Operations at Tesco have historically been quite manual with varying amounts of analytical knowhow applied. As data science and big data technology becomes more embedded into the way we work, this is shifting to centralised solutions at scale. This presents challenges, but also large benefits for producing national, and even international level solutions. We present a couple of examples of how we implement large scale solutions that are now embedded into the operations of Tesco.

• Tesco relies on having accurate forecasts to power all parts of its business. We will talk about how we built a single framework for building and testing thousands of forecast models in parallel using PySpark.
• Recommendations help to reduce friction by helping customers find what they want faster. We will talk about our problem statement, how we built a generic framework to address any recommendation problem and finally we will illustrate it with an example.