Rising costs and supply chain volatility are putting massive pressure on consumer goods brands—but the real issue may be happening behind the scenes. In a new study, DOSS surveyed 230 U.S. CPG (Consumer Packaged Goods) operations leaders to uncover where workflows are breaking down across product launches, manufacturing, and retail readiness.
Key Takeaways:
- one in two CPG leaders shipped products with incorrect labeling or packaging due to miscommunication
- one in four product launches were delayed, costing brands an average of 2.4 weeks
- 36% made major business decisions using outdated or incorrect data
- 44% of teams say their operations are primarily reactive
- Only 14% say AI has meaningfully improved efficiency—despite 40% already using it.
The findings point to a growing operational gap as brands scale—where fragmented systems, manual work, and poor data visibility are driving costly mistakes. As retail expectations tighten and margins shrink, these inefficiencies are becoming harder to ignore.
In an interview with Retail Insider, Sebastiaan Debrouwere, VP Business Development & Marketing at DOSS, discusses the survey results.
Question: The study found that one in two CPG leaders shipped products with incorrect labeling or packaging because of miscommunication. Why are these errors still happening at such a high rate despite advances in supply chain technology?
Answer: While most of today’s consumer brands have invested heavily in operations technology, they have not unified it, creating silos between different parts of their businesses. Critical product information lives in spec sheets from Walmart and Target, shipping and compliance requirements from each retailer, format templates from contract manufacturing partners, and internal artwork files. None of those sources talk to each other. The issue is usually less about a lack of software and more about the brand, the contract manufacturer, the warehouse and logistics partner, and the retail partner working from different versions of the truth.
The breaking point is often coordination with contract manufacturers, the partners who physically produce the product. Around a third of the errors we see trace back to a brand sending one spec, the manufacturer interpreting it against a slightly older template, and the finished product arriving at the retailer’s warehouse with the wrong barcode, product identifier, or pallet setup. Product launches move quickly, packaging changes mid-flight, and retailer compliance requirements update quarterly. When those updates travel through disconnected workflows, the error rate compounds.
Q: With one in four product launches delayed by an average of 2.4 weeks, what are the biggest operational bottlenecks slowing brands down today?
A: The biggest bottlenecks are usually coordination and visibility problems rather than a single manufacturing issue. Modern product launches involve dozens of moving parts across suppliers, contract manufacturers, retailers, and internal teams. When one step slips, such as a Walmart shelf reset, a mapping via electronic data interexchange (EDI) that lags behind a new retailer requirement, or an accounting sync that breaks the order-to-payment cycle, it triggers a chain reaction across every downstream workflow.
Another major challenge is the ongoing dependence on manual processes. Our findings show nearly 40% of workday time is spent on manual data entry, including re-keying purchase orders, reconciling inventory counts between the warehouse and financial system, and building packaging templates for each new retailer. That slows decision-making and increases the chance of errors during already compressed launch timelines.
Q: The report suggests many companies are still making decisions based on outdated or inaccurate data. How much of this is a technology problem versus an organizational or leadership problem?
A: Both, as they’re interrelated.
On the technology side, most consumer brands run a stack of fragmented systems that cannot communicate with each other. An enterprise resource platform (ERP) used for business operations that was not built for consumer goods, a separate system at the warehouse, spreadsheets for manufacturer coordination, and a forecasting tool that does not reconcile to actual on-hand inventory. Teams spend a lot of time reconciling data together across systems before they can make a decision.
On the organizational side, departments optimize for their own goals. Procurement focuses on cost, operations focuses on keeping shelves stocked, finance focuses on closing the books, and the data degrades at every handoff. Leadership teams increasingly recognize this issue, which is part of why we’re seeing more investment in operations technology that solves these silos with a unified view of the business.
Q: Many companies have already adopted AI tools, yet only 14% say AI has meaningfully improved efficiency. Are businesses overestimating what AI can solve without fixing underlying workflow and data issues first?
A: Yes, and that’s one of the clearest findings from our research. AI is only as good as the data it sits on top of. If a brand is still running on fragmented systems, spreadsheets, and inconsistent product data, AI just surfaces the same inefficiencies faster.
Most businesses started layering AI tools before fixing the underlying processes around documentation, system integration, and product data standardization. So the model produces a forecast or a recommendation that no one trusts, because the inventory data feeding it is three days stale and reconciled by hand. We have seen this play out enough that some consumer goods operations leaders, especially those managing fast-changing demand patterns, have started to distrust AI forecasting outputs, which becomes its own problem.
The brands seeing real AI gains tend to be the ones with clean inventory data, integrated order flows, and standardized product information already in place. Everything else is building on a weak foundation.
It all comes down to the ability to make decisions efficiently by accessing a unified source of truth in real time.
Q: As retailers demand faster launches, better forecasting, and fewer errors, what operational capabilities will separate successful consumer brands from those that struggle over the next few years?
A: The strongest brands are building one operational system that connects inventory, procurement, production, fulfillment, and financial data in real time. When a retailer changes a spec, a manufacturer flags a delay, or a shipping route gets disrupted, the right teams can see it immediately without manual reconciliation.
What separates the winners is increasingly purpose-built consumer goods operations software rather than generic ERPs. A $100K+ NetSuite or SAP implementation was not designed for production tracking, manufacturer coordination, retail compliance, or the packaging and labeling cycles that define consumer goods. Brands that try to bend a generic ERP into that shape end up with the same fragmentation problem they started with, except more expensive.
Ultimately, the companies that win will be the ones that reduce operational friction before customers and retailers experience it.
More from Retail Insider:
“On the technology side, most consumer brands run a stack of fragmented systems that cannot communicate with each other. An enterprise resource platform (ERP) used for business operations that was not built for consumer goods, a separate system at the warehouse, spreadsheets for manufacturer coordination, and a forecasting tool that does not reconcile to actual on-hand inventory. Teams spend a lot of time reconciling data together across systems before they can make a decision.”
Many of these challenges are simple automations, rather than needing to design agents and orchestration. Often businesses invest too much time on workarounds every day, rather than making a one-time investment to “automate” themselves into the 21st century and free up valuable resource for the value-adding activities they can never get to. Having an appreciation of the simplicity of automation is key to moving faster