A Company Decided to Pay People Fairly. Here’s What Happened Next.

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Dec 18, 2020

I was hired as a compensation analyst as my first job out of college, and my role was to figure out how to pay people. That was more than two decades ago. Since then, I’ve spent years looking at pay and market data — and while I’ve seen the gender pay gap narrow, I have yet to see equity.

Women only make $0.81 for every dollar a man makes. They’re also being predominantly impacted by Covid-19 job losses and pay cuts as female-dominated industries like restaurants and hospitality continue to be hit hardest. This has led to 55% of job loss increases being attributed to women, despite women only making up 49% of the total labor force.

Additionally, workplace pay inequity extends beyond the gender gap. Many people — including possibly you — continue to find themselves in situations where they feel their pay is biased due to lack of ability to negotiate wages, or a discriminatory manager, or a biased recruiter, or general stereotypes about race, sexual identity, etc.

These issues, coupled with a lack of transparency from many organizations on why employees are paid what they are paid, can cause workers to experience frustration that can ultimately impact their performance and office relationships. 

So when I eventually became head of people at my organization, I set out to design a compensation policy with fair pay and transparency as our guiding principles and to ensure that everything was backed by industry data. 

Here’s how I did it.

Beginning the Process

Our first step in creating fair, equitable, and competitive wages was to break down every job role at the company, including the function, scale and scope of work, and day-to-day activities. From there, we created buckets to sort different job types, including accounting or financial forecasting, software development or product management, recruiting or people operations. We also sorted each job type by years of experience.  

From there, we invested in access to credible market data based on market, industry, and size. Because companies have to participate in the benchmark survey to be able to purchase and access the survey data, we knew we were getting accurate, verified information we could rely on. For our company in particular, we focused on data around what similar companies in San Francisco and Boston paid their employees. Our goal was to pay as well or better than other private tech or fintech companies to remain competitive.

Planning Pay

Identifying and creating benchmarks is crucial in effective compensation planning. There are many factors that businesses need to evaluate to determine how to fairly pay their employees. 

For example, average salaries vary greatly from major cities such as San Francisco or New York vs. smaller cities such as Ann Arbor, Mich., or Fort Pierce, Fla. You want to make sure you’re benchmarking against a business — preferably several businesses — similar to yours, in your market, with similar staffing and operational needs, to feel confident you’re using the right data.

As we focused first and foremost on creating fair pay for our employees and being transparent about our philosophy, the next step was to determine how competitively we wanted to pay our staff vs. the market average. We considered three options:

  • Option 1: Pay in the lower quartile on base salaries and offer variable annual performance compensation (bonus programs) for individual and company performance.
  • Option 2: Pay at the median on salaries and consider offering a bonus or potentially no bonus.
  • Option 3: Pay in the upper quartile on salaries, eschewing a bonus program, believing that if we hired fantastic talent, set actionable priorities and expectations, and gave regular feedback, we would not need to hold back a portion of our employees’ pay as an incentive to do great work.

We ultimately decided on Option 3 and needed to make sure our base salaries were high enough to compete for talent in San Francisco and Boston (where our company is located). So we looked at data specific to these two areas.

Benefits of a Data-Backed Approach

Because our pay levels are driven directly by data, employees joining the company don’t have to worry about negotiating their own salary — they are paid by what the market dictates. Everyone doing the same job gets paid the same salary. Our transparent approach pays all employees consistently and equitably, removing any potential stress or anxiety around employees wondering if their colleagues performing the same job are making more than they are. Everyone is making the same fair amount for the same job.

The implementation of our fair-pay model of paying everyone doing the same job at the same pay has resulted in extremely positive employee feedback. We’ve found that potential candidates also appreciate this data-driven, transparent approach. Our recruiters are able to set expectations about pay early in the interview process, and candidates rarely decline our offers due to compensation. 

How to Get Started

I admit, it does take time, effort, deep analysis, and hard work to create and continue a fair-pay model, but the benefits far outweigh the cons. Here are a few tips for getting started with your own fair-pay model at your company: 

  • Make a concerted effort to fully understand everyone’s roles and the different activities for each position, benchmarking them to market.
  • Allow someone to walk away for higher pay elsewhere.
  • Partner with your managers on how to set realistic, achievable goals, as well as regularly give feedback. Remember that not everyone will be successful or be the right hire for a role. Tough decisions will still have to be made. However, making the decision to pay high on the scale for top performance means that your company has the responsibility to ensure employees live up to those standards.

Our fair-pay model has been a resounding success. Likewise, if you can similarly implement a fair-pay approach company-wide, it can infuse value into everything that your employees do and ensure that your organization is running as equitably and competitively as possible.

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