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There’s no returning to old-style demand forecasting

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It’s become a cliché to say that the COVID pandemic has changed everything about retail, especially the acceleration to online shopping and the creation of demand for categories previously on the fringe of most merchandisers’ plans. While the food business has been the primary beneficiary of this transformation, mainly due to the shuttering of so many foodservice outlets, retail drug isn’t that far behind. Sure, some of the drug store categories were negatively impacted — cosmetics come to mind — but most of these losses were experienced across all channels.

Sivakumar Lakshmanan

Now, however, with the end of the pandemic hopefully in sight, it’s time for retailers to evaluate the issues they faced with inventory during all phases of the pandemic and prepare a strategy and tactics that will help avoid the dramatic challenges they encountered. In addition, retailers need to better understand the changed consumer whose shopping behavior has been altered forever. One thing is certain, drug stores can’t, and shouldn’t, go back to the old way of demand forecasting.

How to adapt to new consumer demand dynamics

Demand forecasting in the retail drug channel has traditionally involved using historical sales data. Most retailers also add some sophistication to their forecasting algorithms, such as anticipating how promotional or other known events will impact future sales. The goal has always been to optimize inventory while meeting required service levels.

COVID has been the single biggest “event” that retailers have faced. But unlike other events that retailers track and manage, like promotions, retailers cannot simply try to isolate the impact COVID had on historical sales and recalculate without that event. Why? Because we also experienced dramatic changes in consumer preferences and buying behaviors. So, what sold last year or even last month in-store may not be what consumers want now, or they may not want to purchase it in the same way.

In their Harvard Business Review article “Adapt Your Business to the New Reality,” Michael Jacobides and Martin Reeves wrote, “Companies seeking to emerge from the crisis in a stronger position must develop a systematic understanding of changing habits. For many firms, that will require a new process for detecting and assessing shifts before they become obvious to all.”

Drug store retailers should start by understanding what the pandemic has caused people to buy more and less of. They also need to understand the implications of new habits gained and their cascading indirect effects, Jacobides and Reeves argue, or they won’t be able to identify weak signals and will miss opportunities in the market.

How COVID created a technology turning point

Part and parcel of demand forecasting is technology, and retailers have had much greater success right-sizing inventories, particularly in today’s omnichannel world, by deploying sophisticated systems with AI algorithms that model consumer behavior.

Jon Duke, vice president of research at IDC Retail Insights, suggested, “At some point during the coronavirus crisis, planning gives way to reacting and executing in the moment for retailers in essential services segments like grocery and drug. Demand forecasting can play an important role in both the planning and the reaction stages of the crisis response for retailers.”

In the retail drug channels, merchants have experienced a sharp dichotomy in terms of demand forecasting during the pandemic. On one hand, lockdowns resulted in a sharp sales drop in profitable categories like beauty. On the other, drug retailers saw a surge in demand for O-T-C, cleaning supplies, groceries and more, often leading to out-of-stocks due to supply chain interruptions, resulting in customer frustration.

In addition to the impact felt at the store, the COVID pandemic is clearly hastening the digital transformation at drug store retailers. Overall e-commerce sales grew 44% in 2020, according to Digital Commerce 360 estimates, and while most analysts report a smaller increase in the drug channel, it’s still substantial.

These two phenomena combine to give demand forecasting an even greater role in a retailer’s go-to-market strategy as the country ends lockdowns and starts on the path to the changed future.

New way of demand forecasting for drug retailers

Like other companies, in preparing for the post-COVID, drug store retailers are devoting most of their resources to ensuring the safety of their employees and customers. But only slightly behind safety on their list of priorities should be creating and maintaining a more resilient supply chain, and that starts with enhanced demand forecasting. It doesn’t take much imagination to understand the impact of rapidly changing consumer behavior on buying, selling and ordering product. Everyone in the world saw it in the form of the panic buying of paper goods and cleaning supplies last spring.

Looking at the big picture, retailers should start by mapping out their new supply chain ecosystem, keeping the customer at the center and building out from there. This process designs a dynamic supply chain by incorporating data from internal and external sources and then calibrating the model to increase inventory flexibility, improve product visibility and traceability, better manage profitability, and enhance customer service levels.

Next, because inventory optimization begins well before the purchasing phase, retailers need to consistently be predicting the demand caused by each customer and business transaction. A common demand engine, powered by AI that evaluates all demand drivers to produce a unified demand signal, is the foundation of inventory optimization.

Lastly, drug store retailers need to deploy solutions with AI algorithms and intuitive work flows that provide contingency power that can quickly predict actions needed to be taken when (not if) circumstances like the pandemic recur.

Benefits from this process include increased customer sales from reduced out-of-stocks and lower inventory and wastage costs from too much inventory, both driving significant margin gains.

Data is key, the more the better, but perfection is not necessary

Retailers already have a lot of data — sales, price changes, promotions, orders, receipts, etc. Most of which is internally generated and stored, and often has lots of gaps and missing elements. The assumption is that this bad data would produce a bad forecast, but this is another traditional way of looking at the world, and why utilizing AI-based solutions is necessary. Not only can these sophisticated algorithms help calculate more accurate and granular forecasts, but they can also see through the data issues. Of course, there comes a point where data is unusable, but many would be surprised to learn the accuracy they can derive from data that’s far less than perfect.

But to truly enhance demand forecasting, especially for drug store retailers, they need to look externally. And not just big weather and national events. The neighborhood drug retailer is impacted by local, often smaller, events more than most other retailers because they are a one-stop shop. So, yes, a drug retailer should be aware of public holidays but also local school holidays, for major weather disasters but also local weather-related cancellations, for national sporting events but also local little league tournaments.

For example, on one Saturday, a local charity puts on a marathon that places the start and finish line within a block of the retailer. This creates demand for beverages, snacks, O-T-C first aid, etc. And if not prepared, the retailer runs out of product in the first hour of the day, losing revenue with it. And not just the revenue from the obvious items, but once the word is out that the store is out of Gatorade and band-aids, people stop coming to the store for any other cross-sell products since they want to go to one location for everything.

That’s what some retailers may call a nonscheduled event. But the truth is, it is scheduled. And with more sophisticated AI algorithms, the elasticity of products across the store in anticipation of such an event are forecastable. Now in this post-COVID world, as people are still coming out of their isolation, external data becomes even more important. Attendance and participation at large group and local events have been altered, and no one is sure if they will ever return to exactly the same form.

Drug store retailers need to review their supply chains for gaps and address any challenges created by the pandemic. The digital transformation that was well on its way prior to COVID will continue to accelerate, and only by redesigning their demand forecasting strategy and tactics can they expect to run sustainable supply chains in the future.

Sivakumar (Siva) Lakshmanan is chief operating officer of AI Forecasting and Supply Chain at antuit.ai, a leader in SaaS AI solutions for forecasting, merchandising, pricing and marketing. His email is siva@antuit.com.


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