A Closer Look at Walgreens’ AI-Powered Demand Planning Transformation
For years, Walgreens enticed customers with an ad highlighting “what’s on sale this week.” Now, it can proactively tailor the whole retail experience around customers’ real-time wants and needs.
There are always so many valuable new insights to be gleaned at shows like the recent NRF Big Show in New York and RILA LINK in Orlando. But this year, I found my sit down with Andy Kettlewell, Walgreens Group Vice President of Inventory & Analytics, to be most enlightening. We looked back on how Walgreens successfully transformed its retail operations using artificial intelligence (AI) over the last few years. His team—now leverages a wealth of advanced data sets to better achieve its core mission—meeting the health and wellness needs of nine million daily customers across 9,000 store locations nationwide, in addition to its sizeable omnichannel customer base. Though I’ve been engrained in the process for quite a while, the journey to get Walgreens to the current state of actionable, business intelligence has been remarkable.
So, let me share a little bit about what turned Walgreens onto AI and the steps they took to get here…
As early as 2017—long before the pandemic abruptly redefined much of our daily world— the Walgreens team began reimagining demand planning and forecasting to better serve an already changing customer.
As you may recall, up through the 2010s, Walgreens’ outbound marketing program primarily consisted of a weekly print advertising supplement included in Sunday newspapers and available to shoppers after they’d already entered a store. Short-term demand for specific food, drug or personal care/beauty products could be broadly influenced by attractive sale prices on the front page of the insert. In other words, the weekly circular worked well enough to draw in customers and help Walgreens hit revenue targets.
But as more consumers started scrolling through their phones versus flipping through papers, the effectiveness of advertising inserts started to wane. So, the Walgreens team started looking at how they could meet their customers where they were and, in the process, take advantage of those digital channels. They came to us to understand how they could harness leading-edge AI technology and predictive data science to dramatically enhance demand planning, inventory allocation, and overall customer satisfaction and get a leg up over the competition. They had a feeling they could use external data that influences demand (like social media and local events) to better forecast customer demand and make sure they had the right product available at the right time at the right price – and they were right.
First Things First: Understand – and Speak Directly to – Each Customer’s Desires
Before Walgreens leaders could change anything about their operations, though, they had to change how the company talked to the customer. They decided to draw upon their existing loyalty card program—over 100 million members strong, with growing numbers also connecting via the Walgreens mobile app – to create a feedback loop. Beyond rewarding customers after a purchase, they asked themselves, “How can this huge audience—driven by an entirely different set of stimuli—be better engaged to shape future demand and distribute inventory accordingly?”
The answer revolved around proactively reaching out to customers on a personal level and utilizing voluminous sets of localized, granular-level data. They didn’t just focus on internal sales goals. They also attuned demand around customers’ daily lives—outside of Walgreens—spanning seasonal, monthly, or even hourly timeframes, such as:
Current local weather forecasts that could influence demand for over-the-counter cold/allergy medications—or bottled drinks and sunscreen.
A popular social media influencer endorsing a brand of cosmetics.
The closure of a large factory or other major local event impacting shoppers’ priorities.
A sports game or concert at a local arena—anticipating what items might be convenient for pickup at the nearest Walgreens before or after the event.
This is especially notable because, prior to the advent of AI, demand planning around a single SKU might have been as simple as pulling in three internal/external variables. Today, it could potentially take into account 50 or more—a monumental task for any human analyst to sift through at Walgreens’ scale: a 300 million time series forecast among those 9,000 locations. AI has proved instrumental for simplifying intricate data sources into effective, low-touch demand forecasts and inventory planning throughout every store.
Next Step: Let Go of Fear
In a seemingly short period of time, our AI solutions have enabled Walgreens to reaffirm its core brand positioning—as a provider of customer solutions, from being their go-to resource for vaccinations and expanded ancillary health services, to providing parents that coveted bottle of medicine for their sick child at all hours of day and night, to helping them navigate the recent troubling shortage of baby formula and other supply chain volatility that will likely continue to plague us for some time. Our AI-powered tools enable Walgreens team members to better anticipate every detail—the brands, sizes, and flavors shoppers expect—as well as predicting the best times to stock extra units on a shelf. This would have never happened without the company’s strategy and leaders’ willingness to better listen, understand, and cater to each customer as their daily needs change.
Knowing not all retailers have been compelled to make the same changes as Walgreens, or at the same pace and scale, I was curious to get Andy’s advice for other retailers looking to embark upon their own AI journey. At both NRF and RILA, he recalled how, after defining their own forecasting and allocation vision, collaborating with the Zebra/antuit.ai team on a live test-and-learn pilot—a relatively small sample size of 10-15 million item/store combinations—was key to validating hypotheses and achieving positive results before a methodical, year-long rollout. Despite some early trepidations around adopting a “black box” for internal decision-making, he affirmed that AI technologies, and the vast dimensions of actionable data they utilize, are ready to take center stage for any large retailer looking to keep pace with a changing customer.
I invite you to view the full recording of our NRF presentation and other useful video content here. And for more information about our demand planning, allocation and other AI-powered solutions for retailers and CPGs, contact us.
Shortly before our first presentation at NRF, we were pleased to learn Andy’s leadership of Walgreens’ AI-powered demand planning initiative was formally recognized by Retail TouchPoints, which included him among this year’s select winners of their annual Retail Innovator Awards. In the ever-competitive retail world, we view our customers’ successes as the ultimate benchmark of our success.
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