Gurdip Singh is Chief Product Officer at Blue Yonder, a leading AI company for end-to-end digital supply chain transformation.
Put a physicist in charge of a dairy farm, and they’ll devise a system scientifically proven to boost milk production—but only for spherical cows in a vacuum. In the real world, of course, cows are cow-shaped, and dairies are messy places. Farmers who ignore those realities don’t get far.
When it comes to retail, though, many companies still take a similarly rigid “spherical cow” approach to space planning. Space planning—what goes on the retail shelf and where—is the critical interface where shoppers get what they want or are frustrated. It’s where sales can surge or slide. It’s where shoppers find what they’re looking for—or an empty shelf.
Every retail store is unique, both physically and in terms of the customers it serves. Yet to manage mission-critical merchandising and display decisions, analysts at headquarters often create planograms directing local managers exactly how shelves should be stocked. Inevitably, those one-size-fits-all planograms don’t reflect the messy reality of actual retail locations, from nonstandard footprints or awkward pillars cutting through shelving to the specific demographics and seasonal factors shaping local demand.
As a result, vast amounts of time and effort get wasted on planograms that can’t be fully implemented, and retail locations seldom come close to optimizing their operations. Industrywide, planogram compliance is well under 70%. As a result, stores miss vital opportunities to maximize profitability. We need a smarter approach.
Failure To Launch
The need for better space planning is clear. Only 30% of purchasing decisions are made before customers enter a store, so product displays make an enormous difference. Simply moving high-margin products to eye level can boost sales by up to 8%, for instance, while fully optimizing assortment and space management can boost profits by over 50%.
Since the 1990s, though, space planning has stagnated. Retailers create sophisticated planograms showing where products should be placed. But for many retailers, the bigger problem of implementing those plans and ensuring stores actually optimize their shelves has been largely ignored.
That’s because customizing planograms for individual stores and ensuring compliance is prohibitively labor-intensive. When some retail employees admit to following planograms only to the extent required to keep their jobs, ensuring shelf-by-shelf compliance seems an insurmountable challenge.
At best, retailers have given store managers a little more agency. Some retailers have used “flexograms,” enabling managers to adapt displays for local needs. Others use only 90% of available space in their planograms, providing wiggle room when conflicts arise. But if you’re understocking by 10% to avoid other problems, you’re not optimizing your shelves.
Time To Aim Higher
It’s bizarre that we can send rockets to the moon but can’t optimize product layouts on shelves. Fortunately, the rise of AI, smarter data tools and ubiquitous sensors and mobile devices finally make it possible to transform space planning. It will require using emerging technologies to drive transformation in five key areas:
Store-Specific Planning
No more spherical cows: Tailoring space planning to individual stores can cut the number of under-spaced products. The gold standard would be “per store, per week” planograms, dynamically updated based on shifting demand and availability. Using AI and other digital tools, it’s increasingly possible to automate customization, enabling store-specific planning with precision and at scale.
Real-Time Collaboration
To enable store-specific planning, we need to radically streamline planogram production. This means upgrading the way retailers and brand owners collaborate to design displays. The current linear system—in which planograms are iteratively exported, shared, revised, exported again and revised again—is woefully inefficient. Instead, we’ll need to bring space planning into shared workspaces where all stakeholders, including store operators, merchants and category captains, can collaborate in real time (similar to Google Sheets).
Dependable Execution
Instead of sending out PDF planograms, retailers will increasingly use AI to digest planograms into specific action items for frontline teams, served via mobile devices to support execution. Real-world challenges will be captured through the same systems, tracking deviations and enabling collaborative problem-solving. Such streamlining boosts compliance while lowering operational overhead. With in-store logistics accounting for up to half of all retail logistics costs, that boosts the bottom line.
Honest-To-Goodness Data
Weaving industry-standard data (including product attributes and images) into space management will radically elevate planning processes. It might help ensure, for instance, that a 15-inch cereal box isn’t assigned to a 12-inch shelf, or it might create visual guides to help employees work more efficiently. It could also support the development of advanced technologies—such as dynamic pricing and automated planogram compliance—to further accelerate retail innovation.
Connected Decision-Making
Interoperable data will fuse planning, execution and broader supply chain processes, enabling smarter decision-making across the network. Planograms might be re-optimized in real time to adapt to supply chain hiccups or reduce the labor needed for replenishment, for instance. Studies show that solving replenishment and space planning simultaneously boosts grocery store profitability by as much as 29% without increasing operational complexity, so there’s plenty of headroom for growth.
The New Space Race
Retail is evolving fast, with buy online pick up in store, experiential shopping and other innovations placing new strains on both central planners and frontline teams. To meet those challenges, we can’t simply rely on the same inflexible tools used to manage merchandising and shelf space since the 1990s. Instead, we need to embrace new technologies—including AI, but also mobile tools, real-time collaboration and interoperable data—to drive retail forward.
For retailers, this is literally the new Space Race. Ignoring the problem is bad for customers, bad for frontline teams and bad for business. It’s time to set our sights higher and start using all the tools at our disposal to unlock a new era of smarter, more dynamic and more flexible retail operations.
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