This is Part 2 of Aligning Factory and Supply Chain, our special series for supply chain and operations leaders working to close the gap between planning and execution. In Part 1, we explored why factory plans so often collapse mid-week. In this edition, we examine a deeper issue—how bad data quietly erodes trust, breaks collaboration, and misguides decision-making across the factory-supply chain interface.
When Strategy and Execution Run on Different Realities
It’s a quiet killer of efficiency. A planning team adjusts the production forecast to reflect a spike in demand, only to learn a week later that the factory couldn’t meet the output—because a key component flagged as available was, in fact, backordered. On the floor, supervisors scramble to adjust schedules. Procurement pushes emergency POs. But none of this should have happened. The problem wasn’t the plan. It was the data.
This is the invisible fracture inside many modern manufacturers: operations and supply chain teams are trying to collaborate while working from different versions of the truth. Until that changes, alignment will remain an aspiration rather than an operational reality.
When Supply Chain and Factory Teams See the Same Problem, Differently
One of the most persistent obstacles to alignment is also one of the most mundane: inconsistent, outdated, or poorly maintained planning data. It manifests in small ways—a lead time that’s no longer accurate, a safety stock level that was never reviewed post-COVID, an item master that lists three versions of the same part. But these small cracks compound.
From the outside, it might look like supply chain is over-ordering or the factory is missing targets. In reality, both functions are responding rationally to bad signals. Planning assumes material is available. Production knows it isn’t. Neither is wrong—they’re just operating from misaligned information.
This is where many alignment efforts falter. The instinct is to hold more meetings, realign KPIs, or invest in a new planning platform. But if the foundational data is broken, all those efforts are built on sand. As one senior director at KPMG put it, “You cannot orchestrate the end-to-end supply chain if every function is using a different set of assumptions.”
Why Mistrust in the System Becomes the System
Over time, these data issues don’t just affect plans—they affect culture. Factory teams begin to rely on tribal knowledge. Planners start overriding system recommendations based on gut feel. Workarounds become standard practice. The formal systems—ERP, MRP, APS—still run, but nobody fully trusts them. The result is a widening gap between the designed flow of information and the actual flow of work.
This gap doesn’t just create inefficiency—it creates friction. A factory manager questions a PO suggestion. A supply planner challenges a production constraint. Both are frustrated, but neither has a full picture. Alignment becomes harder because the underlying facts aren’t shared.
The solution isn’t a better dashboard. It’s cleaner, verified, and consistently maintained master data. This includes accurate lead times, clear order policies, reconciled part numbers, and a commitment to ongoing data governance. Only then can digital tools and cross-functional processes truly serve their purpose: to enable decisions that reflect reality.
Alignment Starts With the Signal
True integration between factory execution and supply chain planning begins not with collaboration sessions, but with signal clarity. Clean, reliable data is the common language that allows both functions to coordinate with confidence. When a material shortage is real—and not a false flag—it triggers the right response. When production constraints are captured in the plan, procurement can act early. It’s this synchronicity that enables agility.
According to PwC’s 2024 Global Manufacturing Outlook, nearly 70% of operations leaders say that poor data quality is the single biggest blocker to extracting value from their digital investments. Technology alone isn’t failing them. What’s missing is a shared foundation. Visibility only matters if the data is trusted. Collaboration only works if the facts are consistent. Strategy and execution only align when they’re built on the same source of truth.
Fix the Fundamentals, Then Scale the System
There’s a tendency to treat data quality as a technical or admin issue—something to be delegated, cleaned up once, and moved on from. That mindset is part of the problem. Data is not just a system input. It’s an operational asset. It defines how decisions are made, how issues are escalated, and how trust is built between functions.
For manufacturers aiming to synchronize planning and execution, the path forward doesn’t begin with AI or a next-gen control tower. It begins with lead times that reflect actual supplier performance. With order policies that mirror real factory constraints. With master data that people across sourcing, planning, and production believe in.
Factory and flow are only truly aligned when the information that connects them is accurate, timely, and shared. Anything less is just well-intentioned guesswork, dressed up as strategy.
