Creating an Effective Merit Plan: Optimize Your Salary Increase Budget like a Pro

by Kara Deyermenjian - January 31, 2018
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Most organizations have already recognized the value in paying for performance. Research shows that having a clearly communicated pay-for-performance plan increases external competitiveness, manages employee perceptions of fairness, and motivates higher performance. Standard salary increases not tied to performance tend to not be enough of an incentive to attract, engage, or retain employees – especially in regard to top performers who would be the costliest to lose.

There are two common approaches when it comes to designing a merit system– the first is based on performance rating alone, and the second involves performance rating, as well as an employee’s position within their pay range. When it comes to creating a merit system for your organization, it’s important to understand the implications of both systems and assess which is right for you.

Straight Percent Distribution Approach

One approach in setting up your merit matrix is using a straight percent tactic, in which increases are based on performance alone. A “typical” matrix involves different performance categories with each escalating category receiving one additional percent in pay increase. In the first example below, the increases max out at 4%, while a more effective (“stronger”) matrix involves steeper increases maxing out closer to 10% (as seen in the second example below). If you have the budget to implement, the “stronger” matrix can help you feel more confident you are distributing rewards in such a way that is more impactful.

  • ‘Typical’ merit matrix: the highest percentage increase an employee can receive is 4% (far exceeds expectations), while others receive 0% - 3% depending on their rating. This would require a budget of 2.49% of total payroll to implement.

Example of a typical straight percent merit matrix with increases maxing out at 4%

  • ‘Stronger’ merit matrix example: the highest percentage increase an employee could receive is 10%, while others receive 0-6% depending on their rating. This would require a budget of 4.92% of total payroll to implement.

Example of a stronger straight percent merit matrix with increases maxing out at 10%

Optimizing your Merit Plan: Consider Location in Salary Range in addition to Performance

Utilizing a more complex merit matrix that takes into account compa-ratio (base salary / midpoint of salary range) or range penetration ([base salary - range minimum] / [range maximum - range minimum]) in addition to performance can be an effective strategy to fully optimize your merit increase budget. This approach also ensures you aren’t perpetuating salary range outliers – a problem heavily associated with distributing increases based on performance alone.

Example of a more complex merit matrix where each quartile represents an employee’s position within their pay range

Quartiled merit matrices can be useful, as they allow you to quickly and accurately consider an employee’s performance rating and their location in a salary range when determining merit pay increases, therefore addressing both where an employee's salary falls relative to their pay range, and in relation to external market pay rates.

A merit modeling solution can automate your calculations, model historical or expected distributions, and evaluate and compare the cost of multiple “what-if” scenarios for the distribution of your merit budget. Solutions, such as’s CompAnalyst, allows you to design a matrix that uses your budget to its fullest potential, and is customized specifically for your organization.

Communication: The Final Piece of Your Merit Plan

Once you’ve determined what kind of merit matrix makes the most sense for your organization, it’s important to build a communication plan around your pay policy. Compensation conversations happen regularly whether there is a formal communication policy in place or not, so a proactive communication plan can help employees understand, and be supportive of, how their increases were calculated.

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