 2024, up from 25% the year before.

That does not mean every skill can be priced cleanly. It means the labor market is already assigning value to specific capabilities, especially when those capabilities are scarce, visible, and tied to business outcomes.

The measurement problem

The hardest part of a title-free compensation system is not philosophical. It is operational.

Before an organization can pay for skills, it has to answer a basic question: what exactly counts as a skill?

Two major frameworks attempt to bring structure to that question.

The Occupational Information Network, better known as O*NET, is maintained by the U.S. Department of Labor and profiles occupations across skills, knowledge, abilities, tasks, work activities, and other worker requirements.

The European Skills, Competences, Qualifications and Occupations framework, or ESCO, is a European Commission classification system for skills, competences, qualifications, and occupations. ESCO is available in 27 ESCO languages and is designed to support a common language for labor markets, education, and training across Europe.

There is also a documented crosswalk between ESCO and O*NET, including a technical report describing the use of machine learning and human validation to connect the two systems.

Micro-credentials represent another promising development. Digital Promise supports competency-based, evidence-based micro-credentials that allow learners to demonstrate evidence of competence in a specific skill. If designed well, these credentials may reduce reliance on standardized testing by incorporating multiple forms of evidence.

But the deeper challenge is tacit knowledge.

Explicit knowledge can be articulated and tested. A programmer either knows Python syntax or does not. An accountant either understands a specific compliance rule or does not.

Tacit knowledge is different. It includes the seasoned leader’s judgment, the experienced negotiator’s read of a room, the recruiter’s instinct for candidate motivation, or the operator’s feel for when a process is about to break. These skills are often highly valuable, but they are difficult and contested to measure.

Any compensation model that rewards only what can be easily tested risks undervaluing the very expertise that makes experienced workers effective.

Equity and the illusion of objectivity

The equity implications of skill-based compensation cut in both directions.

The optimistic case is that skills-based systems can open pathways for people who have been filtered out by traditional credentials. Deloitte reported that many executives believe skills-based decisions around hiring, pay, promotion, succession, and deployment can reduce bias and improve fairness.

Vendors also point to diversity benefits. Beamery cites LinkedIn analysis finding that, in jobs where women are underrepresented, a skills-first approach can increase the proportion of women in candidate pools by 24% more than it would for men.

That is the optimistic case.

The cautionary case is that skill-based systems can still reproduce bias if the underlying definitions of value are biased.

The critical question is not only whether a person has a skill. It is who decides which skills matter, how those skills are valued, and whether historically undervalued work is finally recognized.

Skills associated with work performed predominantly by women, including caregiving, coordination, emotional labor, and interpersonal support, have often been undervalued in labor markets. A skill-based system built on historically biased labor-market data could reproduce or deepen existing inequities unless skill definitions and valuations are audited.

In other words, skills-based pay is not automatically objective. It only becomes fair if the system behind it is transparent, contestable, and actively governed.

The psychology of status

Job titles are not just administrative conveniences. For many workers, they are tied to professional identity, social status, and psychological well-being.

Removing titles does not eliminate hierarchy. It can simply make hierarchy harder to see.

Reputable commentary and case reporting support the risk of hidden power structures in flat organizations. Wired has reported on the “tyranny of flatness,” noting that structureless workplaces can obscure power, accountability, and inclusion problems. Research from the University of Maryland’s Robert H. Smith School of Business also found that job ads promoting flatter hierarchies may attract a lower share of women applicants.

That matters because removing formal titles does not remove status competition. It may simply move status into informal networks, social influence, tenure, charisma, or proximity to power.

There is another issue: career legibility.

Titles provide a shared vocabulary for career progression. They help workers explain who they are, what they do, and where they stand in the market. They also help recruiters, hiring managers, clients, and professional communities interpret experience quickly.

Without titles, workers may struggle to explain their value outside the organization. Internally, the system may feel elegant. Externally, it may create friction.

Technology and the future of work

The practical feasibility of skill-based compensation at scale depends heavily on technological infrastructure.

AI platforms are making skill inference increasingly feasible, but the category should be discussed carefully. ProvenBase is one example of a human-centered, AI-powered sourcing platform that helps recruiters identify skills-first talent, analyze candidate fit, surface pipeline gaps, and reach qualified professionals who may be missed by traditional title-based searches. Its Deep Search capability is positioned around expanding visibility into hard-to-find talent rather than claiming that AI can perfectly measure skill or fairly assign compensation on its own.

These platforms can infer some skills from career histories, profiles, search criteria, and project data, but tacit skill measurement remains difficult. Any claim that AI can fully measure skill, predict contribution, or assign compensation fairly still requires independent validation.

The future-of-work case for skills is strong. The World Economic Forum’s Future of Jobs Report 2025 found that skill gaps are the biggest barrier to business transformation, with 63% of employers identifying them as a major barrier over the 2025 to 2030 period. The same report says employers expect 39% of workers’ core skills to change by 2030, according to the WEF’s skills outlook.

As automation changes the nature of work, the tasks bundled into traditional job titles may shift dramatically. In that scenario, a compensation system anchored to specific, verifiable skills rather than static titles could offer organizations more flexibility.

But flexibility is not the same as fairness. The more compensation depends on skill measurement, the more important it becomes to govern the measurement process.

The verdict

Should job titles disappear?

Not entirely.

The strongest conclusion is not that organizations should abolish titles. It is that organizations should stop treating titles as the primary proxy for contribution.

The most defensible model is hybrid. Organizations should retain some form of role architecture for coordination, accountability, and career legibility, while progressively decoupling compensation from title and anchoring more of it to verified skills.

The goal should not be to eliminate the concept of a role. The goal should be to define roles by the skills and outcomes they require rather than by historical convention.

The organizations most likely to succeed will be those that invest in transparent skill assessment, actively audit for bias, provide equitable access to development, and manage the transition with respect for the workers whose identities and livelihoods are affected.

Skill-based pay is not a magic fix for workplace inequality, talent shortages, or compensation dysfunction.

It is a powerful idea with a hard implementation problem.

And that is exactly why it deserves serious attention.

Author

Jim Stroud is a labor market analyst and Head of Market Strategy and Industry Engagement at ProvenBase. His work focuses on structural hiring gaps, occupational mismatch, and visibility failures in modern talent acquisition systems.