Empowering the Frontline: Inside Grupo Bimbo’s AI-Powered Transformation in Its Bakeries and the Stores It Stocks
One of the things I’m especially proud of since the beginning of antuit.ai is the number of customers who have been eager to come forward and share their positive experiences with us. Like any successful business, the most genuine form of advertising is an enthusiastic word-of-mouth endorsement—particularly in front of a live audience at a high-profile industry conference.
Earlier this year at the Gartner Supply Chain Symposium, I was very pleased to share the stage, before an auditorium of 200 attendees, with Morgan Smith, Vice President of Direct Store Delivery (DSD) Center of Excellence for one of our major CPG customers, Bimbo Bakeries USA.
For those unfamiliar with the name itself, Grupo Bimbo is the world’s largest baked goods company, spanning over 100 brands across 33 countries. In the U.S. alone, Bimbo Bakeries USA produces over 20 distinct bakery brands, from iconic names like Sara Lee, Entenmann’s, and Thomas’ English Muffins to a variety of popular niche or regional brands. Much of what we see in the grocery bread aisle is a testament to Bimbo’s quality standards and efficient DSD logistics.
But as company leaders like Morgan will tell you, success isn’t something that comes easy. In fact, most successes in life are born out of struggle – a tipping point at which we’re forced to really think through the best way forward. In business, that struggle may be stagnation. Other times it’s competition, resource constraints or fluid consumer expectations. For Grupo Bimbo, and the Bimbo Bakeries USA team specifically, it was a knowledge gap between senior leaders and front-line workers, especially as it related to demand forecasting, store delivery and related operations.
Morgan wanted to find a way to close that gap using technology. More specifically, he wanted to find technology that could translate all of Bimbo’s operational and market data into a consistent and satisfactory consumer experience. So, he started thinking about things a lot differently than most people did at that time – and most people still do today.
The Challenge: “Let’s Be What We’re Not”
For our Gartner audience, Morgan first recalled how, six years ago, after already overseeing Bimbo’s U.S. operations for around two decades, he was tapped to lay the groundwork for an organizational transformation:
How could a company that in effect functioned as a dozen fragmented regional bakeries be centralized into a world-class enterprise?
How could scaling business volume be led out of a virtual “Stone Age”—desktop calculators and manual spreadsheets—toward advanced, data-driven technologies?
How could the company’s mission be reshaped around the consumer experience? In particular, the budget-conscious shopper who expects the last two slices of their weekly loaf of bread to be as fresh and tasty as the first.
What tools could be internally developed to empower the company’s front-line workforce—maintaining the highest quality from the production line through final store delivery?
Morgan visually represented Bimbo’s new priorities as an “inverted pyramid”, where the most important stakeholders were everyday consumers, followed closely by the company’s front-line teams that directly serve them:
To find the answers to these questions, Morgan had to visit Bimbo plants across the country, engaging those with decades of expertise to learn what’s working and what’s not—from veteran bakers on the production line to front-line workers such as DSD drivers who are the last to handle products before the final sale. Morgan described these consumer-facing roles—numbering in the thousands nationwide—as Bimbo’s “army of vision carriers,” as well as “the last line of defense” for ensuring a terrific brand experience for the consumer.
Applied to Bimbo’s broader transformation, Morgan noted that this was a marked departure from the “command and control” mindset of other companies. Instead of having operations-related information and instructions flow from top leadership downward to front-line teams, Morgan wanted to find technologies that would help those on the front lines better communicate and coordinate with each other first and foremost, before eventually flowing status reports and real-world insights “downward” to senior management to keep them apprised of issues and opportunities.
Augmenting Human Know-How with AI
After months of soliciting direct input from bakers and delivery people across the company, Morgan explained how they ended up collaborating with the antuit.ai team at Zebra to develop and launch a proprietary demand intelligence platform, which they named “Ion.”
The technical “engine” behind Ion is antuit.ai’s AI-powered demand forecasting and predictive ordering technology, which the Bimbo and antuit.ai teams collaboratively tailored to support different front-line workers via custom user interfaces (UIs). Everyone from operations managers to DSD drivers can now open their respective UI to right-size production and localized delivery plans down to a SKU/store/week level factoring seasonality, local events, promotions, and other outside influences that may not be considered with human-led demand forecasting and inventory planning models.
