Protecting Margins Through Connected Trade Execution

Food & Beverage News: Insights, Safety, and Dining Trends

Every food manufacturer knows margin pressure. Fewer know exactly where it’s bleeding out.

Deductions, billbacks, and short pays often grab the spotlight, but they’re merely the final symptoms of damage that occurred much earlier. To explore the root causes of these issues, we consulted Drew Shields, solutions director at iTradeNetwork Inc. 

Drew has more than a decade of experience in analytics, finance, and enterprise systems within the food and beverage supply chain. He partners with manufacturers, distributors, and foodservice operators to improve forecasting accuracy, pricing execution, and margin performance. His insights can help manufacturers determine where margin leaks originate, define the components of a truly auditable workflow, and distinguish proactive margin protection from simple quarter-end cleanup.

Q. Where do you think the biggest invisible margin leaks begin, before they turn into deductions, billbacks, or disputes? 

Drew Shields: Invisible margin leaks begin with disconnected processes and fragmented data. When pricing, contracts, and item data live across multiple systems, it becomes difficult to detect mismatches early in the supply chain. 

Consider this example: A food manufacturer negotiates a promotional price with a distributor for a group of SKUs. The manufacturer updates the pricing in the distributor agreement, but fails to reflect that change across all their internal systems. When the distributor sells the product at the agreed-upon price, they submit billbacks to recover the difference between that price and the previously contracted rate. Due to the misaligned information across systems, the manufacturer must manually review each billback to determine if it is valid. Over time, this erodes efficiency and margins.

However, if manufacturers maintained pricing and contract data in a single, consistently updated system, they would reduce the risk of applying the wrong rates or making pricing errors across contracts. Issues would surface earlier, reducing the likelihood that small discrepancies turn into deductions, billbacks, or disputes.

Q. What are the first signs that contract terms, item data, or pricing are starting to drift between systems or partners?

DS: Drifting between systems and partners often begins long before contract terms, item data, or pricing errors appear. Most issues begin with miscommunication. A manufacturer takes a phone call and tracks the updated information in a spreadsheet. Distributors discuss pricing information across different Slack and Teams channels. Each person may hold a different piece of information necessary for the supply chain to function. In many cases, it is not an individual failure but the result of disconnected systems and processes.

Newer AI-powered platforms mitigate these risks. AI-enabled systems can scan email threads, PDFs, and other documents to extract exact line-items. AI can then interpret these line-item details and compare them with existing product and trading partner data, preparing data from all fields and SKUs for conversion to OMS transactions.

Automated data consolidation with newer systems is essential in mitigating system and partner drift. Without this data collection and interpretation, miscommunication will proliferate, leading to increased contract terms, item data, and pricing errors. 

Q. If a manufacturer could improve just one upstream process to cut down on short pays and claims, which would you focus on first, and why? 

DS: One of the most important processes to improve upstream is the state of manual purchase orders. Currently, the supply chain involves manually entering hundreds of emailed, faxed, and verbal orders into OMS and ERP systems. This process is tedious and inefficient, ultimately translating into operational and financial consequences. When product must wait hours while manufacturers enter data into OMS, shelf life deteriorates.

What the industry needs is to turn this point of friction into a continuous flow. Integrating AI into these stagnant processes could help supply chains improve efficiency. With AI, manufacturers can automatically digitize every order, integrate collected data directly into OMS, and send automated confirmations to buyers. Leveraging this technology effectively helps reduce the amount of time a product is waiting on manual processes and can expedite its movement to the shelf.

When product movement can maneuver around manual entries, it will remain fresh and reduce stressors related to meeting delivery windows or delivering damaged/spoiled products. When manufacturers can remove these operational barriers up-front, short pays and claims will naturally decrease.

Q. In practice, what does an auditable workflow for pricing, rebates, and claims look like? 

DS: An auditable workflow involves mapping every detail of trade and spending to help eliminate error-prone order intakes. Most trade programs are constrained by inconsistent input data. Introducing automation into the process helps standardize formats and verify that clear data is entered into OMS, allowing for structured pricing, rebates, and claims formatting.

Consider this in practice: A packaged food manufacturer signs a contract with a distributor. The contract outlines a set price and a quarterly rebate for the distributor if they purchase a certain amount of product. With AI, each purchase order, invoice, product ID, and quantity is automatically translated into OMS data, without any unnecessary manufacturer contribution. When the distributor submits a claim at the end of the quarter, the system can automatically determine the rebate liability based on the accrued data. Each step is tracked within the system, allowing finance teams to verify how the rebate amount was calculated.

Without automation, manufacturers must manually enter each input into OMS, which can introduce unnecessary errors and lead to incorrect final rebate amounts. With automation, pricing, rebates, and claims are documented accurately at each order touchpoint, reducing manual work , and encouraging an auditable workflow within the supply chain.

Q. How can manufacturers tell if they are truly preventing leakage, instead of just improving quarter-close cleanup?  

DS: Manufacturers can tell they are preventing leakage when problems are caught upstream. This typically looks like leveraging modern platforms to reduce siloed information and then applying connected data directly into manufacturer workflows.

Workflow controls and automation technology should leverage the full extent of available information to determine when invalid claims, pricing drifts, and mismatched distributor data occur, before they cause major issues for back-office teams. 

When errors are caught before they turn into deductions, disputes, or liabilities, organizations should see measurable improvements across the entire supply chain, ultimately reflected within profit and loss statements. Manufacturers can then lean on automated systems to review historical data and detect patterns, providing organizations with actionable insights.

Quarter-close cleanups can appear as utilizing automated tools to clear large claims quickly or sort extensive deductions after the fact. Long-term revenue leakage prevention involves optimizing performance across the entire value chain to prevent faulty deductions and claims from occurring in the first place, providing manufacturers with the tools to sustain financial growth.

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