Managing Labor in Retail Stores and Supply Chain
As per the National Retail Federation, labor costs account for roughly 10-15% of sales in the U.S. retail sector, making it extremely crucial to profitability and overall customer experience. The heartbeat of every successful retail operation isn’t just its products or pricing—it’s the people. With over 14 million employees working across a million stores in the U.S., labor is not only a significant cost but also the driving force behind customer satisfaction. The quality, availability and training of the staff can make or break a shopper’s journey, highlighting the need for retailers to balance efficiency with empathy. Managing people, unlike inventory, requires a deeper understanding, blending technology with a human touch to ensure employees and customers feel valued at every step.
Recently, we hosted a webinar in conversation with Dr. Ananth Raman, UPS Foundation Professor of Business Logistics at Harvard Business School and Strategic Advisor at C5i, and Manish Srivastava, Global Head, Decision Intelligence Advisory at C5i on Challenges and Opportunities in Managing Labor in Retail Stores and Supply Chain. We explored how blending AI insights with human expertise can elevate retail operations and create a seamless customer experience. We also learned how empowering store managers, with the right tools, can make all the difference in today’s ever-changing retail world.
Let’s delve into the key challenges in managing labor, the role of store managers and optimizing AI and GenAI into the retail and supply chain.
Significant Challenges in Retail Labor Forecasting
One of the biggest challenges in retail is predicting the staff strength needed, given the unpredictable nature of customer traffic. Store managers are often faced with balancing labor against fluctuating demand, which can be affected by everything from local events to weather patterns. While technology offers predictions, it often misses real-time factors like last-minute promotions or specific store issues, leading to either overstaffing or understaffing— which impact profits and customer satisfaction.
The above graph highlights this challenge- While yearly labor forecasts have a low error rate (less than 1%), errors can skyrocket up to 50% at the hourly level, making short-term staffing extremely uncertain.
On the other hand, retail labor is notoriously unstable, with nearly half of the new hires leaving within their first year, as shown in the top right graph. Lateness and absenteeism make things worse, with about 10% of workers failing to show up for their shifts. Challenges such as high turnover, lateness and absenteeism create constant disruptions, making it difficult for store managers to ensure smooth operations in an already volatile and unpredictable environment.
After discussing this, the webinar took the course of exploring the role of data in retail labor productivity.
Data-Driven Exploration of Retail Labor Productivity
Recent research has delved into retail labor productivity using an extensive dataset of over a trillion shifts from major retailers. This data captures the nuances of each worker’s tasks and shifts, providing a deep understanding of how stores manage labor in challenging environments. The ongoing research, led by Caleb Kwon (UT Austin) aims to apply the same academic rigor used in studies of retail inventory and pricing to the field of labor management. As highlighted in the above graphs, issues such as turnover, lateness and absenteeism remain significant challenges. However, this rich dataset allows for precise comparisons across retailers and offers insights into the consistent productivity growth in the retail sector over the past 30 years.
One of the key components of any retail store is a store manager. In the webinar, the speakers also threw light on how crucial the role of a store manager is in tackling labor issues and beyond.
Store Managers: The Real-Time Decision Makers
Store managers, as shown in the image below, are much more adaptable than commercial software, when it comes to anticipating fluctuations in demand. Using on-the-ground insights, they can tweak staffing schedules based on real-time factors. This ability adds significant value, as managers can ensure labor aligns with actual customer traffic patterns.
Store Managers as Team Leaders and the “Buffer of Last Resort”
Apart from acting as real-time decision makers, store managers play a dual role—nurturing their teams while acting as the ultimate safety net when things go off course. They understand that a strong, well-trained team is key to running a successful store, and they invest time in supporting and empowering their long-tenured employees, who are often the backbone of the operation.
But what truly sets them apart is their role as the “buffer of last resort.” When unexpected challenges arise—whether it’s a sudden labor shortage, spike in customer traffic, or last-minute schedule changes—store managers are the ones who step in, making quick adjustments to ensure smooth operations. Their ability to handle these fluctuations with agility and composure keeps the store running, making them unsung heroes who adapt in real-time to an unpredictable environment.
Store Managers’ Flexibility Enhances Scheduling
Retail labor management heavily depends on store managers’ ability to adapt to real-time challenges. Flexibility is not merely a valuable trait; it is essential for successful store management to navigate customer traffic, promotions, and other unpredictable factors.
The graph highlights how store managers frequently override commercial labor scheduling systems—66% of the time they adjust schedules based on real-time factors such as competitor promotions or unexpected traffic patterns. This flexibility is key, allowing managers to fine-tune staffing needs on short notice. Their advanced notice adjustments, as shown in the lower graphs, significantly reduce the need for last-minute changes, particularly benefiting more experienced staff who are more likely to have their requests approved.
Store managers absorb the bulk of the scheduling uncertainty. The graph highlights their critical role in maintaining stability and ensuring smooth operations when disruptions arise, making them the ultimate safety net in the labor-management process.
The speakers then shared their perspectives on how a balanced approach implemented by retail stores can better support store managers.
A Balanced Approach to Support Store Managers: Empathy, Technology and Clean Data
To effectively support store managers, retailers must adopt a balanced approach that integrates empathy, technology, and clean data.
Empathy and understanding are essential for store managers, as many corporate executives don’t fully appreciate the complexities of their roles.
Technology needs to evolve beyond current capabilities. While store managers can tweak and override software recommendations, they rely heavily on real-time data—like weather patterns and competitor actions—that commercial software often overlooks. Enhancing technology to incorporate these factors will significantly reduce manual adjustments and smooth store operation.
Clean data is essential. Inaccurate data forces managers to spend unnecessary time correcting schedules. By prioritizing data accuracy, retailers can provide better tech solutions, enabling managers to focus on more strategic tasks.
The discussion then moved towards the role of AI and GenAI in retail and supply chain. AI plays a critical role in helping companies balance flexible labor allocation while maintaining consistent customer service in retail and supply chain operations.
Optimizing AI/GenAI in Retail and Supply Chain
AI and GenAI are reshaping retail and supply chain operations by integrating data from various sources, including demand sensing and external factors (e.g., weather), to predict labor needs more accurately. The democratization of insights empowers store managers to act as “citizen data scientists,” using AI tools to make informed decisions without needing deep tech skills. Additionally, machine learning helps manage knowledge by continuously learning from past data, allowing retailers to refine their strategies and create more efficient operations.
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Conclusion
In today’s evolving retail landscape, integration of human expertise and AI-driven insights is key to optimizing labor management. Store managers bring valuable local knowledge that enhances decision-making. Incorporating this into AI systems through tools like gamification or simulations can significantly reduce rookie mistakes and accelerate learning.
However, technology alone isn’t enough. Companies must ensure that while increasing productivity, they are also maintaining employee satisfaction and customer experience. A combination of better technology, cleaner data, and empathy towards store managers will allow retailers to thrive, even in the face of growing challenges. As industry reinvents itself, balancing these elements will be crucial for long-term success.
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