Max Kelsen serves automated rostering to Domino’s Pizza

Max Kelsen serves automated rostering to Domino’s Pizza

Solution uses Amazon Web Services’ (AWS) machine learning

Credit: Dreamstime

Max Kelsen has “taken out the guesswork” of staff rostering for Domino’s Pizza using Amazon Web Services’ machine learning technology.

The Brisbane-based provider deployed the automated Cognitive Rostering system, which uses machine learning to create rosters based on previous and predicted sales.

Coming a month after Max Kelsen achieved AWS’ machine learning (ML) competency status, the solution covers 20,000 staff across 800 stores in Australia and New Zealand.

“Previously, our franchisees and managers built rosters manually – relying on anecdotal knowledge about which days were busier or quieter and how many team members were required for each shift,” explained Michael Gillespie, Domino’s chief digital and technology officer.

“This was a time consuming process and not always 100 per cent accurate. Cognitive Rostering takes the guesswork out of it and helps our stores roster appropriately for forecasted sales. That means no more being understaffed on a busy night, or overstaffed on a quiet night.”

Built using software from rostering technology provider Tanda, the platform took a year to roll out for the pizza giant and work remains ongoing. 

Services also used by the system include Amazon SageMaker, Amazon Elastic Kubernetes Service (EKS), and Amazon Simple Storage Service (S3).

“Artificial intelligence and machine learning solutions, developed in Australia, have the potential to change business models, because they can play a key role in transforming the entire value chain of retail businesses, from predicting sales, forecasting staff and improving customer satisfaction and loyalty,” Max Kelsen co-founder and CEO Nick Therkelsen-Terry said.

The deployment follows Max Kelsen joining a project aimed at analysing the behaviour of COVID-19 in intensive care patients using AI.

In collaboration with the University of Queensland, Max Kelsen will be applying AI to enable the project consortium to analyse millions of data inputs about patient responses to the disease to rapidly improve the understanding of risk factors, treatment efficacy strategies and other important information.

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