To increase adoption and traction of analytics, Kmart Australia has hired a group of 10 “data translators” who are entrenched throughout its top three operating areas.
The retailer’s efforts to increase adoption of its Sophia data platform and internal data analytics maturity were on display at an AI event last month thanks to CIO Brad Blyth.
For its analytics capabilities, Blyth claimed that Kmart is constantly engaged in a “three-phase development cycle” that involves “trying to understand the problems and build solutions, scaling that up, and then really attempting to get the value out of whatever we’ve established there.”
He said that the data team has evolved its approach over time, moving away from creating all reports and data models independently to helping teams generate ideas and providing them with self-service tools to create reports on their own.
Additionally, he claimed that the data team had been able to experiment with some of Kmart’s important reports and produce additional value for the company that cannot be obtained by merely reading a report.
In order to test if rostering could be optimised beyond what was achievable with a report alone, Blyth said the data team had taken Kmart’s store rostering report, “which helps store managers identify who they need to roster for shifts,” and run an automated decisioning engine on top of it.
“Store managers are accountable for [rostering] – if they get the roster wrong, that goes towards their KPIs,” he said, highlighting the difficulty of the endeavour. Since they’ve been doing it for a while, they’ve gotten fairly good at it.
As a result, we continued to run the engine, and the six percent rose.
According to Blyth, the engine is an illustration of how the data team can create something once that can continue to produce value over time without requiring the same continuing time and resource commitment.
He claimed, “That’s really driving part of the value rise” for analytics at Kmart, “because we developed something where the value gain was unlocking itself.”
