Danilo Sato, head of data and AI services UK and Europe, Thoughtworks UK
Describe your career to date
I come from a software engineering background and got my Master’s degree by studying the impact of metrics on agile development methodologies. That is how I found Thoughtworks, one of the agile pioneers in our industry and what attracted me to join in 2008. For the past 15 years, I’ve had the opportunity to work with clients in the UK, Europe, North America and Brazil across many industries, including financial services, healthcare, telecom, media, automotive, retail and consumer product goods. Throughout my career I’ve been a coach, software and data architect, consultant and trainer. I’ve delivered many projects, where I’ve grown from leading teams to leading our larger accounts.
I had a year of ups and downs in 2014: I lost my father, but I also had the chance to move back to Brazil for six months and join our ‘office of the chief technology officer’. During that year I published my book ‘DevOps in Practice’ and we refined Thoughtworks’ technology strategy. One of the key initiatives was to bring data into our DNA and our chief technology officer Rebecca Parsons asked me to lead the initiative.
From 2015 onwards, I shifted my focus to data and machine learning, helping to build our internal community, growing our capabilities and creating the channels to facilitate networking and knowledge sharing across the globe. When Thoughtworks decided to bring more structure to our external offerings in 2020, my role as the head of data and AI services for the UK was expanded to include Europe as well.
What key skills or attributes do you consider have contributed to your success in this role?
First of all, my background as a practitioner and my 20-plus years of experience has helped me build a global network and develop a deep understanding of Thoughtworks’ clients, partners and, of course, employees. That has enabled me to establish our data and ML community from scratch. Also, my passion for sharing our lessons with the industry and constant pursuit of excellence inspires others to follow the same path.
What level of data maturity do you typically encounter across your client base and what tends to hold this back?
We help clients with a wide spectrum of maturity, from late adopters that are looking to catch-up with the industry to companies that are already using data and AI in many places.
For the late adopters, the challenge tends to be around improving overall data literacy to understand the value data can bring to the organisation and to justify investments to build their foundations. A good pattern here is to develop a proof of concept and a minimum viable product to quickly demonstrate the benefit in a small scale, and then scale out from there.
For the high maturity clients, the challenges are usually around facing growth issues or driving data governance concerns across the organisation. Sometimes they are able to achieve early success in a few business units, but because they developed different data architectures and processes there becomes a struggle to interoperate and share data more easily. Our preferred approach in this situation is to bring the principles of data mesh, as a distributed sociotechnical approach to governing, sharing and accessing data at scale. The work we’ve been doing with ITV in this space has won the 2022 DataIQ Award for the “shared data, shared culture” category.
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