When did a tight labor market last shrink inequality this fast, with the 90 over 10 wage gap narrowing by 8.6 log points between 2019 and mid 2023 and real hourly pay at the 10th percentile up 7.8 percent while the median and 90th percentiles fell 6 to 8 percent, mostly because workers switched to better paying employers as quits became far more sensitive to pay? See the NBER working paper for detail. This article takes a clear stance. Wage compression can be healthy at the bottom of the distribution when driven by competition, but unmanaged internal compression inside organizations erodes morale, retention, and performance. You need to detect it early, fix it systematically, and build pay architectures that keep equity and market alignment in balance.
Understanding Wage Compression
Start with the evidence. A recent systematic review and a quasi experimental study concluded that raising wage floors reduces inequality and in work poverty. Spain’s 2019 21.3 percent real minimum wage increase measurably lifted lower earners and confirmed the inverse relationship between minimum wages and inequality across the literature. See the systematic review and Spanish natural experiment for the synthesis and design. At the macro level, this is one engine of wage compression. It narrows gaps by lifting the bottom.
The post COVID period reveals a second engine. Labor market competition intensified. The NBER analysis cited above used monthly CPS microdata, linked with job openings and local unemployment series, to show that low wage workers, especially young and non college workers, became far more responsive to tight local labor markets. In plain terms, wages at the bottom became more sensitive to hiring conditions, and workers were more willing to leave for better pay. Employers lost wage setting power, and pay rose most where it was lowest. The same analysis reported a sharp narrowing of racial wage gaps, with the white to Black differential shrinking by roughly 8 log points. That pattern shows how compression can improve equity when competitive reallocation drives it.
Internal pay systems can also compress wages unintentionally. A multi year case study of a unionized U.S. university found that flat dollar promotion raises equalized salaries by rank. That practice caused faculty to cluster at minimums and eroded seniority and merit differentiation. The case documented how promotion increases had been only one quarter of the gap between rank minimums, and how targeted structural fixes reversed the pattern at modest ongoing cost. For design specifics, see the university case and literature review.
Compression’s effects on organizations are not one note. A longitudinal study of more than 10,000 Swedish establishments found that more compressed wages were associated with higher job reallocation in manufacturing. When wages cannot adjust downward, firms adjust through hiring and separations instead. That estimate, roughly a 10 to 12 percent shift in the job reallocation rate for a one standard deviation change in dispersion, supports the classic theory that rigid, compressed wages raise employment volatility. See the industry level panel analysis.
Yet the human side matters most. Experimental evidence shows that relative pay affects morale, not only absolute pay. In a month long randomized controlled trial with 378 factory workers organized in three person units, introducing pay disparity reduced output by nearly a quarter of a standard deviation and attendance by 12 percent. Workers effectively gave up about 9 percent of earnings to avoid unequal teams. The negative effects vanished only when performance differences were extremely clear and visible. See the field experiment. For HR, the message is direct. If differences are not explainable and observable, perceived unfairness will sap performance. That is the risk side of the opposite of wage compression, which is unchecked dispersion.
Identifying Wage Compression in Your Organization
Treat diagnosis as a recurring, data driven process. Start by assembling a clean dataset at the employee level with job family, grade, base pay, target total compensation, location, compa ratio, time in role, time in grade, performance rating, and hire date. Then run three simple diagnostics.
- Compression ratio. For each role or band, calculate average pay for recent new hires and compare it with average pay for incumbents with three to five years in role. A basic rule is new hire average divided by incumbent average. A ratio above 0.95 signals emerging wage compression. Above 1.00 indicates inversion. Use filters by location, shift, and scarce skills so you detect pockets, not only averages.
- Pay progression slope. Analyze whether base pay reliably increases with time in role, time in grade, and performance. If pay growth barely increases or even declines as time in grade rises, progression has flattened. That pattern often reflects across the board raises that only keep pace with range minimums or flat dollar promotion policies. The university case referenced earlier used a pay versus tenure and merit analysis to pinpoint faculty whose pay fell below what their merit, tenure, and market would predict. That analysis then guided targeted adjustments.
- Internal dispersion and equity. Within each pay band, review how spread out pay is relative to the band midpoint. When internal dispersion shrinks while external market midpoints rise, incumbents get trapped against the floor. Track compa ratio distributions by cohort. If new hires cluster at or above 1.00 while tenured employees cluster at 0.85 to 0.90, you are observing wage compression in real time.
Benchmarking matters. Where possible, anchor to a consistent market source and schedule, for example annual CUPA or industry surveys, and normalize for role scope and location. The university case moved to formula based initial salaries tied to market medians and peer pay to reduce negotiation bias and prevent reintroducing compression through inconsistent offers.
Finally, collect employee input to map perceived fairness. Use pulse items tied to distributive justice, I understand how my pay compares to the market, procedural justice, I understand how pay is set here, and informational justice, My manager explains pay decisions clearly. Combine that with behavioral indicators such as voluntary quits among under market cohorts, counteroffer frequency, and acceptance rates. The competitive labor market evidence shows that when alternatives are abundant, low paid employees become more responsive to outside offers. Inside your company, rising quit rates among the lowest compa ratios are the canary for wage compression.
