Manufacturing KPIs Cheat Sheet

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Written By Jeff Winter

Imagine you’re a pilot flying a state-of-the-art jet. The skies are clear, the engines are humming, and everything seems to be going smoothly. But what if your dashboard suddenly goes blank? No speedometer, no fuel gauge, no altitude indicator. You’re still flying, but now it’s all guesswork. That’s a terrifying scenario, right?

Now, swap that jet for your manufacturing operation. Your machinery might be running, your employees might be hard at work, and products might be rolling off the line. But without Key Performance Indicators (KPIs), you’re flying blind. KPIs are the instruments on your dashboard—they give you the data you need to make informed decisions, spot potential issues before they become problems, and keep your operation on course.

I put this cheat sheet together to help companies in their KPI selection process, including the KPIs I see used most often.

ISO 22400-2:2014: Key Performance Indicators (KPIs) for manufacturing operations management

ISO 22400-2:2014 is a standard that lays out key performance indicators (KPIs) for managing manufacturing operations. It’s like a toolkit for manufacturers to keep tabs on how well their production processes are running. The standard offers 34 different KPIs that measure things like how efficiently resources are being used, how available equipment is, the quality of output, and how much waste or scrap is being produced. Most of these KPIs made it into the cheat sheet I created in some form.

Why is it valuable? Well, these KPIs give manufacturers a clear way to monitor their operations, spot issues early, and make smarter decisions to keep things running smoothly. Plus, with the help of modern tech-like web-based systems, these KPIs can be tracked in real-time, making it easier to respond quickly to any problems.

But it’s not a one-size-fits-all solution. The KPIs in this standard are primarily designed for discrete manufacturing, like making individual parts or assemblies. If you’re in a process industry, like chemicals or food production, some of these KPIs might not be as useful without some tweaking. So, while it’s a great starting point, it may require some adjustments depending on your specific needs.

How Industry 4.0 is Reshaping Performance Evaluation

Industry 4.0 is redefining how we measure success in manufacturing. Traditional KPIs, like production rates and defect counts, are still important, but they’re no longer enough. The rise of smart factories, IoT devices, and real-time data analytics means that we can now track metrics that were once hidden from view. We’re talking about granular insights into machine health, energy consumption, and even predictive maintenance—all in real-time.

Moreover, the shift to more integrated and automated operating models means we need new KPIs that can keep pace with these changes. What worked in a traditional manufacturing environment may no longer cut it in a smart factory, where agility, responsiveness, and data-driven decision-making are key. KPIs in Industry 4.0 aren’t just about what we’re producing—they’re about how we’re producing it, how quickly we can adapt, and how well we’re using our resources.

According to IoT Analytics, on average, 73% of manufacturers name operational KPIs as important or very important. Supply chain-focused KPIs follow shortly behind with also a 73% average.

Performance Evaluation and Monitoring Methods

Performance evaluation isn’t just about tracking a single number. Instead, it’s a layered approach, much like concentric circles, where each layer builds on the one before it. At the outermost layer, you have the most data points, and as you move inward, these data points become more refined and focused until you reach the core—the Key Performance Indicators (KPIs). Each layer plays a crucial role in providing a comprehensive view of your manufacturing operation, but it’s the KPIs at the center that ultimately drive your strategic decisions.

  • Measures: The outermost circle represents the raw data. This data forms the basic building blocks of performance evaluation and is typically collected through direct measurement. For example, the number of hours worked, units produced, or energy consumed are all measures. While they’re plentiful and provide essential information, measures on their own don’t tell you much about how well your operation is performing.

  • Metrics: Moving inward, we arrive at metrics. Metrics are measures that have been put into context to provide more meaningful insights. They’re the trends and averages that help you understand patterns over time. For instance, calculating the average units produced per hour or the energy consumption per unit produced transforms raw measures into actionable metrics. Metrics start to paint a clearer picture of performance but still aren’t directly tied to strategic goals.

