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Hungry Lion reduces demand forecasting errors by 40% 

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. Restaurant managers have to juggle various duties from determining customer demand to managing and scheduling staff. Before partnering with Predictive Insights, Hungry Lion relied on a combination of instinct, experience, and pure guesswork to project sales volumes and scheduling staff. This resulted in demand forecasting errors of up to 24% - branch managers were off by more than 40% for every one in five sales predictions made.

Economists as data scientists

12 February 2021

 

Hal Varian, the chief economist at Google, is widely credited with suggesting that the use of statistics in data science would be the ‘sexiest job in the 21st century’[1], and it is worth noting that a number of prominent members of the data science community have economics backgrounds (John Akred from Silicon Valley Data Science[2], and Jenny Bryan[3], now at RStudio, are two who come to mind).

The challenge of forecasting sales, stock and staff during COVID-19

27 January 2021

 

There is no tougher challenge than seismic environmental unpredictability for retailers, restaurateurs and the hospitality trade, who are left to manage and make a best guess for labour scheduling, sales forecasting and stock forecasting, just to survive.

Machine learning in the workplace

18 January 2021

 

There are several common problems with analysing the data routinely collected by companies: measurement error, missing data values or variables, sampling that is non-random or not representative of the population of interest, and the fact that correlation does not necessarily imply causation. These are problems that require careful consideration before implementing a statistical analysis, otherwise the model can provide very misleading answers.

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Neil Rankin

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