Battling an unprecedented situation

As COVID-19 hit, a leading grocer struggled with a massive food wastage due to the overstock of perishable items. With customer behavior changing rapidly, it was getting increasingly difficult to forecast demand and stock the right items. Data analysis at the end of July 2020 showed that despite markdowns, inaccurate demand forecasting caused over 30% of food be wasted as products elapsed on their sell-by date.


Finding treasure under pressure

It was ironical the grocery business had built-in a 30 percent buffer for shrink. It was a reality that the business has grudgingly reconciled itself to. As the pandemic increased margin and performance pressures, this buffer was the easiest to capitalize. All that was needed was a data-led approach to trace why and where the shrink could be optimized. Multiple systems delivering disparate data, and much of it inaccurate was spotted as the source of the challenge and handling that first opportunity. This led the data team to take a step back and investigate gaps in their inventory process. The need was for a system that could unify data from disparate sources and analyze it fast, and enable intelligent decisioning, and all of this in real time.

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A fresh view to profitability

Implementing AI/ML in their merchandising and supply chain processes including store replenishment, pricing and promotions planning the grocer was fast harvesting the value of data intelligence. Decision-makers were able to respond to changing demand factors based on real-time relevance courtesy Hypersonix’s highly automated AI-based algorithms. Hypersonix was able to quickly draw correlations between disparate sets of data, using them to plan ordering, replenishment, and shipping activities accordingly. Aligning store ordering plans with consumer preferences through the help of AI/ML helped the grocer reduce waste, drive sustainability, and increase customer satisfaction.


Embracing sustainability with revenue growth

Within a month of implementing Hypersonix, the data processing speed within the company considerably increased, and decision-makers were able to use real-time data to make accurate decisions about markdowns, inventory replenishment, promotions, and more. Overstocks in perishables decreased by 40% across 200 stores, which led to a 30% increase in revenue within the first month.