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This is a profile from the 2021 version of the DataIQ 100.

The latest list is available here.

Di Mayze, global head of data and AI, WPP

Di Mayze, global head of data and AI, WPP

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

 

WPP is a creative transformation company. We believe that data and technology power creativity, enabling us to build better futures for our people, clients and communities. Data - its power and potency - are embedded in our corporate vision and purpose, which is what makes WPP an exciting and inspiring place to do extraordinary work.

 

The centrality of data is exemplified in our commitments, such as:

 

  • For our people: our sustainability goals are centred around data having committed to net zero carbon emissions in our campuses by 2025 and 100% renewable electricity by 2025.
  • For clients: one of our key offers is creating “powerful ideas based on deep insights to connect brands’ messaging with audiences in meaningful ways and channels at meaningful moments”. To consistently over-deliver against this requires a deep and broad understanding of data, analytics and humans in all parts of the creative process.
  • For our communities: we made a promise earlier in 2020 to help combat racial injustice and support black and ethnic minority talent and pledged $30 million over the next three years to fund inclusion programmes internally at WPP and externally. Understanding the current state and progress on this is essential to driving change. This is a challenging one as the data is so sensitive and the analytics need to be handled with care.

 

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

 

We started out our year focused on improving data literacy having committed to up-skilling 5,000 of our data scientists by the end of 2021. Covid-19 put paid to our in-classroom, seven-week AI enablement and education programme which was due to begin in March with general assembly across Python, data science and analytics. Fortunately, we were able to pivot the programme, move it online and increase the capacity from 150 to 350 (including 120 women - hurray!) all in the space of a few weeks. We have since partnered with Coursera and purchased 2,500 licenses for data and AI training to scale-up this really well-supported initiative and over 3,000 lessons have already been taken.

 

We also promised to up-skill 50,000 of our colleagues on the fundamentals of data and AI and were working with one of our creative agencies to do some shoots for training footage. This, too, needed a re-think and we ended up with a number of creative data training alternatives. These included partnering with visual effects agency Territory Studio to use footage from 23 blockbuster movies to dispel some AI myths, and also with Synthesia where we have used its AI video capability to create training videos on 19 AI questions, such as, “How will AI impact the CPG industry,” and, “Does WPP have ethical guidelines for the use of AI?”.

 

I’m not complaining at the change, though - I’m thrilled that WPP continued to invest in its data talent while the world was a little lop-sided!

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

 

A favourite part of my job is uncovering and celebrating the data work and case studies from our agencies - it always inspires me and makes me proud of my data colleagues! I’m looking forward to seeing further fusion between creativity and data in 2021 and expect to see more data talent move between our media, creative and experience agencies as people apply different use cases to the same data set or industry.


This is all likely to be facilitated by the data and AI community which we launched in 2020 and already has 2,600 active global members. I’m expecting 2021 to continue to bring our data and AI talent together regularly to share interesting data sets, models, stories, predictions, creativity and experiences - and help each other along the way.

 

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

 

Data and AI for good is on both my personal and WPP’s business agenda for next year, as it was this one. 2020 saw us create a data ethics statement as part of our data privacy charter and ten of our agencies came together to develop the first draft of our data and AI ethics guidelines and principles.

 

In 2021, data and AI for good will be a frequent topic of conversation internally and externally via our partners and chief data officer network and also with our clients. We have an AI for good series within our data and AI community planned next year and we are expecting multiple revisions of our principles and guidelines as our understanding in this area grows, particularly around unintended consequences.

What has been your path to power?

 

After nine years in digital roles at Hearst UK, I enrolled at Cranfield School of Management to do a full-time MBA. It was here that I worked on a project with dunnhumby and my passion for storytelling was born. I joined dunnhumby as a senior solutions director in 2008 to work on a price and promotions econometric modelling project for Nestlé before moving to the media evaluation team and finally the category team.

 

In 2011, I was living in Nottingham and joined Boots as its head of supplier insights, building and commercialising data from its Advantage card and consulting for clients such as Estée Lauder, L’Oréal and J&J.

 

At the end of 2014, I moved back to London joining Acceleration, a WPP marketing technology consultancy that is now part of Wunderman Thompson. I was promoted to MD in 2015 and delivered data and tech consultancy for clients including SABMiller, Barclays, Compare the Market and Mazda.

 

I left this role in 2017 to become a freelance data strategy consultant having missed fully immersing myself in data projects! I didn’t go very far away and having consulted for WPP agencies Wavemaker, VML, Geometry, Wunderman Thompson and MediaCom, I joined the WPP CTO team and became global head of data and AI in January 2020. On reflection, my journey is not so much a path to power but to arriving at the perfect job!

 

What is the proudest achievement of your career to date?

 

Getting non-analysts excited about data really motivates me and I spend a lot of time trying to make the subject more entertaining and engaging! I have been fortunate to have many great moments in my career, but I was really proud this year when I was giving a presentation (on data, of course!) via video conference to a group of people I had never met before and at the end, they said I’d got them so excited about data that for the first time in their lives they could imagine having a career in data. Job done!

 

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

 

Being a company that employs over 100,000 people in over 100 markets, we have data people all over the world and often in small teams. It’s important that every one of them feels included and knows that they can have a long and fulfilling data career at WPP.

 

For that reason, we are setting up a data buddy and a data science mobility process where people can see where their next career move could be within WPP and select someone to mentor them in either the same or complementary discipline. It’s an informal process at the moment via our community, but we are reviewing options to build out a proper platform for this next year.

 

Our goal is for every data professional in the world to want to work at WPP!

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?

 

Measurement and targeting have always been a key component of marketing going way back to Lester Wunderman defining the concept of direct marketing in the 1950s. However, data is imperfect and a trend to focus on volume, rather than variety or veracity has led many companies down an expensive and stressful path which has compromised some data and analytics capability maturity. Curating and making an inventory of data is really very hard.

 

David Ogilvy has a great quote to summarise this from a creative perspective: “Big ideas come from the unconscious, but your unconscious has to be well-informed or your idea will be irrelevant.”

 

At WPP, we pay attention to the creative duo; this is a magical and inspirational pairing that occurs when creative and data talent work together, each building on the other’s ideas, proof points and ideas about creative transformation.

 

Data variety is front and centre of our data strategy which means that we are democratising hundreds of data sets (and not just to analysts!), some of which seem irrelevant until a different lens is put on them. My favourite example of this is sharing a data set about raptors and whether you would have been killed by one depending on where you lived. “I love all data, but have to admit this is probably pretty useless,” I said during one presentation internally. “Oh no, this is great” said a colleague. “We are just working on a project around Jurassic Park and this data set is perfect.” So you really never know what data set is gold dust!

 

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

 

To foster data literacy and the building of a data-first mindset, we think you need three things:

  1. A data culture which starts in the boardroom. Data needs to have a representative at the table who will support and sponsor investment. This is especially true for data management, making an inventory and curation which is important, but hard to establish an ROI for. Unfortunately, often you only see its value when things go wrong!
  2. Getting clean and varied data sets to the analysts and scientists with the right tools for their job and providing them with the space to be creative.
  3. Making sure that every single person in the organisation can have a conversation about data and AI.

When all three are in place, the opportunities are there for the taking.

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