  • Performance Indicators (PIs): As we get closer to the core, metrics evolve into Performance Indicators (PIs). PIs are metrics that are directly linked to specific business objectives. For example, if one of your goals is to enhance production efficiency, then tracking the metric of units produced per hour could become a PI. PIs are fewer in number than measures and metrics, and they start to focus your attention on what really matters to your operation.

  • Key Performance Indicators (KPIs): At the very center of our concentric circles are the KPIs—the critical few PIs. KPIs are the most important metrics that reflect your strategic success. They are the core of your performance evaluation system because they directly indicate whether you’re meeting your business objectives. A KPI might be Overall Equipment Effectiveness (OEE) or on-time delivery rates. KPIs are limited in number, highly focused, and are the metrics that, if missed, could mean missing your strategic targets.

In traditional manufacturing environments, KPIs have primarily focused on managing and optimizing daily operations—tracking efficiency, quality, and cost to ensure the business runs smoothly. However, with the advent of Industry 4.0, the focus of KPIs is shifting. As digital transformation becomes a strategic priority, businesses are increasingly moving beyond just running and improving existing operations to fundamentally transforming their processes and models. This transformation requires a new approach to KPIs, with a stronger emphasis on diffusion and adoption metrics. These KPIs are essential for guiding and measuring the success of digital initiatives, ensuring that new technologies are not only implemented across the organization but are also embraced and effectively utilized by the workforce. This shift reflects the broader impact of Industry 4.0, where the goal is not just to enhance current operations but to create a connected, intelligent, and adaptive manufacturing environment that redefines the way the business operates.

  • Diffusion KPIs: These measure how widely a specific technology is being implemented across various departments or processes. For example, in the context of adopting predictive maintenance systems, a diffusion KPI might track the percentage of machinery equipped with sensors for real-time monitoring across the entire production line. This KPI is crucial for understanding how extensively the new technology is penetrating the organization and is primarily used to guide transformational initiatives.

  • Adoption KPIs: These assess how effectively the new technology is being used by the workforce. For instance, after installing predictive maintenance systems, an adoption KPI could measure the rate at which maintenance staff are using predictive analytics data to schedule repairs instead of relying on traditional reactive maintenance. This type of KPI is essential for ensuring that the workforce is engaging with the new technology, indicating the success of transformational efforts.

  • Performance KPIs (Standard): These focus on measuring the operational impact of the technology once it has been adopted. Continuing with the predictive maintenance example, a performance KPI might track the reduction in unplanned downtime as a result of using the predictive maintenance system. Performance KPIs are typically used to 'run' and 'improve' the business by enhancing efficiency and reducing costs, but they do not necessarily indicate a transformative change in the organization. Instead, they ensure that the business benefits from the technology in a way that supports ongoing operations.

Stages in Performance Evaluation

Performance evaluation can be broken down into different stages, helping you ensure you are looking at the right things at the right time.

  • Resources: Resources are the inputs that power everything you do. This includes tangible items like materials, equipment, and finances, as well as intangible elements like time, labor, and data. For any organization, effectively managing resources is the foundation of success. If you don’t have the right resources—or enough of them—your ability to carry out activities and achieve goals is compromised.

  • Activities: Activities are the processes and tasks that turn resources into something valuable. This is where the actual work happens—where inputs are transformed into outputs. Whether it’s a manufacturing process, a service delivery, or a marketing campaign, activities are the heart of your operation. They define how efficiently and effectively you use your resources.

  • Outputs: Outputs are the direct results of your activities—the products, services, or deliverables that come out of your processes. They are tangible and measurable, providing a clear indication of how well your activities are performing. Outputs are what you produce, and they are essential for understanding the immediate effectiveness of your operations.

  • Outcomes: Outcomes represent the short-term effects or benefits that arise from your outputs. They go beyond just the immediate results, focusing on the value these results bring to your organization or stakeholders. