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Fast food chicken giant, Hungry Lion, reduces demand forecasting errors and improves staff scheduling 

10 June 2021

With 230 stores across South Africa and southern Africa, Hungry Lion needed help to forecast demand and manage staff schedules at their fast food chicken outlets.

Most managers, especially in the hospitality and retail sector, have their hands full juggling various duties from customer satisfaction to staff performance, leaving little time to focus on demand forecasting, stock planning and staff scheduling. They often rely on instinct, experience and guesswork to project sales volumes.  


Hungry Lion implemented Predictive Insights to improve demand forecasting and address staff scheduling challenges, by combining economic and behavioural insights with machine intelligence to improve accuracy. Hungry Lion saw a significant improvement. Demand forecasting errors were improved by 40% and the cost of staff scheduling errors were reduced from 34% to 20%.


Gideon Jacobs, business development manager at Hungry Lion said: “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”. Gideon concluded that,  “AI decreases the risk of branch managers attempting to predict sales, stock and staff volume especially during turbulent times.”

Read our full case study which reveals how Predicative Insights 

 

Gideon Jacobs, business development manager at Hungry Lion said: “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”. Gideon concluded that,  “AI decreases the risk of branch managers attempting to predict sales, stock and staff volume especially during turbulent times.” 

Read our full case study which reveals how Predictive Insights applied AI and behavioural insights to:

  • Improved margins of error for demand forecasting by 40%

  • Reduced the cost of staff scheduling errors from 34% to 20%

  • Reduced wasteful spending on the wage bill by 14%

Read the full paper here.

CONTACT US

Neil Rankin

First Floor, Rhino House
23 Quantum Street, Technopark
Stellenbosch, 7600
South Africa