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This a profile from the 2019 version of the DataIQ 100.

To see the current DataIQ 100 please click here.

DataIQ 100

10. Paul Ravenscroft, Head of personalisation and digital insights, Walgreens Boots Alliance

Paul Ravenscroft

Path to power

 

Twenty years ago, when like many at the time, I fell into analytics, the career option was unknown. Starting in Boots’ commercial buying function, I responded to a job ad for an analyst in the then new Advantage Card insights team. Although the days of focused analytics degrees would be some way off, my background as a social scientist put me in good stead and this was a great way to develop my analytical skills in a new team finding its way. After spending two years focusing on personalised communications and modelling, I moved into B2B at RS Components further developing skills across analytical functions with some great people. I also worked with different business partners with a sales focus and more input into strategy. From there, I first cut my managerial teeth at Lands’ End with a small team covering all elements of analytical requirements. Returning to Boots in 2008, my mission was to build personalisation capability in-house. From the early days of implementing new systems to introducing new channels and taking responsibility for the challenge of developing new personalisation programmes for other areas of the business, it’s been a great experience and privilege.

 

What has been the highlight of your career in the industry to date?

 

For me, it has been watching a team and people (including myself) develop. We have seen a massive growth in analytics in the past ten years, particularly as the move to digital demands those personalisation skills. Recruitment has been increasingly challenging, therefore to see people come into analytics and develop into great analysts and leaders, to continue developing those skills as demand evolves, and then to deliver great results has been the highlight for me.

 

If you could give your younger self some advice about how to progress in this industry, what would it be?

 

Data and analytics is broad, for example, personalisation, MI, location analytics, strategy, insights through customer research, etc. My advice would be to try and get some experience in as many areas as you can before choosing a focus and always keep a commercial emphasis, work closely with business teams.

 

Did 2018 turn out the way you expected? If not, in what ways was it different?

 

There was much apprehension and work beforehand - GDPR was the big change, but the discipline it has brought is a good thing for the industry. The capability of data science and engineering has led to further transformation in the art of what is now possible and has accelerated the speed of achieving it in ways that were difficult to imagine a few years ago. A good balance of GDPR discipline and innovation was achieved in 2018.

 

What do you expect 2019 to be like for the industry?

 

I expect to see more organisations embrace and innovate with new sources of data. I see more outfits joining together data to provide a more coherent data and analytics proposition for internal users and customers. GDPR has set the terms of reference and bedded in, so I hope we will continue to see the promotion of using the data customers have volunteered to share with the industry in all kinds of creative and positive ways that benefit the customer.

 

Talent and skills are always a challenge to find - how are you tackling this in your organisation?

 

This is a challenge. For some time, I have operated a recruitment policy that is not too prescriptive and is focused on finding people who can develop the right skills and behaviours - not just analytical and technical skills, but people skills, too. Many have gone through this development path and are skilled at guiding new joins through it drawing on skilled external expertise when required. Knowledge of analytics as a career still remains a challenge to be addressed by us all.

 

What aspect of data, analytics or their use are you most optimistic about and why?

 

The digital transformation of big data has been huge. Some see more machine-led analytics as the way forward - no doubt it will increase, but I think there will always be a strong human element that together creates a better customer or user experience and more exciting careers for analysts.

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