Picture this: A customer drives across town, wallet ready, only to find an empty shelf where your product should be. Sale lost. Brand damaged. Customer possibly gone forever.
With average out-of-stock rates hovering at 8-10%, this scenario plays out millions of times daily across retail. Yet despite billions invested in technology over two decades, the problem persists. On the latest episode of Confessions of a Supply Chain Executive, host Chris Walton sits down with two industry veterans, Richard Stewart (EVP of Product & Industry Strategy) and Eugene Amigud (Chief Innovation Officer) from Infios, to conduct a forensic deep dive into every failure point that creates out-of-stocks.
The Problem Has Changed, Not Disappeared
“I really wish I could take today’s technology and capability, hit rewind 20 years,” Richard admits, “because I would be the smartest person in the room and I could solve all the out-of-stock problems. But the reality is there’s really only one answer—it’s different.”
Twenty years ago, out-of-stocks were primarily supply constraints or bad replenishment processes. Today, it’s less about whether the product exists and more about whether the data exists. As retailers have connected dozens of systems—from planning to order management to store execution—the weak points now exist at the seams between these systems.
Eugene reinforces this evolution: “Fundamentals remain the same, but complexity increased exponentially. Yesterday I was watching something on TV that I could buy. How do you surface that inventory, especially if you’re fulfilling out of store?”
The Connectivity Crisis
When CEOs approach Richard about out-of-stock problems, he challenges them immediately: “You don’t have an out-of-stock problem. You have a connectivity problem. Most of the time, the inventory exists somewhere in your network. It’s just not where it needs to be when it needs to be there.”
This insight reframes the entire challenge. The question becomes: Where’s the disconnect? Is it in the systems? The incentives? Human nature? The data? The timing?
Every Breakdown Point in the Journey
The conversation methodically examines each potential failure point:
Forecasting and Demand Planning: While machine learning has improved demand forecasting significantly since 2014, many mid-tier retailers still rely on spreadsheets. The key challenge? Getting real-time point-of-sale data feeds to make algorithms truly effective.
Supplier and Inbound Logistics: Richard estimates that 75% of inbound issues stem from coordination failures rather than supplier failures. “How many people are still managing their inbound with email threads and spreadsheets and attachments?” The result: being days behind reality before products even arrive.
Warehouse Execution: Eugene shares a favorite story: retailers showing inventory in their warehouse when it’s actually still in the yard, awaiting receiving. “I’ve seen this 15 years ago—still see it now.”
The Phantom Inventory Problem: Warehouse accuracy typically reaches 98%+, while store accuracy ranges from 97-99%—a massive improvement from the 85-90% rates of a decade ago. But phantom inventory remains a persistent challenge, particularly in stores where customers interact with products before purchase.
Store Complexity: Eugene describes a fashion retailer doing pick-pack-ship from stores where customers would see items on the picking cart and simply take them, assuming they were popular items worth buying. “Good luck predicting that kind of behavior.”
The System Integration Challenge
“Any individual system doesn’t create the out-of-stock,” Richard explains. “What creates the out-of-stock is when they’re not talking to each other.” He uses a memorable analogy: the OMS is the brain, the WMS is the arms, and the TMS is the legs. When these functions aren’t communicating, things go wrong very quickly.
Eugene expands on this: “You may need capabilities from multiple systems. That’s quite different than saying, ‘I want to buy order management.’ Systems are becoming more agile. Your stack cannot be a bottleneck for the business.”
The AI Solution Framework
When asked about fixing the fundamentals, Eugene outlines a clear approach:
- Choose the right AI tool: Machine learning for demand forecasting, generative AI for configuration and tribal knowledge capture, optimizers for specific routing problems
- Centralize inventory as one brain: Create a single engine that coordinates across OMS, WMS, and TMS
- Tie AI to specific use cases: Avoid “AI washing” everything—focus on purposeful innovation
- Build bridges between systems: Different channels have vastly different requirements (100-millisecond response times for website vs. batch processing for financial reporting)
The Uncomfortable Truths
As befits a podcast called “Confessions of a Supply Chain Executive,” both guests delivered uncomfortable truths:
Richard’s confession: “Out-of-stocks are never going to go away. Perfection isn’t the goal. What you’re trying to do is make yourself resilient. The ones still trying to chase zero stockouts are really just fighting yesterday’s battle.”
Eugene’s confession: “Start small. I’ve been in so many conversations where it’s, ‘Okay, out-of-stock—I’m going to replace every single system to get it all perfect.’ Start with one problem, get a small win, then move on to the next.”
The Human Element
Perhaps most surprisingly for a technology podcast, both guests emphasized that technology alone cannot solve out-of-stock problems.
“Technology is probably the easiest part of this whole equation,” Eugene admits. “People and processes—that’s where the real heavy lifting is. Technology just cannot be the bottleneck.”
The solution requires cross-functional mandates from the top, aligned incentives toward the common good, and early stakeholder engagement. As Eugene puts it: “Nobody hates anything more than somebody saying, ‘This is the API, start calling it tomorrow.’ Pull in the right stakeholders early so there are no surprises.”
Who Owns the Problem?
When Chris asks who actually owns the out-of-stock problem, Eugene describes the worst scenario: going to a retailer and watching someone from digital and someone from supply chain shake hands and introduce themselves for the first time.
“I don’t see a single owner,” Eugene concludes. “It’s a collection of systems put in place across this whole supply chain portfolio that have to work together.”
Richard adds: “If you assign a single person to own out-of-stocks, they’re only going to get worse. There is only one way to get it done—go cross-functional.”
The Path Forward
For retailers ready to tackle their out-of-stock challenges, the episode offers a clear roadmap:
- Accept that perfection is unattainable; build for resilience instead
- Focus on connectivity between systems rather than replacing individual systems
- Implement a centralized inventory “brain” to coordinate decision-making
- Start small with purposeful innovation tied to specific business needs
- Align incentives cross-functionally toward customer satisfaction
- Leverage the right AI tools (machine learning, generative AI, optimizers) for specific use cases
- Remember that technology enables solutions but doesn’t create them—people and processes do
As Eugene summarizes: “Start building out the brain to control the out-of-stock inventory situation, but at the same time deliver specific business value. It’s definitely more art than science.”
Listen to the Full Episode
Ready to dive deeper into the forensic analysis of out-of-stocks? Listen to the complete inaugural episode of Confessions of a Supply Chain Executive featuring Richard Stewart and Eugene Amigud from Infios, available now wherever you get your podcasts.
Apple Podcasts | Spotify | Soundcloud | Amazon Music
Because when it comes to supply chain challenges, confessions are almost always good for the soul.
Be careful out there,
– Chris, Anne, and the Omni Talk team
Music by hooksounds.com
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Omni Talk® is the retail blog for retailers, written by retailers. Chris Walton and Anne Mezzenga founded Omni Talk® in 2017 and have quickly turned it into one of the fastest growing blogs in retail.