How Big R is Implementing AI with RANDEM-ED
We recently announced the launch of our OMS AI solution, RANDEM-ED, and are seeing promising results. Big R, an OMS client of ours for nearly 4 years, has been a pioneer in embracing RANDEM-ED and has seen strong results.
BigR already uses our full OMS product suite, but like any business with 50+ store locations, things change rapidly. They faced daily operational friction due to complex inventory movements, shipping methods, and an inability to obtain actionable, real-time inventory data. They needed a way to transform the retail operations - How did we do this together?
The Setup: Diagnostic First Approach
We didn’t just turn the AI on and hope for the best. When we built RANDEM-ED, BigR was one of the first clients to undergo our detailed AI Readiness Diagnostic.
We dug into their operations to understand their readiness and identify the biggest “blockers” their team had to untangle daily.
We paired this with our AI governance processes to ensure the implementation was secure, safe, monitored, and effective. This then aligned with our 3 phase systematic AI implementation approach based on Phase 1. RANDEM-ED "the Doer" - Phase 2 RANDEM-ED "the analyst" - "Phase 3 RANDEM-ED “the strategist"
Phase 1 Results: The “Doer”
Since releasing RANDEM-ED, BigR has fully leveraged its capabilities. The results speak for themselves:
⯈The Outcome
This was only possible because of our controlled operation blueprint - with a key module of this being the training and coaching of RANDEM-ED's
new colleagues at Big R. We strictly monitored how RANDEM-ED performed tasks, allowing it to relearn immediately when new requests were made.
⯈The Verdict
Don’t just hear it from us. Here is what Christine Pittman, Group Head of E-commerce at BigR, had to say:
