Friends,

Dropping in briefly from holidays with two things.

If you’re like me you’ve been to all the HR conferences and been handed the 1,000’s of pens and other crap that just ends up in the rubbish. When I decided I would do merch, I always wanted to do it differently. Small batch, high quality. Example: I did a bunch of hampers to a select group of clients earlier this year, and it. went. off. I even shared a couple of pics and got a mention in my favourite new guilty please DRIP DROP, a newsletter all about great merch! Check it out here and subscribe if you’re as addicted to great merch as me.

I’m officially in Tanzania and enjoyed my first day of safari! And it was incredible. There’s just no doing justice to these kinds of animals running free in the wild. But despite that, here’s a couple of pics anyway (including the endangered white rhino).

Ok, I’m back to looking at animals.

Enjoy this weeks edition ✌

Matt

In case you’re new here (or just missed it) here’s the past three editions of the FNDN Series:

You've spent years building a people function you're proud of.

Great onboarding, competitive benefits, a culture that actually holds up.

Then someone needs a visa, and the whole thing unravels into spreadsheets and panic, which doesn't match the standard you've set everywhere else.

Every visa has its own timeline, its own paperwork, its own dependencies. Multiply that across countries and it's a full-time job - most likely sitting on your plate (reluctantly).

We built Concord for exactly this: to make your life easier as you juggle this new responsibility you probably didn’t ask for! We're a startup-native immigration firm who work in Slack and Google, not 100-page email threads. Our advisors actually understand fast-moving companies, and they'll keep things moving without you having to chase.

Our purpose-built app gives you and your employees real-time visibility into every application. Immigration that finally feels like the rest of your People stack.

If your immigration process currently lives between someone's inbox and a neglected spreadsheet, we should talk.

Know a startup Head of People looking for answers 🙋 why not forward this to them for some instant karma? ✨

When you're scaling fast, market data is one of those decisions made in a hurry.

I know, because I’ve been that person.

You sign with whatever vendor came recommended by a peer CPO, your VC or the first sales rep who returned your call.

I still remember when I was in an early role, I signed with one vendor because the other took too long to get back to me. Literally that was the extent of my decision making experience… (don’t look at me like that, we’ve all been there)

So you buy the data, the bands look sensible, recruiters stop complaining, and you move on to the next fire.

Then the issues start.

Offers come in flat. A senior engineer leaves and casually mentions she'd been underpaid for eight months. None show up in a board pack as a "comp data quality issue."

They show up as missed hires and the slow drip of credibility that leads back to you as a People professional.

This is where the true cost sits if you get comp data wrong.

It gently degrades the salary bands you stand behind, and it impacts your ability to hire and keep the people you need to deliver on strategy (the reason we’re all here).

So what are the signs, and what do you do about it?

If your mid-point says $180k but offers consistently go out at $195k+, the data is behind the market.

Quick test: Pull your last 10 accepted offers and compare them to your published bands. If a third or more are clearing above target, your benchmarks are the weak link, and in a hot role family, that issue compounds quickly.

Watch for compensation coming up in stay conversations or exit feedback, even casually.

If you're losing top performers to competitors paying 15-20% more, your bands aren't where the market clears. Be clear to test for people moving to a similar role though, don’t inadvertently count exits for promotion as a pay issue.

But if you’re not already, start doing exit interviews. Ask "what would have kept you?" The answer could end up telling you where the market sits.

Recruiters live closer to the market than anyone. When they start saying "this band won't get us the candidate," trust them, but verify it.

I love recruiters, but their job is to close roles. Salary is often an obstacle, so validate the concern by asking for expectations across the shortlist (that way you know you’re comparing people actually qualified for the role).

Track band-stretch requests by role family over a quarter. If you’re starting to see band stretch across a meaningful number of offers, the data is telling you your bands are off.

I've seen this with CPOs whose vendor was solid on generalist engineering and product, then suddenly felt 20% off once they started hiring specialised AI or security talent.

Can you pull a sample size report in your tool for your top 10 role families — the ones central to your hiring efforts?

