Coping with demand uncertainty to manage retail outlet profitability

Dynamically manage staffing levels and job assignment at retail or foodservice chains using real-time data and self -adjusting algorithm modelling

With competition intensifying and customers expecting ever-higher service levels, many retailers are now looking for new ways to further improve productivity while enhancing customer service.
Although lean activities have been implemented during the last decade, achieving everyday efficiency improvements, retailers are always looking at overcoming top performer’s labour productivity and customer service, as a key lever for the future success.
Building a store digital twin helps to match store operations with demand and customer expectations under several scenarios, to create some algorithms to dynamically manage staffing levels and job assignments based on real-time store activity measurements, focusing the employee attention on the customer experience while improving efficiency operations.

From navigating uncertainty to managing information: A data-driven workload scheduling

Representing the complexity in the physical world allows to (re)imagine the operating model to adapt to the changing circumstances, evaluating “what if” scenarios analysis that will lead practical and detailed discussions about which store activities could be improved, where service-level targets could be relaxed / improved and how many employees will be needed based on an accurate demand / operations knowledge.
This knowledge is translated into adaptive algorithms, that provides insights / recommendations / orders about job assignments based on real time store activity data.

Becoming more efficient while improving customer service

The deployment of real-time job assignments & staffing data driven decision taking, based on adaptive algorithms, allows at retail / food service chain, overcome traditional people management paradigms by
- Flexible workforce: the right employees are working at the right times, performing the right tasks by leveraging workload volumes.
- Activity-based data-driven workload allocation based on the right customer service level / cost ratio by providing multi-skilled employees
- Matching store employees’ working hours to a changing workload by providing shared employees by store.
- Ensure sustained store productivity, customer service, and employee satisfaction, all while keeping labour costs firmly under control.

Creating impact

The implementation in a foodservice chain of this way of working, in less than 6 months, achieved sustainable improvements.

The next future

What if having a virtual store manager providing instructions to employees, adapting its real-time decisions to the changing environment?

Coping with demand uncertainty to manage retail outlet profitability
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