Implementing a data-driven approach to guarantee fair, equitable and transparent employee pay
Your pay is important. It's usually something most people don't understand - why are we paid what we're paid? Ultimately, this lack of clarity can lead to confusion and negative feelings that affect our productivity and relationships with our employers. You may have encountered situations when you felt your pay was unfairly biased by your manager, recruiter, HR or company policies.
You may know or suspect instances in which your pay has been determined based on someone else's preferences for background, or stereotypes about your gender, race, ethnicity, identity or abilities. It can even feel unfair based on your own confidence in your ability to negotiate.
What do we think is the right thing to do, and how do we aim to achieve it here at Plastiq? Paying employees fairly, equitably and competitively is what's right. Being transparent about our philosophy and practices is the commitment we've made to achieve this goal.
In designing our compensation philosophy, the Plastiq leadership team agreed that fair pay and transparency would be our guiding principles. Then it was all about the data.
The first step was to understand everyone's work: their job function, the scale and scope of their work, and their day-to-day responsibilities. This led us to being able to identify if someone was working in accounting or financial forecasting, software development or product management, recruiting or people operations, contributing as a recent graduate/new person to the workforce, a seasoned individual contributor, a senior team lead, an experienced people manager or a more strategic cross-functional vice president.
Next we invested in access to market data from a credible resource - one that we know is used by other companies we respect - with comparable market, industry and size to Plastiq. 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 trust. This ensures a few things: no subjective self-reported data, accurate alignment in assessing the scale and scope of all the roles, as well as mutual interest by the user base to make sure the data reporting and retrieval was reliable. For Plastiq, the most relevant data centered around what other companies in San Francisco and Boston pay their talent. We also cared about paying as well or better than other tech companies - in particular fintech companies - that were not yet publicly traded.
These distinctions are important for any business when planning pay. To use another small business as an example - let's say a food truck looking to hire cashiers and cooks - one might evaluate how much to pay its employees using several factors. For example, there may be a difference in pay for food trucks operating out of Austin versus Seattle; the type of food truck (savory or sweet) may influence the level of skill required to prepare or serve the food; margins may be vastly different, meaning the business may be able to employ many or only a few. If you were planning to staff and pay a large-scale, lower-margin cupcake food truck in Austin, would it make sense for you to base your employees' pay on a two-person sushi truck operation that required skilled sushi chefs in Seattle? Probably not. You'd want to benchmark against a business - preferably multiple businesses - like yours, in your market, with similar staffing and operational needs, to feel confident you're using the right data.
There is always a way to understand the market data for a company's particular situation and what their competitors pay for talent. On the flip side, if you're trying to figure out what you should be paid and what's fair, there is market data available to help guide you. You could start by asking other people you know that do the same type of work as you what pay they've seen around. You could even (and should), ask your manager, recruiter or HR team for the data.
For us at Plastiq, knowing we were committed to fair pay and to formalizing that into a transparent philosophy, the next piece was to decide how competitively we wanted to pay versus the market rates. We considered three possibilities: