On a Tuesday morning in March, a production planner at an automotive engine plant in Ohio discovered a problem that would ultimately cost the company over $750,000. A purchase order for aluminum cylinder blocks from their supplier in China — a routine transaction that happened every week — had never been received. The order submission had failed silently seven days earlier due to a portal update, but no one knew until the planner ran a weekly check. By then, the 45-day ocean freight timeline had shrunk to 38 days, and the factory’s production schedule was now in jeopardy.
As a result, the team faced expedited supplier fees, premium air freight for critical components, weather delays, customs holds due to documentation errors, and ultimately a six-hour production line shutdown.
Despite how common this scenario is, many companies remain under-invested in the capabilities needed to prevent it. The assumption persists that good planning software alone can ensure supply chain efficiency. But as this engine manufacturer learned, the gap between planning and execution is where companies see their profit margin disappear.
Supply chain planning and execution serve fundamentally different purposes, operating on different time horizons with different objectives.
Planning occurs before any order is placed. It’s the strategic work of forecasting demand 3 to 24 months ahead, determining what to produce, where to source materials, and how much inventory to carry. They translate those forecasts into supply requirements and answer the question: “What should our supply chain look like?”
Execution, by contrast, starts the moment a purchase order or sales order is created. It operates on a 0-3 month horizon and focuses on a single question: “Is this specific order going to deliver on time and in full, and if not, what are we doing about it?” Execution teams monitor orders in real-time, detect when something is going wrong, and intervene before small problems become expensive failures.
The distinction matters because planning, no matter how sophisticated, cannot account for the countless variables — supplier issues, missed deliveries, documentation errors — that emerge in real-time operations.
From the moment a purchase order is issued until a product reaches its destination, dozens of potential failures lurk in the process.
Purchase orders fail to transmit due to portal issues or EDI errors. Suppliers don’t acknowledge orders within expected timeframes. Advance shipping notices arrive late, incomplete, or in formats that systems can’t parse.
Many companies still rely on manually logging into carrier portals to check shipment status. By the time a delay is discovered, it’s often too late to avoid downstream impacts.
Facilities lack real-time visibility to inbound shipments, making dock scheduling difficult. Trucks arrive after receiving hours end and sit in yards overnight, accumulating detention charges of $200-500 per day.
Customer facilities have their own constraints — dock hours, labor availability, specific requirements — that aren’t always communicated in advance. Late deliveries trigger On-Time In-Full penalties with major retailers, while missing or incorrect proof of delivery documentation leads to payment disputes that take weeks to resolve.
The engine manufacturer’s cylinder block crisis touched every one of these failure points, with each failure compounding the next. With the right capabilities in place, all of it could have been avoided.
The financial impact of execution gaps extends beyond immediate crisis costs. The engine manufacturer’s $750,000 loss breaks down instructively:
Beyond these direct costs, the manufacturer faced mandatory increases in safety stock (tying up $840,000 in additional inventory), elevation to “supplier on watch” status with their customer, and over 400 person-hours diverted to root cause analysis and corrective actions.
Many of these costs were avoidable. If the order acknowledgment failure had been detected within 24 hours instead of seven days, normal ocean freight would have sufficed. If real-time shipment tracking had flagged the customs documentation error before the shipment reached port, the hold could have been prevented. If predictive inventory analytics had identified the impending stockout 72 hours in advance, the production shutdown could have been avoided.
Conservative estimates suggest that 70-80% of the financial impact — over $500,000 — could have been prevented with better execution capabilities. Not through perfect operations, which don’t exist, but through earlier detection and faster intervention.
Organizations with mature execution capabilities — often built around supply chain control towers — approach operations differently than those relying primarily on planning systems.
Real-time visibility forms the foundation by integrating data from ERP systems, transportation management systems, supplier portals, and carrier tracking systems into a single view. They know the status of every order and shipment without manually checking dozens of systems. Purchase orders that aren’t acknowledged within 24 hours trigger automatic follow-ups. Shipments that deviate from expected routes or timing generate alerts based on business impact, not just delay duration.
Predictive analytics enable proactive intervention. Machine learning algorithms analyze historical patterns and real-time conditions to predict which shipments face delay risk, which suppliers are likely to miss commitments, and which inventory positions may lead to stockouts. These predictions provide lead time for corrective action — rebooking freight, expediting production, reallocating inventory — before problems crystallize into failures.
Automated coordination reduces manual effort and accelerates response. Instead of planners spending hours each day chasing carrier updates, automated systems handle routine communications. When documents are missing, AI agents follow up with suppliers. When appointments need rescheduling based on updated arrival times, systems coordinate with facilities. When customers inquire about order status, automated responses provide instant information.
Integrated workflows connect all stakeholders. Suppliers can submit shipping notices in any format — PDF, Excel, email — and systems extract the relevant data. Carriers provide tracking updates through their preferred channels. Customers receive proactive notifications about shipments and can access self-service portals for detailed information. These AI workflows reduce friction, improve communication speed, and create transparency across the supply chain.
The engine manufacturer had good planning systems and capable people. What they didn’t have was an intelligent control tower — the systematic capability to catch the order transmission failure within hours instead of days, spot the documentation error before the shipment hit customs, or see the inventory shortfall coming with enough time to do something about it. Any one of these would have stopped the cascade and saved most of that $750,000.
The business case isn’t complicated. If you’re spending $10-20 million a year on expedited freight, cutting that by even 20-30% puts $2-4 million back in your budget. If your plant goes down a few times a year at $50,000 an hour, preventing just a handful of those shutdowns pays for itself many times over.
Planning tells you what should happen. Execution is what actually makes it happen. Most supply chain organizations have spent twenty years investing in better planning tools — demand forecasting, S&OP platforms, inventory optimization. The execution side has gotten less attention, even though that’s where the weekly firefights happen and where the money actually gets lost. Intelligent control towers that create real-time digital twins of orders, shipments, inventory and assets—combined with AI-powered automation to act on that data — address exactly this gap. One undetected order failure shouldn’t cost three-quarters of a million dollars, but without the right capabilities in place, it does.
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