Production cost losses do not always stem from raw materials, energy or labor. Delayed detection of quality deviations, discrepancies between inventory records and actual shop-floor conditions, and engineering changes that fail to reach relevant processes on time can also drive up hidden costs. Tolga Küçük, IoT Project Manager at IAS, explains how ERP and IoT integration can provide real-time traceability in manufacturing and help prevent scrap, rework, capacity losses and delivery delays.

Tolga Küçük
IoT Project Manager
Industrial Application Software (IAS)

The factors that increase manufacturing costs are not limited to raw materials, energy and labor. Delayed detection of quality deviations, discrepancies between inventory data and actual shop-floor conditions, and engineering changes that fail to reach the relevant departments on time can also generate significant losses for manufacturers. Tolga Küçük, IoT Project Manager at Industrial Application Software (IAS), told BBM Magazine that real-time integration of shop-floor data with ERP processes can help prevent a wide range of hidden costs, from scrap and rework to emergency procurement, capacity losses and delivery delays.

When we talk about manufacturing costs, raw materials, energy and labor usually come to mind first. However, you point out that delays in the flow of information can also be a significant cost factor. How do these losses occur?

Manufacturing companies already closely monitor direct costs such as materials, energy and labor. However, some losses that erode profitability are spread across different processes, including quality, warehousing, engineering, procurement and planning. As a result, their total impact often becomes visible only later.

The common factor behind these losses is that up-to-date information from the shop floor does not reach the right process at the right time. Cost control in manufacturing requires companies to identify the process and decision behind each deviation. Accurate data can lead to the wrong decision if it arrives too late. Therefore, it is not enough for data simply to be accurate; it must also be up to date, accessible at the point of decision-making and consistent across processes.

What advantages do smart manufacturing investments offer companies in this respect?

The real value of smart manufacturing emerges when data generated on the shop floor is placed in the right business context and transformed into timely decisions. When machinery, quality, warehouse, engineering, procurement and planning teams work with information that is updated at different intervals, even a small deviation can create a chain of costs extending across multiple processes.

Deloitte’s 2025 Smart Manufacturing and Operations Survey, conducted with 600 executives from large manufacturing companies, also highlights the importance of this transformation. Ninety-two percent of respondents believe smart manufacturing will be one of the primary drivers of competitiveness over the next three years. Companies report that smart manufacturing initiatives have delivered average improvements of 10–20 percent in production output, 7–20 percent in employee productivity and 10–15 percent in unlocked capacity.

A small quality deviation can trigger a major chain of costs

For BBM Magazine’s core industries, particularly flour, pasta, bakery and industrial food production, maintaining consistent quality is critical. How can delayed quality data translate into higher costs for manufacturers?

When a quality deviation cannot be detected while production is still underway, every additional product manufactured under the same conditions can increase the impact of the problem. An issue that initially appears to involve only scrap or rework can subsequently lead to additional costs associated with sorting, extra inspections, production rescheduling, delivery delays, returns and warranty claims.

It is also noteworthy that in the 2025 ASQE Insights on Excellence Cost of Quality Research, only 31 percent of respondents said they fully understood the impact of quality costs on their organization’s financial performance. This demonstrates how difficult it can be to make the total financial impact of quality losses occurring at different stages of production fully visible.

The key here is not simply to record an event that occurs on the shop floor. The information must be linked to the correct production order, material, lot and process. Otherwise, decisions are made on the basis of incomplete or delayed information, and a minor deviation can quickly develop into a significant cost.

Does a similar information problem occur in inventory management?

Absolutely. The inventory quantity shown in the system does not always represent the amount that is actually available for production. A material may appear to be in stock but could be located in the wrong warehouse, belong to an unsuitable lot, still be awaiting quality approval or have already been allocated to another production order.

When physical movements are entered into the system late, or when warehouse and production records become disconnected, planning decisions are based on inventory that is not actually available for use. This can cause production lines to wait. Emergency procurement, unnecessary inventory accumulation, capacity losses and delivery delays may then follow. Inventory accuracy is therefore not only a warehouse management issue but also an essential element of production continuity and cost control.

Engineering changes must reach all processes simultaneously

Product recipes, bills of materials, routings and technical documents are continuously updated in manufacturing facilities. What risks arise when engineering changes are not reflected in the system on time?

With engineering changes, it is important not only when the information reaches the organization but also which processes it reaches. If a change to a material, bill of materials, routing or technical document is not reflected with the same revision information across procurement, planning, quality and production processes, materials may be ordered or production may continue according to an outdated specification.

The later such a discrepancy is detected, the greater the number of orders, materials and semi-finished products that may be affected. This increases the risk of scrap, rework and delivery delays. Engineering changes therefore need to be communicated to all relevant processes simultaneously and in a traceable manner.

How does the integration of ERP and IoT systems make a difference at this point?

Companies need to be able to see, within the same workflow, which production order and lot are affected by a production or quality signal, which production plan is affected by an inventory movement, and which bill of materials, routing and procurement decision are affected by an engineering change. When all departments work with the same up-to-date information, the chain that creates the loss becomes visible and the opportunity to intervene before costs escalate becomes much greater.

Canias IoT uses industrial communication protocols to enable real-time monitoring and analysis of production data generated by machines, control units, sensors and smart devices. When a predefined event occurs, the relevant data is transferred to the ERP solution.

Canias ERP then links the shop-floor event to production orders, work centers, personnel, materials, inventory, lots, quality processes, bills of materials, routings and revision information. Through integrated workflows, this information can then trigger the necessary alerts, controls, approvals, planning updates or corrective actions.

Can we therefore say that this integration enables managers not only to report costs, but also to intervene while production is still underway?

That is the critical point. In a traditional approach, some losses may only become apparent when cost figures are reviewed at the end of a reporting period. However, cost control in manufacturing needs to begin while production is still underway.

When quality, inventory and engineering change processes are monitored within the same data infrastructure, companies can identify more quickly which products, orders, lots and production stages are affected by a problem. This gives them access not only to historical records explaining why costs have increased, but also to up-to-date information that enables them to intervene while production is still running.

This is one of the most important benefits of ERP and IoT integration. Real-time reporting, productivity, cost control and end-to-end traceability cease to be separate issues and become components of a common management discipline.

Finally, what would be your most important message to companies planning investments in digitalization for their manufacturing operations?

Technology investments should not be viewed simply as a way of collecting more data. What matters is the ability to use that data at the right time, in the right context and at the right decision point. When information from the shop floor is linked to production orders, materials, lots, quality, inventory and engineering processes, a company can see not only what has happened, but also why it happened and which processes have been affected.

Preventing a small deviation in production from developing into a major cost depends on making the problem visible as early as possible. An up-to-date and integrated data infrastructure gives manufacturers precisely this capability.