Earlier this year, Progressive Grocer released a series of articles focused on discussing the future of the grocery industry. Gina Acosta’s piece, entitled Workforce 2020: A Sneak Peek at the Future of Labor in the Grocery Industry is a spot-on discussion of the key challenges grocers must overcome to be successful in 2020 and beyond. Her commentary on the importance of recruitment and training align exactly with our mindset at Connors Group and reflect similar recent blogging done by the Connors Group team. These two areas are unfortunately often overlooked or deprioritized by many retailers (not just grocers) – yet when retailers get it right, the results can be impressive.
To build on Gina’s commentary, there are two areas I believe grocers should focus on in 2020 and beyond to ensure a successful workforce management strategy:
1 – Machine Learning & Artificial Intelligence
Yes, I know ML/AI is this year’s latest craze in the retail industry, but unlikely many previous industry fads, ML/AI has real, tangible and immediate value for grocers in their workforce management strategy. Anyone that has worked in the grocery business will tell you, forecasting sales (and the associated labor plan to support those sales) is one of the most important, yet challenging aspects of the business. Store Managers, Financial Analysts and Forecasting Gurus across the grocery industry put tremendous effort into predicting store sales each week.
All this effort (and cost) is put towards this activity for two reasons. First, accurately predicting grocery sales is tremendously important to a company’s bottom line. Over-forecast sales and a store will be in the red with excess labor and product wastage (shrink). Under-forecast sales and risk not having enough product on the shelves and not enough cashiers to get customers out the door. Neither of those scenarios is a recipe for success. Second, it is flat out difficult to accurately predict grocery store sales and therefore the process requires a tremendous amount of effort to achieve even just a reasonable and consistent level of accuracy. Customer shopping patterns change regularly, weekly promotional activity can swing buying patterns and external events such as weather and even sporting events can impact a sales forecast.
So how does ML/AI help with a grocer’s workforce management strategy? It takes an activity (sales forecasting) that is extremely important, yet difficult to get right and greatly improves upon it.
The latest forecasting algorithms that leverage ML/AI are able make sense of those customer buying patterns by continuously improving their parameter logic and accuracy, and by evaluating enormous amounts of data and constantly identifying improvements at the most micro of levels. Gone are the days of relying on a single forecasting methodology (Holt-Winters for example) for all variables, across all stores. The result is a sales forecast that is more accurate, but more importantly, labor and inventory plans that are more accurate.
2 – Associate Schedule Flexibility
Gina hit on this in her article, but I want to dig a little deeper. In the gig-economy world and a workforce that is essentially at full-employment, providing Associates schedule flexibility is becoming an increasingly important competitive advantage for attracting and retaining talent. Schedule flexibility includes empowering Associates to clearly define (and change) when they want to work, allowing Associates to easily swap shifts with their peers and giving Associates the ability to pick-up shifts at additional store locations. Some retail executives and industry consultants have come out against this level of Associate flexibility, arguing it risks shifts going unfilled or stores ending up with “sub-optimal” schedules, particularly in small-box retailers, with fewer employees per store. While I can understand their perspective, I disagree with that mindset overall and find the exact opposite to be true for grocers. Given their massive employee counts and highly variable workloads, Grocers are ideal candidates to enable this level of schedule flexibility with their Associates.
Additionally, as shoppers migrate more to delivery and/or pick-up options the need for shifts to be filled at short notice and at odd hours will increase. Most grocers will struggle to do this within their current paradigm and systems. Allowing schedule flexibility might be the best way to accommodate these evolving trends.
Grocery will never go away. People need to eat. The nature of the grocery experience will, however, need to evolve. Most grocers know that they need to figure out how omni-channel fits into their world over the long term. They know that being lean in their supply chain is not a differentiator, but a competitive necessity. They need to be equally open to thinking differently about their workforce. Grocers no longer compete amongst themselves for talent; they also compete with other retailers, the service industry, and even Uber. Most importantly, they no longer compete for talent on a binary basis, but are trying to attract individual shifts. To win this war for talent, it is critical that grocers are ultra-accurate in forecasting demands and flexible in attracting the talent to fill those shifts. ML/AI and Schedule Flexibility will very quickly become competitive necessities for successful grocers in 2020 and beyond.
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