Product design question

As a product manager at Walmart, how would you use AI to optimize in-store and online inventory management to reduce stockouts and overstock issues?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Ability to apply AI to a concrete, measurable operations problem across two channels, online and in store.

Separate the two contexts: in store shelf level inventory versus online fulfillment center inventory, since data and failure modes differ.
Identify the core prediction task: demand forecasting per SKU per location, factoring in seasonality, local events, and promotions.
Propose using computer vision or IoT shelf sensors to catch shelf level discrepancies faster than manual checks.
Propose dynamic reorder triggers based on the forecast plus real time sell through, rather than static reorder points.
Define success with paired metrics: stockout rate and excess inventory carrying cost.
Confirm whether the focus is grocery or general merchandise, since forecasting differs significantly.

Separates in store and online inventory as different problems with different data sources.
Proposes a real detection mechanism for the notoriously hard in store stockout visibility problem.
Uses paired metrics to show awareness that over correcting one creates the other.

Treating online and in store inventory as the same problem with the same fix.
Optimizing only for reducing stockouts without acknowledging the overstock cost tradeoff.

How would you handle perishable grocery items differently from general merchandise?
How would you validate the forecasting model before rolling it out chain wide?