Bringing (data) science to the art of compensation
FairOffer is a compensation algorithm.
Today, compensation is based on low-sample size benchmarks that quickly go stale. We had access to a wide range of data; instead of building another benchmark database, we did something different. We built a data science model to identify the predictive effects of function, title, location, and stage of company.
The result: an algorithmic model that robustly simulates compensation across 2.4 million scenarios. It's not perfect, but it's incredibly accurate at estimating a fair offer for any title. Any stage. Anywhere.
Our methodology and algorithm are published in a series of posts:
- Part I: What's broken today
- Part II: The Total Rewards Algorithm
Benchmarks are an important input! But they do not (by themselves) allow hiring managers / recruiters to generate a clean offer out of the box, for three major reasons:
- Spotty data, especially for globally distributed workforces
- An isolated benchmark without the context of a comp philosophy or framework makes it harder to communicate compensation to employees and candidates… not to mention the compensation “journey” as the employee grows and company advances.
- Wide, imprecise ranges resulting in muddy data (e.g., in salary bands — $150-220K base; or company stage — $100-250M raised)
- Benchmarks go stale quickly because each combination (e.g., "Staff engineer in Memphis TN at a Series B company") needs new data to be updated. However, a data science approach allows you to detect trends in the underlying factors (staff engineer trends x Memphis trends x Series B trends) to better predict what a competitive, market offer should look like. Skate to where the puck is going, not where it's at.
Based on hundreds of conversations with HR teams, compensation experts, hiring managers, and executives, we’ve devised a solution to these deficiencies in how compensation is handled today.
Absolutely! We're in early / beta access on a compensation management product that lets you leverage the Fair Offer model, but train it and tailor it to your specific organization and needs.
Just head on over to Autograph, and submit the 30-second form. We'll get in touch as soon as we're able to take you off our waitlist! Please feel free to include any other relevant context.
You can use Fair Offer for non-commercial purposes with attribution.
If you'd like to leverage it in a commercial project, we'd love to explore it if it's mission aligned (promoting transparency, standardizing the language and principles used in compensation). Please submit the interest form at Autograph with your intended usage and we'll get back to you.
