Every grocery retailer invests heavily in planograms.
Planograms are data-driven, carefully negotiated, and designed to maximize sales. Category teams invest months determining precise product placement, with the expectation that these plans will be executed accurately in stores.
However, in practice, store shelves often do not reflect these plans.
Items may be misplaced, facings incorrect, or stock keeping units (SKUs) missing. New planograms can take weeks to implement. While each issue may seem minor, collectively they drive significant revenue loss.
The gap between planning and execution is not new. What is new is the availability of technology to address it.
The Execution Gap We Have Learned to Live With
Most retailers recognize that in-store execution at the shelf is imperfect. Over time, this imperfection has become widely accepted.
Once a planogram is distributed, visibility declines rapidly. Execution still depends on static PDFs. Store teams operate under labor constraints and frequent interruptions. Audits are often conducted later by third parties, and reports may arrive days or weeks after issues have affected shoppers.
By the time insights reach category teams, the critical moment has often passed.
The result:
- Category teams lack real-time shelf visibility into execution.
- Store associates must interpret instructions and improvise solutions.
- Omnichannel promises break down at the shelf.
- Even a 1% execution gap can result in significant revenue loss.
In high-volume categories, a 1% execution gap can cost millions annually. Failed BOPIS picks, substitutions, and shopper frustration further amplify the impact.
Everyone Owns a Piece, No One Owns the Loop
Shelf execution often fails due to fragmented ownership.
Buyers design the plan.
Stores execute it.
Third parties audit it.
Reports arrive later.
No single party manages the entire process from plan creation through shelf execution and actionable feedback.
As a result, when shelves do not meet expectations, the same questions arise:
- Was the plan unrealistic?
- Was inventory constrained?
- Was labor the issue?
- Was the execution unclear?
Without timely, objective insight into shelf conditions, these questions remain unanswered, and the same mistakes repeat each cycle.
Why This Problem Is Urgent Now
Shelf execution has always been important, but three recent changes have made it a critical focus:
- Labor is tighter than ever
Stores are expected to accomplish more with fewer staff. Manual audits and delayed feedback are no longer sustainable in this context. - Physical shelves now power digital fulfilment
BOPIS, curbside, and same-day delivery all require accurate shelves. Inaccurate shelves lead to failed digital orders and quickly diminish shopper trust. - The technology gap has finally closed
This represents a great turning point.
Previously, retailers lacked scalable tools to monitor shelf conditions without significant labor or hardware investment and this is no longer the case.
Modern AI, particularly computer vision, can now interpret shelf conditions visually, quickly, and on a scale, using tools already available to store teams, marking a practical turning point for AI in retail.
The primary barrier is no longer technology, but organizational mindset.
What AI Changes About Shelf Execution
AI does not replace store teams. It enhances their existing observations.
Store associates regularly walk the aisles and are the first to notice issues. AI enables these observations to be shared with the broader organization in real time.
With AI-driven smart shelf intelligence:
- Shelf photos become structured data, not just images.
- Planogram compliance can be detected automatically.
- Issues can be prioritized based on sales impact rather than assumptions.
- Category teams gain real-time visibility into execution, rather than waiting weeks for updates.
Rather than relying on delayed audits and retrospective reports, retailers can now understand the shopper experience while it is still relevant.
This shifts shelf execution from:
- Manual → Intelligent
- Reactive → Proactive
- Fragmented → Connected
Most importantly, shelf execution shifts from a cost center to a driver of revenue and retail operational efficiency.
This Is Not About More Audits
To clarify, this approach does not add additional work for stores.
It is not about policing compliance.
It is not about blaming associates.
And it is not about layering on complexity.
The goal is to establish a real-time feedback loop between shelf conditions and decision-makers.
Imagine if:
- Shelf issues were captured in the moment.
- Associates could report issues by submitting a photo, rather than relying on temporary workarounds.
- Category teams could see execution gaps by store, region, or category.
- Issues could be resolved during the same shift rather than in the following quarter.
This illustrates the value of applying AI at the intersection of store operations and merchandising strategy.
Rethinking Shelf Execution for Modern Retail
For decades, shelf execution has been viewed as a downstream task, checked after the fact rather than managed continuously.
Modern retail now requires a different approach.
Execution needs to be:
- Immediate, not delayed
- Visual, not abstract
- Actionable, not retrospective
- Embedded into daily store workflows, not layered on top
AI enables this approach to be implemented at scale, for the first time.
Let Us Start the Conversation
The industry recognizes shelf execution challenges but lacks a practical solution to bridge the gap between planning and reality.
Consider the following questions:
- Where do you see the biggest breakdowns between planogram design and in-store execution today?
- What’s holding retailers back from real-time shelf visibility?
- If AI were applied thoughtfully, what would “great” shelf execution look like?
Shelf accuracy is now central to merchandising, operations, and omnichannel fulfillment. Addressing this challenge requires innovative thinking, clear ownership and the adoption of modern tools.
HTC works with retailers to apply AI-driven shelf intelligence in a way that fits naturally into existing store workflows. By connecting visual shelf data with real-time insights, HTC helps organizations move from delayed audits to continuous execution visibility, enabling faster decisions and more reliable in-store outcomes.
If you have observed execution gaps or have examples where technology has made a significant impact, I welcome your perspective. Please share your experiences.
