Optimizing Demand Forecasting: How One Online Grocer Reduced Food Wastage by 40%
Optimizing Demand Forecasting: How One Online Grocer Reduced Food Wastage by 40%
40%
reduction in food wastage30%
increase in revenue7%
increase in profitabilityBackground
This online grocer was ready to handle online ordering when the pandemic hit, but unprepared for other challenges such as demand forecasting and being able to stock products intelligently to meet anticipated demand. They needed a system that could unify data from disparate sources, analyze it quickly, and provide actionable insights in real time, making it easy to see where changes could be made to respond quickly to demand.
Industry: Online Grocery
Hypersonix Products: ProfitGPT, Pricing AI
Goals: Accurately forecast demand and determine the right price at the right time to minimize wastage.
Battling an Unprecedented Global Situation
The COVID-19 pandemic disrupted a leading online grocer’s operations and led to unforeseen challenges. Inaccurate demand forecasting and the inability to respond quickly to rapidly changing customer behavior resulted in significant food wastage. With customer behavior changing rapidly, it became increasingly difficult to forecast demand and stock the right items. At the end of July 2020, data analysis showed that, despite markdowns, inaccurate demand forecasting led to more than 30% food wastage as products lapsed on their sell-by date. Multiple systems delivering disparate and inaccurate data hindered the grocer’s ability to optimize their processes and minimize wastage. They were seeking a data-led approach to trace why and where shrink could be optimized.
A Fresh View to Profitability
Hypersonix ProfitGPT enabled the online grocer to unify their data from multiple sources into one single source of truth. The platform was able to quickly draw correlations between disparate sets of data and provide actionable insights that the company could use to plan ordering, replenishment, and shipping activities accordingly. Aligning store ordering plans with consumer preferences through the help of machine-learning and generative AI helped the company 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 increased considerable, 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, leading to a 30% increase in revenue within the first month and a 7% increase in profitability.
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