The growth in retail data is growing at a phenomenal rate. Every second the world’s data increases by three times the amount currently held in the print archives of the US National Library of Congress. While most of it is largely irrelevant, you need excellent contextual awareness and retail analysis filtering techniques to quickly disentangle the important things from the background noise.
Traditionally, businesses have often acted based on gut-feel or rule-of-thumb, ignoring relevant statistical facts or analysis. Instead people opt for accessible hindsight which may not tell the full picture and is often biased. Businesses are complex, interconnected and interdependent operations require us to consider many things at once. Assortment planning, space planning and merchandise placement decisions need to be managed simultaneously. Simple heuristics aren’t enough.
The output of analytics and insight programmes has often been designed for the few rather than the many. The cost of entry into an organisation’s data and insights is often too high an intellectual price for most to pay. The predictive analytics modelling is often complex, of course. But the outputs need to be simple and actionable if they are to be useful for retail execution purposes.
The national arm of a leading global retailer identified the key drivers of sales performance to prioritise head office and store action to grow sales
A UK brand owner identified a £15m sales opportunity for one category in one retailer through the optimisation of its assortment planning software
A UK retailer estimated a £19m improvement in their waste bill through the identification and creation of driver-centric action plans