Retailers have become remarkably adept at absorbing complexity. They adjust staffing around changing demand, build inventory and fulfillment processes to account for uncertainty and develop rules, buffers and manual interventions that keep the business running when the ideal answer is difficult or impractical to find.
Over time, however, those accommodations can become so embedded in the operation that their original purpose is easy to forget. A process that consumes dozens of hours each week becomes simply how scheduling gets done. Extra capacity becomes part of the plan. A compromise introduced because available technology could not manage all the variables becomes a permanent operating assumption.
That ability to adapt is essential in retail, but it can also make inefficiencies difficult to see. Some of the most expensive problems may be the ones an organization has become so accustomed to managing that it no longer thinks of them as problems at all.
When a workaround becomes the way you work
Retail decision-making has always involved balancing competing priorities. A workforce schedule may need to account for employee availability, customer demand, service levels and business policies, while inventory decisions must consider where products are likely to be needed, how quickly they can be replenished and how much working capital the business is willing to commit. Fulfillment adds another layer of choices involving capacity, timing, transportation and cost.
As these decisions become more complex, organizations naturally find ways to make them manageable. They may simplify the problem, limit the number of scenarios considered, rely on rules developed through experience or dedicate more people and time to producing a workable answer. These approaches can be entirely practical, but the compromise they represent may remain in place long after the technology available to address the problem has changed.
Advances in optimization are giving retailers new ways to revisit some of these difficult decision-making problems. Quantum-hybrid optimization combines quantum and classical computing to help retailers evaluate complex decisions, balancing priorities such as cost, service and profitability while accounting for operating constraints.
The opportunity is not to replace the systems retailers already depend on. Quantum-hybrid applications can work alongside existing planning and operational systems, with implementation focused on modeling the target problem, connecting the necessary data and integrating optimized decisions into established workflows.
Reconsidering an 80-hour weekly task
Pattison Food Group, Canada's largest provider of food and health products, faced this kind of challenge in its e-commerce delivery operation. Creating weekly driver schedules across more than 100 stores was a manual process handled by three to four schedulers, who built schedules province by province.
The work required about 80 person-hours each week.
Pattison worked with D-Wave to develop and deploy a quantum-hybrid auto-scheduler for the operation. The weekly scheduling effort dropped from 80 person-hours to 15, an 80% reduction in time spent scheduling, while consistently meeting a 95% demand-fulfillment threshold across more than 100 stores. The application is in production today.
The significance of the example goes beyond automating a time-consuming task. The existing process was already producing schedules and supporting the business. The opportunity came from reconsidering whether the amount of manual effort required to make those decisions still needed to be accepted as part of the operation.
When accepted costs become competitive costs
Retailers often face many of the same pressures around labor, inventory, fulfillment capacity, transportation and shifting demand. Competitive advantage can emerge from how effectively each organization makes decisions within those constraints.
A process that requires less manual effort can free employees to focus on higher-value work. Better scheduling or allocation decisions can improve how existing resources are used. At retail scale, improvements that appear modest in isolation can become more meaningful when they are repeated across stores, employees, orders and operating cycles.
This changes how familiar inefficiencies could be viewed. An operating compromise may remain perfectly reasonable when better alternatives are not available. But once another retailer finds a way to make better decisions under similar constraints, what once looked like a shared industry limitation can become a source of competitive disadvantage.
This perspective makes processes that already appear to work worth another look. Retail leaders can examine where employees spend substantial time compensating for complexity, which rules or buffers were created because the business once lacked a practical way to consider more possibilities and which trade-offs have remained largely unchanged as technology has advanced.
Retail will always involve uncertainty and constraints, but some long-standing assumptions deserve to be reconsidered. The opportunity may be less about finding entirely new problems to solve and more about recognizing that a problem the business learned to live with does not necessarily have to remain that way.
Read our blog to learn more about how to determine if quantum optimization is a fit for your business.
