In order to make production processes as efficient as possible, it is important to regularly monitor, evaluate and, if necessary, optimize their performance. Key performance indicators (KPIs) help with this. How this works and which key performance indicators are important for industrial companies is explained below.
What are key performance indicators?
Key performance indicators or KPIs are key figures that industrial companies can use to monitor the efficiency, quality and profitability of production processes. It is crucial that the KPIs are carefully selected. It is therefore not a question of collecting just any key figures, but of identifying key performance indicators.
Why are key performance indicators important for production processes?
In order for industrial companies to remain competitive, production processes must be designed in such a way that they run as quickly as possible, at low cost and with high quality. Nothing should be left to chance here. This means that efficiency, quality and profitability must be continuously monitored. KPIs are used for this purpose. They enable a transparent evaluation of your own production processes. At the same time, the key performance indicators help to identify weak points. In this way, suitable optimization measures can be developed to improve production processes. KPIs also offer the opportunity to monitor the effectiveness of these optimization measures. This allows ineffective measures to be identified immediately.
What are important KPIs for the industry?
Which key performance indicators are relevant for your own production processes must be determined individually. This is because meaningful conclusions can only be drawn from the results if the KPIs are tailored to your own production situation. In addition, you should not work with too many KPIs, as the evaluation of the results can otherwise become confusing and unnecessarily complicated. Some of the most important KPIs for the industry are briefly presented below.
Overall equipment effectiveness (OEE)
The overall equipment effectiveness (OEE) can be used to make statements about the productivity of a system or individual machines. The parameters availability, performance and quality are usually used to calculate the OEE. If the overall equipment effectiveness KPI does not fit, the productivity of the equipment must be optimized.
Lead time or cycle time
The lead time (LT) or cycle time is an important KPI. It records the total time that elapses within a company from the receipt of an order to the completed delivery of the finished product. The shorter the lead time, the more competitive the company is. The total cycle time can be broken down into smaller areas. This allows the KPI to be evaluated in an even more differentiated way: For example, a distinction can be made between the production lead time and the delivery lead time. Weak points can thus be identified more precisely, enabling a more targeted approach to improvement measures.
Production costs per unit
The production costs per unit (unit cost = CPU) allow differentiated cost control and enable the best possible pricing. To calculate this KPI, the total production costs are divided by the number of units produced. It is crucial to consider all relevant manufacturing costs, as this is the only way to derive the optimum sales price from the KPI.
Complete and timely delivery
The on-time-in-full (OTIF) key performance indicator indicates how many orders were completed without delays or errors. Incomplete or late deliveries, on the other hand, reduce the success rate. This KPI is crucial for customer satisfaction, as they want to receive punctual and complete deliveries for their orders.
Production Schedule Accomplishment (PSA)
Production Schedule Adherence (PSA) is a key performance indicator that shows how a company's actual production compares to planned production. A low PSA value indicates problems with planning and/or implementation.
What role do digital solutions play in connection with key performance indicators?
KPIs are key performance indicators for companies. In order for the results to be usable, it is important that KPIs can actually be measured and that these measurements are carried out accurately. They must then be evaluated, as this is the only way to interpret the data and use it for the development and implementation of optimization measures. Smart technology equipped with innovative measurement sensors and data analytics applications are important key elements in connection with key performance indicators. They not only help with data collection, but also with data analysis and thus make a significant contribution to increasing productivity in the long term.