Cognitive Rostering uses machine learning to help Domino’s franchisees and managers build accurate rosters based on forecasted sales – taking into account things like public holidays, sporting events, marketing activity, historical data and seasonal changes.
Domino’s says the solution, which leverages Amazon Web Services machine learning, significantly improves the accuracy of sales predictions compared to historical averages.
Domino’s Group Chief Digital and Technology Officer Michael Gillespie said the pizza company was always looking for ways to make store operations easier and more efficient.
“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. This was a time consuming process and not always 100 per cent accurate,” Gillespie said.
“Cognitive Rostering takes the guess work 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.
“With labour being one of our highest costs in store, it’s important that we are as accurate as possible when it comes to rostering.”
CEO and Co-Founder of Max Kelsen Nick Therkelsen-Terry said “there’s never been a better time to invest in machine learning and artificial intelligence”.
“Max Kelsen was founded on the belief that machine learning and artificial intelligence, applied by experts and with a focus on key business outcomes, can drive competitiveness,” Therkelsen-Terry said.
“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.”
The collaboration between Domino’s and Max Kelsen utilised a range of Amazon Web Service services, including Amazon SageMaker, Amazon Elastic Kubernetes Service (EKS), and Amazon Simple Storage Service (S3).
Karl Durrance, Director of Enterprise for AWS Australia and New Zealand said: “Machine learning solutions such as Amazon SageMaker can help organisations like Domino’s to leverage the power of their data to uncover critical insights that enable them to plan in-store operations and create new solutions that delight their customers”.
“We are excited to continue collaborating with Max Kelsen and Domino’s to deliver innovative solutions that drive better business decisions and meet customer demand in Australia and New Zealand.”