<aside> 🛑 This guide is still a draft. More content will be added later.
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Increasingly, companies need to develop a cohesive compensation philosophy, especially earlier in their growth given the rise in regulations and move towards greater salary transparency.
Unless your organization likes ‘shooting from the hip’, operating without data is one of the worst things you can do.
This guide could easily balloon into a lot of topics. So I’m keeping the focus narrow on selecting and implementing. Subsequent guides will focus on how to develop a compensation philosophy based on market data. (Related, I have a lot of compensation resources here).
Few good things in life are truly free. If you’re getting the data for free, you’re likely giving something up in turn. Though in the world of salary surveys, theres a lot that you can get access to either on a freemium basis or through an exchange of data.
My argument: for most any organization, base salaries represent the largest organizational expense. The upfront cost can seem like a lot. Though here are some of the benefits:
Using a salary survey is helping you to be ‘less wrong.’ (Ie. improving your confidence interval). Sure you can get data for free. But it’s not going to be very precise. A salary survey is going to give you both precision and greater confidence in your decisions.
The tl;dr is that free data is often spotty, prone to massive variances, and / or includes data erroneous to your peer group. Either way, you end up ‘paying’ for these decisions.
Think of salary surveys like grocery stores. The end outputs are all very similar (things you can eat), but the choice (brands, quantities, availability, etc.) all vary widely.
When selecting a survey, you should ask vendors about their: