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Gail Miller, head of data, Scottish Power

Gail Miller

Path to power

I came to a data role later in my career, having worked for many years as an accountant and also in change management and commercial management positions. It’s fair to say I fell into it. My previous role was as lead for the retail business in the industry wide competition market investigation, which, among other things, required me to support lobbying positions with evidence and prove or disprove long-held theories based on data and related insights.

 

It was while I was doing this role that I experienced first-hand the frustrations of not being able to access the data you want in the most timely and effective manner. At the same time, the business was looking for greater digitisation, process automation and data-led decisioning, and while we had a level of expertise spread across the business, there was a clear need for investment in technology and people to make the step change we were after.

 

After the Competition & Markets Authority investigation ended, I took up the newly formed role of head of data, consolidating what we had and building on it, including both the investment programme for our data estate, as well as building the new data team.

 

What is the proudest achievement of your career to date?

It’s been a total roller coaster of a ride but my greatest achievement has to be the creation of a hugely diverse, very skilled data team. We have staff from all over the world, from many different career histories and an open culture where everyone’s opinion is heard.

 

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

I know it’s cheating but I need to say two. First, Duncan Bain who leads my data science team - an incredibly intelligent guy who has been by my side through the journey and who continues to challenge my thinking on a daily basis. Second, our previous global retail director Neil Clitheroe, who showed an enormous of faith in me, giving me the opportunity and backing to build a data function that I’m really proud of.

 

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

2019 was so different from how I expected it to be. Like many data functions we are a victim of our own success, and this has resulted in a much broader list of demands from the business, at a pace I simply didn’t see coming. We have adapted well - it’s not perfect but the team have embraced an agile delivery model, while managing to retain some of the critical quality metrics essential to make sure that we deliver production ready insights to the business.

 

However, there’s more to do and that’s what 2020 is going to be all about. But I also think it’s important to recognise that this heightened level of demand from the business is actually an endorsement of the data team that we’ve created, and of how the business has embraced data-led decisioning.

 

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

The pace of change is astounding, and new innovative solutions and opportunities present themselves almost daily. I don’t expect this to change but believe we are starting to see a greater focus on technologies and approaches that hit the balance between innovation and getting good, production stable outputs.

 

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

There are so many to choose from. From a business perspective, I think the use of machine learning/AI to automate business process that simply distract everyone from looking forward is definitely going to be a core area of focus. Similarly, in the rush to digitize, we have seen many companies building great front-end experiences, but with little or nothing in terms of back-end processes to support this, and this simply isn’t sustainable to meet customer expectations while remaining efficient. In terms of humanity, there are so many options but at the most basic level, using data and technology to help us connect people and provide greater support to the vulnerable in society - who would not want to know that an elderly relative made it up and had some breakfast?

 

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

This one is simple: data quality, data quality, data quality. We can always up our processing power or scale our technology, build clever models and manage the demands of the business, but if the core data you have is not available or not accurate then you may as well not bother. While data quality issues are fixable, they remain a challenge for many organisations.

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