Data Futurology Podcast Episode 215: How data skills are putting digital specialists at the centre of organisations.

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

This week on the Data Futurology podcast, we have three special guests to share insights on how data works in retail settings. Nick Merry, the Head of Analytics at flybuys (Loyalty Pacific), Kathryn Gulifa, the Head of Data and Analytics at Catch, and Stuart Garland, the Director at Talent Insights Group, join us for a wide
ranging and in-depth look into how analytics are changing and the impact this is having on teams.

“The really good analysts that I see are the ones that are able to crystalise their understanding of what a business is trying to solve, and solve for that problem in
particular,” Gulifa said. “I always think that the technical skills can be taught if you’ve got the aptitude. With the technology landscape changing so rapidly, if
you try and peg yourself to recruiting people that have experienced only particular tech, you're really limiting your options.”
As Garland then notes, those that focus purely on their technical capabilities would limit their career development opportunities, unless they’re willing to learn how to engage with the broader business anyway: “Even if you’re not leading people, you still should be learning the ability to demonstrate the value and impact that a project is going to have on the business at a more senior level,” he
said.

As Merry also notes, the days where the data team would be separate from the other lines of business are largely over. Now, the digital team is integrated into everything from marketing to security and governance, and people on that team need to be able to have conversations across all of them. “Having digital analytics, not as separate functions, but more integrated with the broader view, is one of the encouraging things that I’m seeing,” he said. For more deep insights from these three thought leaders on the changing dynamics of work in data and analytics, tune in to the podcast!

Enjoy the show!

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Quotes:

I’m not a fan of the data translator role because I feel it absolves data analysts from developing the skills of consultation and defining a problem. What differentiates good analysts from really good analysts, is understanding the business context and the ability to drill down into what's actually important to the business.

When it comes to recruitment, I always think the technical skills can be taught if you've got the technical aptitude. The technology landscape is changing so rapidly, all the time, that if you really try and peg yourself to recruiting people that have experienced only with particular tech, then you're really limiting your options. I think what you should be trying to find people that have not necessarily the polished and ready to go consulting skills, but the curiosity, the engagement, the wanting to understand why they do something, and what impact their work actually has on the business that they work for.

Considering people with longer or shorter tenures depends on what the role is and what you want from that individual. If you're in the process of building a platform and bringing in a data engineer that has gone across three or four different builds over the last four or five years might be useful because from that perspective, you've got three or four different pain sets, lots of experience in regards to what went wrong and, more importantly, what went right.