SA chicken empire Hungry Lion has brought on Stellenbosch-based AI startup Predictive Insights to reduce errors in demand forecasts and staff scheduling.

Predictive Insights was founded by Richard Barry, Rulof Burger, Neil Rankin and Kevin Kotze in 2017 to improve the products, services and strategy of prospective clients through data science.

The challenge for restaurant managers

Founded in 1997, Hungry Lion is a market leader in the fried chicken fast food sector with 230 stores across Africa.

“We simply didn’t have enough business intelligence to predict sales on a particular day for a particular store,” says Gideon Jacobs, Business Development Manager at Hungry Lion. “We have 230 stores across multiple countries, all with varying sales figures. No person can predict that accurately – but a machine algorithm can. It looks at the historic values, actual performance, as well as behaviour and economic insights to predict sales volumes.”

Combining human and machine intelligence to improve accuracy

Hungry Lion brought in Predictive Insights to compliment the human element with machine learning algorithms that reduce prediction inaccuracies. The startup developed a process that extracts point of sales data, staff scheduling data and clock-in data (showing the time staff arrived and left and when they took breaks) from each of Hungry Lion’s branches daily. The system then checks the data for any anomalies including peculiarly slow sales, missing or incomplete clock-in data and incomplete schedules.

The system communicates this to Hungry Lion and imputes reasonable values for the data where necessary. Finally, it combines this with historical data and a curated dataset containing information such as SASSA payment dates, instances of load shedding and weather.

The algorithms combine machine learning methods and economic models of consumer behaviour, calibrated to aggressively learn about any new trends in behaviour, including changes expected in various COVID-19 lockdown levels. The data is used to predict daily sales for each branch for the next five weeks.

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