The instinct is to hire a copy of the person who built your success. In a field moving this fast, that is how teams quietly age out. Hire for how people learn.

Hire for the next decade, not the last one

When a business goes to hire, the quiet instinct is to clone its best person from five years ago. Same background, same tools, same turn of mind, because that is what success looked like and success is reassuring. In a field that moves as fast as this one, it is also a comfortable way to age out.

In practice, this is where our data strategy and leadership work comes in, and Today Versus Tomorrow: The Data Leader's Toggle covers useful related ground.

The skills that built where you are now are not the skills that will build where you are going. Five years ago the right hire knew the on-premise stack inside out. Today the work is in the cloud and in Fabric, the tools rewrite themselves every few months, and a real part of the job is knowing how to work alongside AI rather than pretending it is not in the room. Hire only for yesterday's stack and you will not fail dramatically. You will just get gradually slower than the people who hired for tomorrow, and you will notice the day a competitor does in an afternoon what still takes your team a fortnight.

Hire for how someone learns

In practice that means hiring for how a person learns, not only for what they already know. The most useful member of a fast-moving team is rarely the one with the longest list of current certifications. It is the one who, dropped in front of a tool that did not exist when they trained, works it out and ships something useful by the afternoon. That is a different quality, and you can test for it.

A question we like, for any candidate at any level: tell me about a tool or a way of working you picked up entirely on your own this year, and what made you bother. The answer tells you more about the next decade than any qualification on the page. People who learn because they are curious keep learning. People who learned only because someone made them tend to stop the moment nobody is making them.

The generational point, said plainly

There is a generational edge here worth naming without sentiment. The people entering the workforce now are native to tools the rest of us are still adjusting to. They do not find AI assistants novel or threatening. They find them obvious, the way everyone now finds a search engine obvious. That is not a threat to manage. It is a free upgrade to your team's instincts, provided you hire it in and then actually listen, rather than asking the new arrival to do things the way they have always been done.

We are putting our money where this is, bringing fresh people into the business who think in tomorrow's tools and giving them room to change how we work rather than slotting them into how we already do. It is one reason being named on the UK's Best Workplaces for Development list [confirm placing and year] matters to us more than most of our certifications: it is outside proof that the curious, self-teaching people this whole piece is about can actually grow here, rather than being quietly trained to do things the old way. We hire for that quality first, and the recognition is the by-product, not the point.

The honest test for any leader is short. Look at your last three hires. Did you hire three more of who you already had, or did you hire for where the work is going. If it is the former, your team is not getting worse. It is quietly getting older than the market, which is the harder problem to spot, because nothing about it feels like a mistake until it is an expensive one.

If you are early in your career and you learn for the love of it, we tend to be hiring, and you can get a feel for how we work here.

If any of this sounds familiar, talk to us about your data.

Related reading

• Do Not Make Your First Data Hire An Analyst
• Your Data Strategy Should Fit On One Page
• Work From Happy, And Why We Put A Number On It