Earlier this year, Pave acquired Advanced-HR, the parent company of the Venture Capital Executive Compensation Survey (VCECS), Option Impact, and Option Driver. Since the acquisition, we’ve been working on bringing the best parts of Advanced-HR into Pave to up-level how our customers benchmark compensation.
We talked to dozens of Advanced-HR customers to deeply understand their compensation needs, and we quickly learned that one of the most critical aspects of Advanced-HR was the annual VCECS report that is released every September. True to our strategy, we set out to learn what made VCECS so valuable, with the ultimate goal of incorporating these aspects into Pave. Pave will be releasing the 2022 Executive Compensation Benchmarks on September 26, 2022. Participate by signing up for Pave here.
Along the way, we discovered a lot of nuances around executive compensation benchmarking. Here are our top 4 insights.
Almost every customer we talked to described benchmarking executive compensation as an art, not a science, especially in comparison to benchmarking general employee compensation.
Many of the guardrails used for employee compensation aren’t applicable when benchmarking executive compensation. While a company may have a general compensation philosophy to pay at the 75th percentile, this doesn’t always apply to executives. These roles are often higher stakes and result in more frequent exceptions. Customers leverage data to help inform these exceptions and ensure their pay is roughly in line with executive compensation in the market, regardless of their compensation philosophy.
Similarly, when pulling executive compensation benchmarks, it’s common to filter data across many different dimensions to help with triangulation of the data. Customers search by valuation, capital raised, location, and various other filters to build confidence in the data they’re looking at and ultimately the compensation decisions they’re making.
Simply put, the process of pulling benchmarking data to make an offer or build a comp band is more involved and ad-hoc for exec compensation, especially when compared to broader employee compensation.
Luckily, Pave will support all of your filter dreams – founder status, company stage, and more – in an easy-to-navigate interface that allows you to view and filter data quickly and with confidence.
For every CTO there are tens, hundreds, or thousands of software engineers in the world, which means there are far fewer CTO compensation data points available. Inevitably, executive compensation decisions are made with fewer reference data points.
What Pave (and our customers) would historically consider a “small sample size” for employee compensation can actually be a valuable sample for executive compensation benchmarks. Making a compensation decision for a mid-level software engineer based on 10 data points might seem crazy. Making a compensation decision for a CTO hire based on 10 executive data points is the norm.
While Pave has more than 30,000 executive compensation data points, that’s still only a fraction of our employee compensation benchmarking data volume (510,000, and growing).
Pave’s API-integration based approach means our executive data volume is constantly growing. However, we know all data is valuable for executive compensation, even with small sample sizes.
The workflow surrounding how and when people pull executive compensation looks different relative to how and when people pull employee compensation benchmarks. People often start benchmarking executive compensation with expectations of what the data should look like based on what they’re seeing from candidates in the market or their existing executive compensation packages.
While this motion isn’t unheard of when benchmarking employee compensation, it’s most common with small companies before they have a solidified compensation philosophy or compensation bands. With executive benchmarks, benchmarking with expectations in mind is far more common, regardless of company size or stage!
People often turn to using benchmarking data to validate or enrich an already existing hypothesis about executive compensation, rather than using compensation benchmarks to start from scratch.
The 2022 Executive Compensation Benchmarks powered by Pave will provide access to all of the information you need to quickly and easily test your executive compensation expectations against the market.
When pulling executive comp benchmarks, people want to search by title. A CTO is a Chief Technology Officer, not an E9-level Engineer, and users expect to search this way.
In employee compensation, there is so much variation in titles: in some orgs, titles don’t indicate level (let alone specific department). Conversely, at the executive levels, titles are much more homogenous and a good indicator of job scope and level. Being able to search for executive compensation by job titles is simpler and gives users confidence they are pulling the relevant benchmark.
Supporting title-based search in the 2022 Executive Compensation Benchmarks is critical, and we’re excited to bring this capability into Pave.
Like Advanced-HR & VCECS, Pave is focused on offering fair, transparent, and equitable compensation data. As Pave releases the 2022 Executive Compensation results, we promise to keep the most valuable parts of VCECS and iterate on the parts that we think we can improve. One of the benefits of our API-integration based approach is that we’ll continuously evolve our data and product throughout the year and move away from a static annual report. This means you get access to more accurate data every day.
If you’d like to explore Pave’s full benchmarking data set, you can sign up for free here.