The retail giant has been using Matlab modelling tools from MathWorks to simulate performance of its distribution depots based on four years of sales data held in a Teradata data warehouse.
Because a significant proportion of capital is tied up in stock held in depots, for example, the onus is on supply chain management to minimise stock levels. Feeding demand forecasts into the model showed where stock can be optimised.
It is just one of the projects executed by an analytics team, which has grown from five to 50 people over the past six years.
The group also used regression testing to understand the links between weather data and sales patterns. Factoring weather into Tesco’s demand forecasts has helped avoid having too much or too little stock, saving £6m each year. Similar techniques have been applied to understanding the demand for special offers, cutting out-of-stock by 30% on these items.
Meanwhile, Tesco has also overhauled discounting of food towards the end of its shelf-life. Previously left to managerial judgement, algorithms built by the supply chain analytics team now produce discounts transmitted to handheld devices in-store. This alone has saved £30m of wasted stock.
This series of projects has helped the analytics team gain the ear of the top management team, allowing it to build on its approach of measuring, modelling, testing and acting.
Tesco programme manager of supply chain development Duncan Apthorp said: “We have a proven track record of success that means that we have access to some very senior people.”
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