When I asked Morgan to evaluate the quality of our AI data modeling, he offered perhaps the most succinct answer we’ve ever heard: “Nine times out of ten, it knows what my wife wants to buy on a Tuesday with a coupon in her pocket and she’s hungry. That’s unbelievable accuracy.”
In fact, it was the predictive accuracy of this particular AI platform that drove Morgan and his team to call antuit.ai in the first place. There are many different ways to improve demand forecasting, inventory planning and the efficiency of operational execution. However, many—too many, perhaps—are disadvantaged by people’s inability to see and process everything happening in the world around them. We can’t aggregate data, much less detect patterns, at the scale or speed of machine learning algorithms or adaptive AI, no matter how hard we try. So, business leaders who want to be well-positioned to respond to market volatility, and those who want to be confident in the daily decisions their teams are making in response to even slight changes to consumer behaviors, are finding that they must investigate AI’s capabilities. They need to be able to assess current market demand and business capacity alongside recent performance and future efficiency opportunities almost simultaneously, every day, and then flow those insights in a highly tailored manner to each person in their organization calling the shots on how to execute that day. That is no easy feat, and it has proven impossible for humans to accomplish on their own.
Fortunately, Morgan—and all 20,000+ Bimbo employees—now have clear guidance on what they must do to deliver the right quantity of fresh goods to the right place at the right time. They don’t have to waste time guessing if they’re making enough product for the day or mapping the right delivery route based on current inventory levels and demand, and the predictive accuracy of Ion means they don’t end up with wasted products on store shelves due to overestimated demand and overstocks.
The COVID Crucible
The real test for Ion would come at the outset of the pandemic when grocery demand patterns changed instantly. While so many CPG companies—and competing bakery companies—struggled with supply chains and logistics for months on end, the Bimbo team was able to adapt its forecasting and production far more quickly. They were able to meet the heightened demand for their baked goods as more consumers started to eat at home amid restaurant closures. In less than a month, they were able to right-size their production volumes, adjust delivery routes to avoid out-of-stocks, and properly staff production lines, loading docks and trucks to meet the skyrocketing demand.
You can read all about the specific changes they made across their operations and why here:
How Bimbo Bakeries USA Improved Order Accuracy, Reduced Waste
No Easy Journey, But Worth the Payoff
Now that things are stabilizing a bit, Morgan and his team have had time to really assess the impact of his decision to lean on AI for DSD predictive ordering. How did this one change help maintain the balance between product freshness and product availability, simplify collaboration between planners and route operators, and scale operations to support Bimbo’s more than 11,000 U.S. distribution routes? And did this one software investment really deliver the “Perfect Order” solution the Bimbo Bakeries USA team was collectively looking for?
As you’ll see when you dig in more to Bimbo’s story, this adaptive AI tool has absolutely reduced forecast errors that used to result in overstocking and understocking – by up to 30% no less! It has also helped the team maintain a forecast efficiency rating of over 80% for more than five years, including through the pandemic. And Morgan says over 20,000 employees, from bakers to DSD drivers, have found it easier to deliver exactly what baked goods consumers want—fresh goods every day—thanks to the more accurate guidance provided by the AI tool’s predictive capabilities.
Before we wrapped up the Gartner session, I asked Morgan what advice he’d give other business leaders before embarking on a similar data/IT journey for their organizations. He responded by giving everyone a heads up that changing how you plan and execute operations on this scale is invariably a huge undertaking—something that must happen over the course of years rather than months. However, he stressed that if you begin the journey by defining the right leadership model, then choosing the right data technology partner and strategic advisor to help bring your ambitions to life in a tangible and measurable way, then you’ll gain a very real strategic advantage that competitors won’t be able to match, especially if they’re not yet leveraging adaptive AI to help them adapt their production and delivery operations to align with current (i.e., changing daily) demands.
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Related Read:
Bimbo Bakeries USA Minimizes Waste by Improving Its Forecasts by 30% with Zebra Technologies
