Headline Partner

Gabriel Straub, Chief Data Officer, Ocado Technology

Describe your career to date

I studied Mathematics at Cambridge and then started my career as a management consultant in the Middle East and Germany. I returned to the UK to do my MBA and then joined Tesco to build up the Data Science Function. We worked on anything from recommendation systems and search to last mile optimisation, price optimisation, and space optimisation.

I then spent some time at notonthehighstreet as Data Director before joining the BBC to help them get more comfortable with machine learning (ML). There, I launched the first fully algorithmically driven BBC app and the team then built recommendation engines for the big BBC products (News, iPlayer, and Sounds). Our proudest moments were getting the news colleagues comfortable with algorithmically driven news recommendations and that we ended up replacing the commercial recommendation engine on iPlayer and Sounds with the ones built by us.

In 2020, I joined Ocado where I am now the Chief Data Officer, looking after a team of about 140 people and being responsible for making data and ML a compelling competitive advantage for us.

How are you developing the data literacy of your organisation, including the skills of your data teams and of your business stakeholders?

We are doing different things for different stakeholders based on the needs and the maturity and capability of that area of our business. In general, we try and remove the fear that some people have of data by making it fun and accessible. We also put a lot of effort into making improving the data utility by increasing the quality and by making it more easily accessible and discoverable. Then we put a lot of effort into clarifying the operating model around how analysts should work with the product organisation. Our aim is that most data questions can be self-served and that analysts and data people become strategic partners that then help answer the really difficult questions by bringing a data lens to the conversation.

What stage has your organisation reached on its data maturity journey?

We have developed our own maturity assessment that covers six dimensions and four levels for each dimension. This allows us not only to identify the maturity but also what drivers we should be putting most of our efforts in. We then assess ourselves regularly, not just as the whole organisation, but at a level within our organisation that we call streams. What has been interesting in doing it this way was that it allowed us to identify which areas are good at different tasks and where they might need help. We found that, often, what areas are good at differs, so we are able to take learnings from one part of the organisation and apply them to another part.

Gabriel Straub
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