Merit Increase Software: Make Every Pay Raise Count

In 2018 and 2019, researchers working with Sierra Leone’s Ministry of Health and Sanitation tested how promotion rules and expected pay progression affected frontline health workers. The field experiment covered 372 health units and 2,009 community health workers. Ten months later, the published results showed that a more merit-based promotion system raised productivity by 22%, while greater perceived pay progression raised productivity by 23% when promotions were merit-based and reduced it by 27% when they were less merit-based. The lesson from the American Economic Review: Insights study is direct: employees respond to the rules behind pay progression as well as the financial reward.

That matters for employers planning annual raises because salary budgets leave little room for careless allocation. WorldatWork reported that U.S. employers projected a mean salary increase budget of 3.6% for 2027, matching the actual mean of 3.6% in 2026. Its 2026 survey included 1,799 participating organizations and 4,733 submissions from HR and rewards leaders. When the available pool is limited, inconsistent ratings or unclear payout rules can shift real money between employees.

The Sierra Leone case shows why the raise rule matters

The experiment changed the basis for promotion and what workers believed a supervisor earned. Community health workers received SLL 150,000 per month while peer supervisors received SLL 250,000, leaving the lower-level workers earning 40% less. Many workers also had inaccurate beliefs about supervisor pay, so researchers could test what happened when expectations about the value of promotion changed. A bigger perceived reward encouraged effort when workers believed performance would influence promotion.

The same reward could work in the opposite direction when the promotion process appeared less connected to performance. Merit increases are often discussed as percentages, yet employees experience them as decisions about whose work counts and how those decisions are made. A raise formula can be mathematically correct and still produce weak outcomes if the performance inputs feeding it are inconsistent. The quality of the decision process is therefore part of the compensation question.

A merit increase is a policy choice before it becomes a percentage

A merit cycle usually combines manager ratings, salary-range position, budget limits, and approval rules. Those inputs have to produce a payout that an employer can explain across departments. A Compensation Planning Software system can help by keeping salary structures and proposed increases in one place while showing how individual decisions affect the remaining pool. BullseyeEngagement says its system can model salary structures within budget constraints and track merit raises across departments.

Software still depends on the policy behind it. If 2 managers apply the same rating scale differently, automating the payout won’t fix the rating problem. Compensation teams need to define what performance levels mean before converting them into raise percentages and set rules for employees near range limits.

Tighter budgets make inconsistency more expensive

The WorldatWork 2026-2027 Salary Budget Survey findings show why allocation discipline matters now. U.S. organizations projected a 3.6% mean salary increase budget for 2027, the same as the actual mean budget recorded for 2026. WorldatWork also found that 13 of 24 surveyed countries or geographic regions projected slightly lower 2027 budgets than their 2026 actual levels. A limited pool leaves less room to absorb rating inflation or unplanned exceptions.

A Compensation Management Software process should make budget use visible while decisions are still being reviewed. Teams need to see whether one department is consuming a larger share of the pool and whether that difference is supported by performance or pay-position evidence. Catching an unexplained pattern before approval is more useful than finding it after payouts are announced.

Manager discretion needs guardrails and visibility

A separate 2026 NBER field experiment on performance pay studied 131 tehsils in Pakistan’s Punjab Agriculture Extension Department. Researchers compared an objective performance-pay scheme with supervisor-controlled bonuses and another version that added light oversight to supervisor discretion. All 3 approaches increased outreach, but they changed worker behavior through different channels. The result shows that measurement and approval design can influence what employees choose to do.

A Salary Planning Tool is most useful when compensation teams can inspect those decision paths instead of seeing only the final raise. Reviewers should be able to compare recommendations against budget rules and check how ratings translate into proposed pay. That visibility can also expose managers whose recommendations repeatedly sit above or below comparable teams.

Software should make the reasoning behind each raise visible

The practical test for Merit Increase Software is whether reviewers can understand a raise before approving it. Bullseye Engagement says its compensation-planning system can track merit raises, bonus payouts, and one-time awards across departments while supporting configurable approvals and post-cycle compensation statements. It also supports multiple concurrent salary structures for scenario comparison. These functions can help teams connect a recommendation to budget limits and the employee’s place within a pay structure.

A useful review process should answer basic questions without forcing HR to rebuild calculations in a spreadsheet. Reviewers need to know which rating produced the recommendation, how much budget remains, and why an exception applies. Clear answers make it easier to compare similar cases across the organization.

Federal pay projects show why payout logic needs controls

A GAO review of 6 federal pay-for-performance projects found that agencies used different methods to evaluate performance, translate ratings into pay, account for current salary, manage costs, and explain decisions to employees. GAO reviewed projects including NIST, the Department of Commerce, and several Defense Department programs. Its broader finding was that pay-for-performance systems need clear rules around evaluation and payout decisions.

Compensation teams should be able to trace a final increase back to the rating, salary data, approved guideline, and any exception. That record helps explain unusual payouts and gives HR something concrete to review before the next cycle. It also shows where managers repeatedly need exceptions, which may point to a policy problem.

What this case can and cannot tell a private employer

The Sierra Leone experiment doesn’t prove that a corporate merit increase program will raise productivity by 22%. It studied community health workers in a public program, and the incentive involved promotion to a higher-paid supervisory role rather than a standard annual merit raise. The experiment changed promotion rules and workers’ knowledge about pay progression, not the software used to administer compensation. Those differences limit how far employers should carry the numerical findings into another setting.

The study supports a narrower lesson: financial incentives work inside a decision system, and employees can react differently depending on whether that system appears connected to performance. Employers can use that insight when setting rating rules and approval controls. The next step is to test whether the company’s own raise process produces consistent decisions across comparable employees.

Make the next merit cycle easier to defend

A merit cycle should end with evidence that the approved rules were applied consistently. HR should be able to explain how performance affected each increase, where exceptions occurred, and whether the final distribution stayed within the approved pool. Software can make those checks easier, but the policy still determines whether the outputs make sense. Review the decision rules before the next cycle, then choose a system that can apply them consistently.

Frequently asked questions

What is merit increase software?

Merit increase software helps organizations calculate and review performance-based salary increases within an approved budget. It can bring employee pay data, performance inputs, budget limits, and approval steps into one workflow. The main value is giving HR and managers a consistent way to review proposed increases before payroll.

How is a salary planning tool different from a spreadsheet?

A salary planning tool can apply shared rules across departments while tracking budget impact as recommendations change. A spreadsheet can perform the math, but controls become harder to manage when many managers edit separate files or use different assumptions. The useful difference is central visibility into changes and their effect on the pool.

What should HR review before approving merit raises?

HR should check the performance rating, current salary position, applicable merit guideline, and remaining budget before approval. Exceptions should have a recorded reason so reviewers can separate justified cases from inconsistent decisions. HR should also compare similar employees across teams before the cycle closes.

Can compensation software remove bias from merit decisions?

Compensation software can expose patterns and enforce shared rules, but it can’t remove bias from the performance evidence entered by managers. Employers still need clear rating standards and a review process for unusual recommendations. Software helps when it makes differences visible early enough for HR to investigate them.

How should a company judge whether its merit cycle worked?

Start with whether the cycle stayed within budget and whether comparable cases received explainable outcomes. Review exception frequency, rating distributions, and manager-level differences to find areas that need policy changes. Employee questions after the cycle can also show whether the reasoning behind pay decisions was clear enough to understand.

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Donaldbrian is an HR Recruitment professional at BullseyeEngagement, specializing in identifying and attracting top talent to support organizational growth and performance.