Modern manufacturing, which traces its origin back to the 19th century, has always been about numbers. Its techniques, as perfected by Henry Ford and the “scientific management” legend, Frederick Winslow Taylor, were based on extensive, continuous measurements. How many parts are we making? What size? How many are defective, and so forth? The process of measuring manufacturing has come a long way since the stopwatch and time-motion-studies of “Taylorism,” however. Today, it’s all about Internet of things (IoT) sensors and big data analytics.
The fundamentals, though, have not evolved so much. Manufacturers establish quantitative targets that define success for them, e.g. the speed of production or the utilization of a piece of equipment. These are known as Key Performance Indicators (KPIs). In our recent Manufacturing KPI whitepaper, we explain how technology has made powerful, flexible measurement systems with KPI capability both affordable and user-driven.
Why KPIs Matter in Manufacturing
Manufacturing managers like data and KPIs because they provide a way to measure how well manufacturing operations are doing. The goal is to address issues before it becomes a financial problem. KPIs are also used to improve performance and results. Manufacturing can always get better, more precise, less costly, higher quality and so on. At a high level, KPIs help senior managers make decisions about the overall business. For instance, if executives determine that a competitor is achieving better quality or asset utilization, that might prompt them to make investments or change operations.
Types of Manufacturing KPIs
Manufacturers typically rely on two main types of KPIs. A historical KPI is a measurement of production or financial activities in the past. Examples include measures of sales, costs, margins, cash flow or asset utilization. Historical operational KPIs might track a figure like the percentage of goods returned as defective.
A predictive KPI, in contrast, looks at current and past data to anticipate future events. These might comprise market research data and historical sales performance. A predictive KPI could blend analysis of multiple data streams to predict sales volume for a particular product.
Manufacturing KPI Examples
Having worked with numerous manufacturers on data analytics projects from ERP systems, we have seen different KPIs put to good use. Examples include:
- Plan vs. Actual Hours and Cost—Charting actual hours and costs against plan offers a good indicator of a plant’s effectiveness. Over time, managers can use this KPI to spot trends and detect early warnings of potential problems, e.g. seeing the impact of a change in crude oil prices on the cost of plastics.
- Utilization and Capacity—Manufacturing managers generally want high rates of utilization for equipment. A high KPI in this regard would suggest a strong Return on Assets (ROA). However, this KPI could be offset by another KPI that tracks the length of time finished goods inventory sits in the warehouse. High ROA may not be a good goal if it means depleting cash reserves to manufacture unsold products. The KPIs give managers the data points they need to figure out what they want to do.
- Scheduled Production—KPIs can be presented visually on ERP dashboards. Production schedules offer a good example. At a glance, plant managers can look at scheduling KPIs and see if there are bottlenecks affecting throughput, potential delays and so forth.
To learn more about KPIs in manufacturing, click here to read the full guide.
Systematizing the KPI Process With Acumatica Cloud ERP
Today’s KPI dashboards are truly flexible, adaptable, and user-driven. There’s no need to draw up a detailed description of the changes and beg IT to recode the reports. User-friendly tools make changes and new reports simple and easy, putting the user firmly in the driver’s seat. Acumatica Manufacturing ERP is cloud-based so the information is readily available on any device, at any time, from anywhere. And Acumatica’s cloud-based applications are built for real-time updates and a high level of flexibility so your KPIs remain dynamic and responsive in every sense of the word.