If you can't easily see the data points behind each band, or the numbers come back thin, you've got your answer.

If you can't slice by industry, stage, function and geography the way your business operates, you're benchmarking against a population that doesn't look like you.

I recently did some work with an organisation where the cut of roles they were hiring for was 20%+ clear of the ‘general industry’ data we were using. Drilling down into the filters left huge gaps in data, meaning were we flying blind.

Once you're scaling across markets and functions, you need to be able to drill down into data in a way that reflects your real hiring footprint. Specific companies, in specific industries, with relevant revenue or headcount sizes.

Can you pull a benchmark for your most specific role (for example a Senior Security Engineer at a 200-500 person SaaS in your primary market)?

If the filtered sample comes back empty or low on integrity, you're extrapolating, and it might be time to re-evaluate your benchmark vendor.

The most common mistake is letting the vendor set the criteria, so walk in with your own scorecard.

Before any demos, write down what you actually need: roles and geographies you hire into, refresh cadence, access requirements, and benchmark philosophy.

If you’re looking for a detailed guide, I’ve worked with my friends at Pave to put together an agnostic view on how to diligently buy your next. Grab it here (it’s a great free resource).

Without your selection criteria, sales reps will happily reshape your requirements to match their product. This is what we want to avoid!

Once you’ve written these down, it’s worth weighting them.

I tend to rank in this order: coverage first, usability second, cost third.

Coverage is non-negotiable. If the vendor's data doesn't credibly cover your roles and markets, the rest doesn't matter. Ask for sample reports on your hardest-to-benchmark roles; if those come back thin, the contract will too. Push every vendor on data refresh cadence, contributor base, and sample size behind your top role families. Vague answers are coverage gaps.

Usability is where most teams underweight the decision. Some incumbent platforms still require 1-3 days of manual work every six months to refresh your bands. A modern platform handles the heavy lifting in hours.

Cost only matters once coverage and usability check out. Cheap vendors with patchy data cost more in bad offers and lost hires than you'll ever save on licence fees.

The ROI on good data is easy to spot. It prevents you from overspending just because your hiring managers or recruiters are saying salaries are lifted. On the other hand, keeping up with the market ensures you’re not copping the turnover penalty.

I saw a great turnover cost calculator from former FNDN Series guest Andrew Bartlow, here, if you’re looking for help to do this.

Lastly, pilot before you sign.

Most vendors will let you run their data against a recent offer set.

A week with real data on your roles tells you more than any sales deck will.

Before you go shopping for a new comp dataset — bring Finance in! — certainly before you've shortlisted vendors.

Get them aligned on the why and where the budget impact might land. The earlier they're across it, the more cover the project gets if surprises surface.

Now let’s talk rollout, once you’ve actually made the call to switch, because this is where it usually goes wrong. The rollout carries most of the risk, even when vendor selection has been spot on.

Map your existing comp architecture before importing new data: levels, families, geo zones, philosophy markers. Reconcile up front, or you risk spending three months untangling why your bands look weird.

Importantly, give yourself a runway on timing.

Plan enough lead time before your next comp cycle to migrate and validate, so you're not juggling two datasets during merit reviews.

Outgrowing your first comp data provider is a normal part of scaling. It usually means your company has moved past the assumptions baked into your original contract. The CPOs who do this well treat vendor review as a recurring discipline.

So ask yourself: how did you end up with your current comp data provider? And when did you last check it's still the right fit for the company you've become?

If you want the deeper version of how to run this process, the Pave team and I have built a full playbook covering evaluation criteria and switching pitfalls.

Download it here (it’s free!).

If you enjoyed this post or know someone who may find it useful, please share it with them and encourage them to subscribe.

A roundup of the most interesting stuff from the week:

When you’re ready, here’s three ways I can help you:

1. Tools & resources
Resources and tools that give you what you need to build your own startup compensation practices.

2. Comp consulting
Building startup compensation practices that are clear, fair and competitive.

3. Startup People Summit
A 1-day annual event for People professionals in scaling companies. Creating the playbook for startup people practices. Grab recordings from past events, or subscribe to join the next summit.