I studied air transport management and economics and spent a few years between Madrid and Barcelona in the airline industry. I came to London and joined easyJet in 2006 as a yield developer, working on the R&D side of the pricing engine.
Back then I was quite surprised at how inefficient companies were at creating value with their data so in 2009 I did an MSc in data mining. My final project was a neural net, which learned from our pricing experts and brought a major productivity improvement and many millions of pounds. I took on the responsibility of all the pricing engine development in 2012 and led the team into applying data science techniques in our pricing area, with results still ahead of many airlines today.
In 2015, I became head of data, tasked with creating the data capabilities we had on the pricing side, going from a three-people team to a total of 40 by the time I left. In early 2019, I took on my current role, managing a highly talented team of over 70, in charge of reporting, analytics and data science.
As data practitioner is difficult to single one out, I have very fond memories of particular projects I coded and implemented, and how I solved a particular technical challenge and the benefit for the company. I have found that solving hard problems that have a meaningful impact is usually a good motivator for analysts and data scientists. But my proudest achievement is that my team and I created the pricing engine that powers easyJet.com; that’s a real example of data in action driving great value for the company.
Throughout my career I have met amazing people, so it is hard to single out one. However, during past year I have had the fortune of working more closely with Peter Duffy, CEO of Just Eat during 2019 period, and witness a perfect example of a truly visionary, inspirational and people-oriented leader.
Yes and no, I wasn’t expecting a year of change in which I would leave an industry, aviation, where I had spent 17 years and try something different. But the surprising bit was that things were far better than I’d imagine, so it was brilliant. It hasn’t been a stroll in the park, but I have landed in a great place, with great people, and highly capable team, and I think I’ve managed to make my contribution to Just Eat’s success.
The value of data is clear and many organisations had a go at their own data revolution with more or less success, we have learned how to light on the fire. But there are many cases of wasted resources or promising beginnings crippled by technical debt. Thinking about what is coming the next ten years, we are still in pre-historic times and we need to learn how to master the fire. In the immediate future, the focus will be more and more on “data ops” or how you set up a lean production line, a data factory, of data products that continuously enhance and transform your organisation in a sustainable way.
History has shown us that technology multiplies human capabilities. In a data context, during the last 100 years, we have gone from adding numbers on paper to spreadsheets chaining operations to create sophisticated decision support models. Today, we are in a more mature stage of the same technological progress. During the last three decades, we have advanced significantly on the decision automation side, but again, these are just tools which will enhance our capabilities. I don’t see a future of just machines taking decisions but of humans and machines working in partnership to deploy extraordinary capability
I think Just Eat is in a good position. We have a quite advanced data platform where analyst, data scientist and other business stakeholders can satisfy their data needs. And we have successfully embedded data products at the core of many processes in the organisation but “doing data” implies business transformation and this also affects your tech stack, no matter how mature or experienced the organisation is. Data is something new and processes, design principles and technologies need to leverage our data assets.