Operational disruptions caused by delays in information flow during production processes turn into invisible costs. Late detection of quality deviations, inventory records failing to reflect the reality on the shop floor, and engineering changes not reaching relevant processes in a timely manner lead to scrap, rework, urgent procurement, capacity loss, and missed deadlines. Industrial Application Software (IAS), a global player in the enterprise software market, emphasizes that integrating data from the shop floor with ERP processes makes these losses visible before they escalate and provides the opportunity to intervene while production is ongoing.
Manufacturing companies closely monitor direct costs such as materials, energy, and labor. However, because some losses that erode profitability are distributed across different processes such as quality, warehousing, engineering, purchasing, and planning, their total impact can often only be seen in hindsight. The common denominator of these losses, which appear to be independent operational disruptions, is that up-to-date information from the field does not reach the right process on time. Therefore, in production, it is just as important for data to be current, accessible at the moment of decision, and consistent across processes, as it is for the data to be accurate.
Deloitte’s 2025 Smart Manufacturing and Operations Study, conducted with the participation of 600 executives from large manufacturing companies, reveals the operational returns of smart manufacturing investments. 92% of the participants believe that smart manufacturing will be one of the main drivers of competitiveness in the next three years. Companies report that with smart manufacturing applications, they have achieved an average improvement of 10% to 20% in production output, 7% to 20% in employee productivity, and 10% to 15% in available capacity.
The value of a smart manufacturing investment emerges when data generated on the field meets the right business context and transforms into timely decisions. When machinery, quality, warehouse, engineering, purchasing, and planning units operate with information of varying timeliness, a minor deviation can create cost chains that span across multiple processes.
Information Delay Transforms into Cost at Three Points
When a quality deviation goes unnoticed during production, every new product manufactured under the same conditions can amplify the impact of the error. Sorting, additional inspection, changes in the production plan, delivery delays, returns, and warranty expenses are added to the initial scrap or rework costs. According to the 2025 ASQE Insights on Excellence Cost of Quality Study, only 31% of the respondents state that they fully understand the impact of quality costs on their organization’s financial performance. This finding highlights the difficulty of making the total financial impact of quality losses incurred at various stages of production visible.
In inventory management, the quantity shown in the system does not always reflect the usable quantity in production. Although a material may appear available in the records, it could be located in the wrong warehouse, in the incorrect lot, lacking completed quality approval, or reserved for another production order. When physical movements are recorded late in the system or when warehouse and production records diverge, planning relies on inventory that is effectively unusable. As a result, the production line may face downtimes, leading to urgent purchases, unnecessary inventory accumulation, capacity loss, and delivery delays.
In engineering changes, which processes receive the information is just as decisive as when it arrives. When a modification to a material, bill of materials (BOM), routing, or technical document is not reflected across purchasing, planning, quality, and production processes with the same revision data, materials may be ordered or production may proceed based on the outdated specifications. The later the discrepancy is detected, the greater the number of affected orders, materials, and semi-finished products. This escalates the risk of scrap, rework, and missed deadlines.
“The right data can turn into a wrong decision if it arrives late”
IAS IoT Project Manager Tolga Küçük pointed out that cost control is a management discipline that begins while production is ongoing, stating: “Cost control in manufacturing requires being able to see in which process and with which decision deviations occur. The right data can turn into a wrong decision if it arrives late. Furthermore, merely recording an event that occurs on the shop floor is not sufficient. This information must be correlated with the correct production order, material, lot, and process. Otherwise, decisions are made with incomplete or delayed information, and a minor deviation can quickly turn into significant costs. It must be visible within the same workflow which production order and lot are affected by in-process or quality signals, which production plan is affected by an inventory movement, and which bill of materials, routing, and purchasing decision are affected by an engineering change. When all departments operate with the same up-to-date information, the chain of events leading to the loss becomes visible, broadening the scope for intervention before the cost escalates.”
Canias IoT enables real-time monitoring and analysis of production data from machines, control units, sensors, and smart devices using industrial communication protocols. When a predefined event occurs, the relevant data is transferred to the ERP solution. Canias ERP then links the event from the shop floor with the production order, work centers, personnel, material, inventory, lot, quality process, bill of materials, routing, and revision information. Integrated workflows transform this information into the necessary alert, control, approval, plan update, or corrective action.
Monitoring quality, inventory, and engineering change processes within the same data infrastructure simplifies identifying which products, orders, lots, and production steps are affected by a loss. This enables companies to consolidate records explaining the cause of sudden cost spikes with the up-to-date information needed to intervene during ongoing production within a single system. The integration of ERP and IoT brings together real-time reporting, efficiency, cost control, and end-to-end traceability into a unified management discipline.