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Revolutionising retail: The use of AI in workforce management

In the realm of Retail, particularly within fast-moving consumer goods and fast food sectors, maintaining a sustainable profit margin is key for business continuity — meaning that at the best of times, it is crucial to manage costs.
Luke Seocharan, workforce management specialist at Altron Systems Integration. Image supplied
Luke Seocharan, workforce management specialist at Altron Systems Integration. Image supplied

In tough times, or during phases of economic headwinds, managing costs becomes critical. If we consider that labour is one of the single biggest costs for retailers, it is fair to suggest that one of the most important considerations for any retailer is optimising it’s workforce management strategies.

The advent of artificial intelligence (AI) and machine learning (ML) has ushered in a new era of precision in workforce management, with platforms such as UKG Pro Workforce Management (WFM) leading the way in transforming forecasts into meticulously tailored staffing strategies.

When implemented by a skilled partner who’s an expert in the field, the power of harnessing tools such as these dramatically changes what is possible in the pursuit of efficiency gains and, importantly, cost savings.

The impact is substantial. In an industry where every cent matters due to thin profit margins, even a modest percentage reduction in payroll expenses translates to millions of rands in monthly savings.

Tech-driven forecasting, highly accurate and facilitated by platforms like UKG Pro WFM, coupled with subsequent workforce optimisation, fundamentally enhances retailers’ bottom lines while concurrently elevating customer service standards.

Consider the example of one of our clients, which has 300 stores, leveraging the machine learning algorithms of UKG Pro WFM that we have implemented. These algorithms analyse sales patterns and can predict future trajectories up to a year in advance.

The innovation doesn't stop there; it delves into the nitty-gritty of labour management, for example, predicting the number of cashiers needed, the skills required, and even which staff members need to be present at certain times, even looking at which are due time off based on the country’s labour laws.

Naturally, the platform offers a full, 360-degree workforce management capability - it’s just that as more advanced technology becomes available, its predictive nature takes things up a notch.

The success of an implementation like this lies in its ability utilise data in a meaningful way, in this example, using data to convert forecasts into tangible human resource management. Utilising AI in workforce management goes beyond the generalised workforce management landscape, incorporating intricate details such as SASSA payment days, weekends, public holidays, events such as Black Friday, and more.

The system is so advanced that it not only ensures compliance with labour laws but also introduces a level of flexibility that allows for efficient adaptation to address any unforeseen or sudden scenarios.

The system, across various customer integrations, excels in the delicate balancing act between the Labour Department prescribed hours, contractual hours, and the dynamic needs of the business. Imagine a scenario where a cashier is needed for only six hours on a regular weekday but for 12 hours on a busy Friday.

A retailer needs to be able to plan for and handle this with finesse. When a business gets this right, the result is not only better customer service but also increased productivity and cost savings.

As with most discussions around digital transformation, the goal is to empower managers with data-driven insights. By automating the scheduling process, it frees managers to focus on more value-added tasks.

It means managers can now spend an hour as opposed to a day on scheduling shifts, and spend the rest of their time managing the store. The system then, being a wholistic workforce management platform, allows for strategic continuous staffing management using AI and data driven insights for managing exceptions on the system, as well allowing timeous change functions allowing managers to effectively manage variable events and outcomes such as identifying who performs more efficiently during peak hours or who can’t work a shift because of a health issue, or any such variable.

In a pioneering use case in Switzerland, we have introduced a function in UKG Pro WFM that enables staff to accept, request, and swap shifts using their mobile devices. This not only adds a layer of convenience for employees but also ensures that staffing remains optimal, even in the face of unforeseen circumstances.

Perhaps the most exciting development in the race to optimise workforces is the investment by Kronos itself in diverse algorithms tailored for specific industries. A retailer will want an algorithm and learned insights that are relevant to retail and not, say, manufacturing. The same will be true of any industry.

It is clear that the merging of AI, forecasting and workforce management is transformative for businesses, however, it is crucial for retailers to work closely with experienced partners who understand the intricacies of retail and the capabilities of platforms such as UKG Pro WFM.

About Luke Seocharan

Luke Seocharan, workforce management specialist at Altron Systems Integration
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