EasyJet's Holistic Data Science Operations Model - From Ideation to Scaled Product Delivery
The data scientist profession has been dubbed as "The Sexiest Job of the Twenty-First Century" by Harvard Business Review. While some businesses thrive by capitalizing on data's transformative power, many more succumb to the hype as a result of a failure to manage and expand their data strategy. The mismatch of stakeholders has been acknowledged by enterprises as the driving force behind poor performance and lack of impact. Such issues can be directly traced back to process flaws and organizational structure, which result in long model delivery periods with little impact. The EasyJet Operating Model addresses the lack of understanding of end-to-end processes for implementing data science solutions and bridges the gap between accelerating the data science discipline and the absence of some of the required stakeholders and governance that would allow a proactive rather than reactive approach. By fostering a collaborative environment between business and data science, EasyJet was able to take a rigorous approach to iterative data science initiatives. The EasyJet Data Science Ops model is comprised of end-to-end documentation that describes a timeline of procedures and actions to be carried out, allowing key stakeholders to influence data product development in order to generate incremental business value. While transitioning from a "lean" start-up to a mature data-driven organisation might take time, the EasyJet Data Science Ops Model accelerates the process and guides numerous teams through the transformative "marathon" to generate momentum toward the goal of developing a strong data-driven company where data solutions can be produced more quickly and with greater scalability. Working with numerous stakeholder groups over time enables EasyJet to achieve its goal of becoming the world's most data-driven airline. The EasyJet Ops Model reveals areas where the aim is being missed and provides an honest appraisal, allowing EasyJet to take solid steps to improve the system. The efficiency of the EasyJet Ops Model is based on the involvement of all necessary stakeholders while ensuring the necessary support and governance are in place to guarantee that it is suitable for its purpose (from both a functional and non-functional perspective).
Ioannis has worked as an ambitious data scientist expert and a trusted member of EasyJet's Data Science & Analytics community since 2019. In his current role as a Lead Data Scientist, he is on a mission to support EasyJet in reaching its ambition of becoming the world's leading data-driven airline. The famous Sherlock Holmes quote—"You see, but you do not observe"—was enough for him to end up holding an M.Sc in Data Science and counting over three years of experience in the field. Analogously to Sherlock Holmes and John Watson, Ioannis teams up with EasyJet's Digital, Customer & and Marketing departments to form an A-team that thinks beyond the obvious and delivers data-driven solutions under uncertainty through effective data products.