Building Data Literacy and Demystifying AI

In the recent Data Leaders Roundtable, Di Mayze, Head of Data and AI at the advertising giant WPP discussed how her role helps improve data literacy across 100,000+ people business.

Read the summary of Di’s presentation to learn:

• WPP’s approach to data literacy
• How the company has demystified AI for 50,000 employees
• Pitfalls to avoid and steps to take on your journey towards data literacy

WPP is responsible for the production of one in three ads, the firm also operates media companies across the whole ecosystem.

Di is placed in the head office, and holds a position leading the data and analytics globally, setting the tone for how the WPP agencies should collect, treat and share their data. Her team focuses their work in three main areas:

1. Discovery and curation: rather than focusing on creating a data lake, the team centres their work around people. 
2. Education and empowerment: these two E’s emphasise the importance of not only illustrating the advantages of leveraging an ad-hoc data strategy, but also the value in getting people excited to take part on this journey. 
3. Content and community: data is democratised and made accessible for everyone to join in.

Data catalogue helps to unlock the power of data sharing

Creation of data catalogue allows to unlock and share resources across the huge WPP network of agencies. They partnered with Data World to maximise versatility and analytical blending possibilities.

Data and analytics  leaders across the business take part in collaborative projects and deliver valuable insight from an individual location. Access to this catalogue is granted to everyone, but, in the spirit of reciprocation, agencies are asked to list and utilise data and data virtualisation capabilities. This has brought to the creation of data stories using the information available on the catalogue. 

Since WPP covers a variety of areas ranging from B2B to global markets, it now counts with around 400 data sets. Nonetheless, Di emphasises that power the power of the data set can only be unlocked if applied right.

Boosting data literacy at scale

Upskilling in data is a trend across all industries, and WPP is no exception. Di has focused her efforts in upskilling 5000 data experts, and worked on the AI “demystification”, which was delivered across 50,000 employees. The training programs were developed in partnership with providers such as Oxford University, General Assembly, Microsoft and Coursera. These courses included AI Business School, AI diploma and were specifically tailored to the different teams within the organisation, including the C-suite and seniors.

Community is at the heart of getting people engaged

When it comes to the community, WPP takes an approach that covers various groups of people, and tailors the content to their audience.

In 2020, Di launched the WPP Data & AI network, the initiative which now counts 3000 active members and revolves around the principles of inclusivity and diversity. The aim is to provide a risk-free environment for everyone to experience, connect and expand their data literacy. The program hosts talks, webinars and even data challenges with prizes. 

To cater to the needs of the most senior data leaders across WPP agencies, Di launched the CDOGs. This network is specifically tailored to the Chief Data Officers to feel less isolated, and connect with their peers in other parts of the business, network and learn from each other.

Boosting engagement through creative communication

As creativity is the drive behind the data literacy journey, WPP has partnered with Synthesia – a synthetic media company – to help their teams understand AI and machine learning through educational videos. A welcome side effect of this initiative was also simplified operations and reduced costs (e.g. no need to hire physical actors). A list of all available webinars and learning opportunities can be found on the company’s website.

Four short-term actions to take

Di points out 4 important actions to take in the short term:

1. Onboarding the C-suite: expected yet worth mentioning. C-levels should be invited to community meetings and kept in the loop of things.
2. Finding a way for data people to meet and collaborate: this step is essential to foster a healthy data culture. Di also points out the data available to prove collaboration is a productivity hack, as is skill swapping. 
3. Creating an inclusive environment where “noobs” are welcome: once again, Meyze emphasises the importance of data being accessible and understandable to many.
4. Rewarding the behaviour you seek: positive reinforcement is a great strategy to guarantee the continuous engagement of your teams.

Pitfalls to avoid

Di warns against the following pitfalls:

1. Trying to build everything in the centre: she advocates for a bottom-up and bottom-down approach instead.
2. Assuming everyone knows the basics: everyone within the organisation should be offered learning opportunities on data literacy. Effort should also be put towards clarifying and demystifying data language and making the conversation around data inclusive.
3. Thinking communities can run themselves: there is a lot of behind-the-scenes organisation and production efforts to run events. Proactively investing in these becomes paramount to the success of the operation.

Three long-term actions to take

In the future, Di believes you should focus on the following:

1. Investing in skill and talent, even when ROI does not stack up: it is important to put a solid business case to show even if it is sometimes not easy.
2. Plan for roles changing in the future: referencing WPP 2030 Report, Mayze points out that creativity is bound to play an increasingly pivotal role in data culture.
3. Crowdsourcing: as people value what they help create, it is important to let them create with you.

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