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This is a profile from the 2020 version of the DataIQ 100.

The 2021 list is available here

Denholm Hesse, head of data analytics, M&G

Denholm Hesse

Path to power

At university I co-founded a small, not-for-profit consultancy, which offered local businesses support from management school students and, in return, students gained work experience. I enjoyed it so much, that after graduating I joined Deloitte as a consultant. While on my first project, my manager asked me if I could help out with a small data challenge they had. I loved it and a few months later I moved across to the customer analytics team.

 

I found my home in that team and spent the next five years working with some of the largest financial services organisations on their data challenges. This ranged from building out business information reporting suites and single customer views, to helping organisations define their data strategies and think about data governance.

 

From there, I moved to M&G to lead data and analytics for the wealth business. My first year was great and we made real progress by building out a team and driving data driven decision making across the business. After a year looking after analytics for wealth, I was given the opportunity to lead data engineering and analytics across customer and distribution at M&G.

 

What is the proudest achievement of your career to date?

My proudest achievement so far is the team we have built at M&G. There is a feeling across the team that there is no challenge we cannot solve and it’s great to be part of a team like that. Our quarterly team health checks reflect that, and our progress towards our vision shows us we are on the right path and moving at a good pace.

 

Who is your role model or the person you look to for inspiration?

For his curiosity and philanthropy Bill Gates. He is a data guy, but, more than that, I love how he trusts himself to be able to learn anything and he uses that to make the world a better place. His YouTube and book recommendations are a great source of inspiration.

 

Did 2019 turn out the way you expected? If not, in what ways was it different?

In general, yes. We focused and delivered on what we needed to do last year, such as building a strong team, aligning analytics across all new digital deliveries and ensuring we are complaint with regulation. I would have perhaps expected more in the way of AI and machine learning, but I expect this to come this year as the team is now established and a lot of the analytics groundwork has been completed, meaning we can spend more time on these areas.

 

What do you expect 2020 to be like for the data and analytics industry?

I think that 2020 will be less about buzzwords and more about genuine exploration and experimentation. Today’s hot topics of AI, deep learning etc, are amazing capabilities but I think we will see a year when these capabilities are more often applied when required and in a way that drives true value rather than as opportunities to boast about. At the heart of this is the idea that data should help us to make better decisions as frequently as possible; it’s an analytics team’s job to work with the business and find the right techniques for the situation and apply them.

 

Data and technology are changing business, the economy and society – what do you see as the biggest opportunity emerging from this?

I feel optimistic for 2020. I think what we will see is that more and more organisations looking to use data as a force for good and positive change. Companies will ask themselves; how can we use data to identify opportunities to reduce the impact we have on the environment? How can we use data to improve diversity and inclusion for customers and employees? How do we best build a successful, sustainable future?

 

What is the biggest tech challenge you face in ensuring data is at the heart of your digital transformation strategy?

In order for data to be at the heart of our digital transformation, we have to work hand in hand with many functions across an organisation, such as security, risk and privacy. Working collaboratively and pragmatically will be crucial in using data science to improve customer outcomes and it’s a challenge we face confidently together.

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