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Phil Maine, head of data science, BT

Phil Maine, head of data science, BT

How is your organisation using data and analytics to support the corporate vision and purpose?

 

BT’s purpose is “We connect for good” and to achieve it demands a greater level of understanding and intelligence around our customers and our own operations and being smarter with that data to continuously improve every aspect of the business.

 

Data and analytics has always been a core part of BT in understanding the networks, the customers, and using insight to make intelligent decisions. Now we’re progressing beyond that with data science, artificial intelligence and machine learning, looking to drive the strategy - everything from self-healing operations to customer recommendations.

 

2020 was a year like no other - how did it impact on your planned activities and what unplanned ones did you have to introduce?

 

It’s hard to know where to start with 2020, where so many people pulled together in a time of crisis to do the right thing for one another, so perhaps then to just shine a light on the data corner of our world.

 

In our work to use data, AI and ML to personalise and tailor every customer journey and experience, this year we effectively had to throw out everything we knew about predictive habits and customer behaviour when it came to how customers interacted with us. Typically, changes in behaviour are gradual over long periods of time, but this year we saw overnight en masse changes to the people’s wants and needs, what was important to them and particularly a growth in our digital channels.

 

Everything had to be refreshed, refocused and updated to reflect “the new normal”, which was and still is effectively continuous volatility. The ongoing challenge over the next few months if not years will be determining how many of these market and behavioural changes will stick. Our continued ability to adapt, let the data tell the story and be comfortable questioning previously held beliefs will be key to maintaining success.

 

Looking forward to 2021, what are your expectations for data and analytics within your organisation?

 

The expectations for 2021 can be summed up in one word – scale. There has been lots of recent investment and transformation within BT to re-baseline our foundation, both from a technology perspective, including better use of cloud and upgrading legacy IT to ways of working, with agile practices across large swathes of the business. This year is about all of those things coming together in sync, to allow data-led transformation at scale, both for our customers and how we operate as a business.

 

Is data for good part of your personal or business agenda for 2021? If so, what form will it take?

 

One personal agenda for me is around the ethics of AI. This isn’t anything new across most businesses, albeit with a heightened focus since GDPR, but we’re now clearly at the point now where we’re able to work within those boundaries. However, as machine learning drives decision-making more and more, we also have to increasingly ask ourselves tougher questions. Is the data biased? Are we training models to learn from potentially negative behaviour? Does the experience diminish for those who opt out of data driving their interactions? It is the old adage of "just because we can, doesn’t mean we should", which will certainly for me be underpinning everything we’re looking to do in 2021.

 

What has been your path to power?

 

Data definitely wasn’t my career masterplan, and for my first proper role I thought I was applying for a job in finance, and it was only in the interview I found out it was actually a job in credit risk modelling! For me it was always a case of being fascinated by how data was being used to drive decisions. That led me towards business intelligence and analytics at Vodafone, which not only opened my eyes to how much data and information was out there – large amounts as an untapped resource – but how much impact analytics and insight could make. The right data, and the right insight at the right time can be the difference between keeping up and racing ahead.

 

Working at British Airways introduced me to the concept which I now think is the key thread throughout my career – personalisation. BA had an analytics programme to understand each customer as an individual and used that with great success to tailor communications and experiences to them.

 

My interest in data science grew as it became clear to me that the next obvious progression from generating insight for a person to decide, was in using AI and ML to drive those decisions and impacts directly, with people used more as curators of that intelligence.

 

This led me to EE to set up an advanced analytics team, which later expanded to include both EE and BT brands, building a new data science function at the heart of the consumer business.

 

What is the proudest achievement of your career to date?

 

I’m incredibly proud of forming the first data science team for BT Consumer, and in that first full year the team added mulit-million pounds-worth of incremental revenue solely down to AI and ML.

 

From my experience to date, no matter the industry, all organisations are effectively trying to do the same thing, to treat data as an asset from which to gain value, and competitive advantage.

 

The ability to use that knowledge, to use AI and ML to fully realise what personalisation at scale can achieve, is something I think we have begun to deliver on with my current team, and I hope to continue to be delivering on in my career going forward.

 

Tell us about a career goal or a purpose for your organisation that you are pursuing?

 

A key tenet from my career is that data is the closest anyone can get to knowing each and every customer. One of my career goals is to ensure that data is used for every decision as in effect that means putting the customer at the heart of every decision. Customer obsession is always a key pillar for a successful business, and data is the best way to achieve that at scale.

 

How closely aligned to the business are data and analytics both within your own organisation and at an industry level? What helps to bring the two closer together?

 

Data and analytics are intrinsically aligned with the telecommunications industry, with the vast mobile and fixed networks generating huge amounts of data. As fixed and mobile convergence becomes even more prevalent in the UK, this also means telecommunications companies will become more like technology companies, using data, AI and ML to offer both connectivity but also the services that go along with that.

 

What is your view on how to develop a data culture in an organisation, building out data literacy and creating a data-first mindset?

 

I believe a key principle in developing a data-first mindset is the same as building any new mindset - “show, don’t tell.” Often you still need the early adopters to be bought in to the concept, or at least enough to get started, but to reach critical mass requires demonstrable data-led successes to start telling that story and helping people understand how things differ from what they know today. It’s best to start simple and deliver something quick, and then continually build on it, as that way you’ll get the groundswell of data-first converts to help tell the story as no one can do this alone!

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