Addressing Wage Compression
Fix structure first. The university case shows what works. Switch promotion raises from flat dollar amounts to a consistent percentage of base pay so higher paid individuals maintain their relative position. Decouple cost of living adjustments from increases in range minimums so seasoned employees can move away from the floor. Formalize a standing inversion committee with clear criteria and formulas to correct cases where newly promoted or newly hired employees surpass veterans. In that case, promotion raises increased substantially and an inversion process adjusted a small number of salaries each year at modest budget cost. That outcome is proof that structural changes paired with targeted fixes are sustainable.
Next, use targeted raises to realign internal equity without breaking the budget. A practical method is a Compensation Equity and Performance Matrix that ties raise percentages to both compa ratio quartile and performance rating. The design makes your strategy real. The largest percentage goes to high performers who are furthest below market, while you still reward high performers who are at or above market with smaller increments. An implementation study showed how this approach reduced a 14.5 percent pay spread among same rank faculty to 11.3 percent in a single cycle while staying within a fixed pool. See the implementation study for the grid logic. Operationally, build the matrix, model total cost by headcount per cell, adjust percentages until the total equals your budget, and then simulate impacts on compa ratios and pay gaps before launch.
Communication is non negotiable. The field experiment on pay inequality found that negative productivity and attendance effects disappeared only when the reasons for pay differences were extremely clear and visible. Use that insight. When you make compression oriented adjustments, publish the rules of the road. Explain how you choose market medians, how compa ratios translate into raises, how performance interacts with equity, and how exceptions are governed. Equip managers with talk tracks and comparative examples. Employees accept differential outcomes far more readily when the rationale is consistent and clear.
Avoid the pitfalls that cause wage compression to recur. Flat dollar promotion increases, synchronized increases to range minimums and across the board raises, and loyalty taxes on long tenured staff all push salaries toward the floor and invite resignations among your most mobile employees. The university review highlighted how these dynamics accumulate over time. It also acknowledged limits. Formulaic initial salaries can hamper the ability to match outsized external offers for stars. Build exception channels with governance to manage that trade off.
Advanced Strategies for Combating Wage Compression
Develop a robust compensation strategy that anticipates external shocks. The inequality literature across Central Eastern Europe shows how policy choices around taxes and transfers shape distributional outcomes over decades, even among countries that started from similar positions. By synthesizing 152 publications, a comprehensive review showed that divergence in inequality largely reflected the strength of government redistribution and labor market policies across countries such as Poland, Hungary, and Bulgaria. See the systematic literature review. Translate this macro lesson internally. Make redistribution choices explicit in your pay architecture. Decide in advance what share of your salary budget addresses market drift, performance differentiation, and compression remediation. Plan scenarios for minimum wage changes, inflation zigzags, and talent shortages. Hard code response rules into your annual cycle so you do not inadvertently compress wages with blanket increases.
Leverage automation and analytics to keep wage compression visible. Build dashboards that flag when offer pay for a role exceeds the average pay of incumbents with two or more years in role by more than, for example, 5 percent. Set automated alerts when compa ratio distributions by tenure band converge. Run quarterly reviews of how pay changes with tenure, grade, and performance to catch flattening progression early. Track early warning behavior signals. Watch for rising quit rates among below market cohorts, spikes in declined counteroffers, and growing gaps between posted range midpoints and actual accepted offers. While the national evidence measured quit sensitivity using industry wage premia, you can mimic the spirit by monitoring how sensitive your resignations are to external offer gaps. Set thresholds that trigger targeted adjustments before pressure turns into avoidable attrition.
Foster a culture of equity and fairness that prevents wage compression from becoming a trust issue. Publish pay bands and progression criteria, make promotion timing and pay consequences predictable, and invest in manager capability to explain both the what and the why of pay decisions. Where you differentiate, make the justification transparent and observable. Again, the experimental evidence shows that clarity about performance differences neutralizes the morale hit of pay differences. This is culture as compression management.
Finally, align to external wage floors proactively. When legal minimums shift, do not let your internal architecture invert. The international evidence cited earlier shows that minimum wage hikes compress the lower tail with spillovers to adjacent groups. Translate that into action. Adjust entry level ranges and re slot affected bands. Allocate a dedicated pool for incumbent adjustments so that new hire rates do not leapfrog internal peers. Codify the sequence in your annual compensation calendar.
Wage compression will ebb and flow with macro conditions. The past few years proved that a tighter labor market can reduce inequality rapidly by intensifying competition for lower paid workers. For employers, the playbook is clear. Measure compression with the right metrics, fix it with structural levers and targeted raises, and prevent its return with transparent rules, disciplined budgeting, and always on analytics. Do this well and you will capture the upside, more equitable pay, stronger retention of experienced talent, and better allocation of people to roles, while you avoid the performance and morale costs that come with unmanaged pay structures.
