Ask a manufacturer what it costs to produce a unit, and you will usually get a fast, confident answer. Ask how that number changes when labour varies, machines slow down, or scrap increases, and the certainty starts to fade, and this is often where production planning begins to break down.
At Kodershop, we have seen this pattern repeatedly. Teams are not careless. They are working with systems and processes that were never designed to give a complete, real-time picture of cost. Over time, small gaps in visibility turn into meaningful financial blind spots and operational chaos on the shop floor.
Manufacturers already track costs. Materials are logged, labour is estimated, and overhead is allocated. On paper, it looks structured and controlled.
The issue is that these inputs are often based on assumptions rather than actuals. Standard costs are set once and adjusted infrequently. Production realities change daily. When costing is not grounded in what is actually happening on the shop floor, decisions are made on numbers that no longer reflect the business.
Where Accuracy Breaks Down
Indirect costs are often spread broadly. Energy, maintenance, supervision, and quality control are treated as averages rather than tied to real activity, making some products appear more profitable than they are, and distorting production priorities.
Production performance is not consistently captured, with the impacts of machine downtime, changeovers, and reduced throughput typically not being tracked in detail. These elements affect the cost per unit without existing in the costing model.
Labour is treated as stable when it is not. Skill levels, overtime, and shift variability all influence output. Without tracking actual time against work orders, labour cost remains an approximation. Scrap and rework are usually underreported at a granular level. High-level percentages do not reveal which products, batches, or processes are driving loss. Disconnected systems force teams to reconcile data manually. Inventory, production, and finance often operate in separate environments.
The result is a fragmented view that no one fully trusts.
Mission Produce, a global avocado distributor, implemented a new ERP system in 2021 to improve visibility across inventory, finance, and operations.
Instead of gaining clarity, they lost it.
After they went live, the company could not accurately track core operational data. Teams struggled to answer basic questions about how much inventory they had, what condition it was in, whether orders had shipped, and whether invoices had been processed.
This breakdown was not just an IT issue. It directly impacted operational decision-making.
When you cannot see inventory clearly, you cannot plan production or fulfilment effectively. When you cannot trust order or shipment data, you cannot align supply with demand. When financial and operational data diverge, costing becomes unreliable.
In practical terms, this creates the exact problem many manufacturers face at a smaller scale every day:
- Costs are calculated based on incomplete or outdated information
- Inventory assumptions replace actual availability
- Production decisions are made without real-time feedback
- Financial reporting lags behind operational reality.
- Production schedules are constantly adjusted, delayed, or overridden.
Mission Produce is a large-scale example, but the underlying issue is common. When systems fail to reflect what is actually happening on the ground, the business loses its ability to understand true costs.
And when you cannot see clearly, you cannot cost accurately.
Data that Lives Everywhere
Data exists across the business, of course. But we often find with the businesses we work with that it is scattered. Finance holds part of the picture. Operations hold another. Inventory sits somewhere in between.
Bringing together data across all departments requires time and interpretation. By the time numbers are consolidated, they are already out of date. This is why many costing exercises feel like they are always catching up rather than guiding decisions.
American Adventure Lab faced growing complexity as its product range expanded. Managing hundreds of components across multiple products created challenges in tracking materials, understanding build costs, and maintaining operational control.
Their processes relied heavily on disconnected tools and manual workarounds. This made it difficult to link production activity with financial outcomes.
After implementing a unified system, they were able to connect bills of materials, inventory movements, and production workflows in one place. This provided a clearer view of how products were built and what they actually cost.
The improvement came from alignment rather than automation alone. When operations and finance began working from the same data, costing became more accurate and more actionable.
When You Assume...
When manufacturers move from assumed costs to actual costs, the impact is immediate and often surprising.
Products that appear profitable may reveal thin or negative margins. Processes that seemed efficient begin to show hidden inefficiencies. Eventually, operational improvements become easier to prioritize because the financial impact is visible and aligned with production reality.
This level of clarity changes the conversation inside the business. Finance and operations start working from the same understanding rather than debating whose numbers are correct.
A Practical Way Forward
Improving cost visibility does not require a complete transformation on day one. It starts with identifying where assumptions are replacing actual data. That usually means capturing real production data more consistently, linking inventory directly to work orders, and ensuring that overhead is allocated based on activity rather than broad averages.
From there, the focus shifts to connecting systems so that data flows between teams without manual intervention. This is where platforms like Odoo become relevant. They allow manufacturers to bring production, inventory, and finance into a single environment, reducing the gaps that distort costing.
In an environment where margins are tight and variability is constant, those gaps matter. Understanding true production cost is not about precision for its own sake. It is about making decisions with confidence and protecting profitability over time while keeping production plans grounded in reality instead of constant chaos.