DISCUSSION
Does retail need a data-based rebuild?
Written by RetailWire Staff
Brad Banducci (center) and Amitabh Mall (right) of Woolworths at NRF 2023 – Photo: NRF
Australian supermarket Woolworths has succeeded in using analytics to inform and redesign a number of processes core to its business in a short amount of time. In a session at the NRF 2023 Big Show, Brad Banducci, chief executive officer and managing director at Woolworths, and Amitabh Mall, chief analytics officer at Woolworths, explained what the retailer has been doing with its analytics and why other retailers should do likewise.
“We are not about incremental changes,” said Mr. Mall. “We are about looking at the core processes and fundamentally trying to reimagine it.”
Woolworths sees a place for such technology, not just for streamlining customer experience, but for other areas of the business such as buying and merchandising, store ops, replenishment, supply chain and support.
Mr. Banducci and Mr. Mall gave a couple of examples of areas where Woolworths has applied analytics to reimagine core processes.
- Streamlining holiday hiring: Before the data-driven rethink, Woolworths store managers were looking at data points like labor needs, their previous year’s holiday hiring numbers and their budgeting for and hiring of tens of thousands of temps accordingly. After the rethink, the company utilized data on departmental business expectations and skillset needs, implemented predictive modeling to assess potential attrition and churn, and gave store managers more robust, granular information. This gave managers the knowledge, for instance, to ask particular workers if they would work more hours instead of hiring seasonal temps. The retailer reduced seasonal hiring by 50 percent year-over-year, even as business volume increased.
- Reducing energy usage: Through a basic IoT control center that turns things off, the chain reduced energy consumption by one-half percent.
- Pricing optimization: Woolworths formerly ran deals based on a combination of previous sales data and supplier suggestions on pricing, sometimes overwhelming category managers with data. Analytics allowed the retailer to look deeply at how specific promotions performed and predict how they might perform under different circumstances, giving category managers actionable insights.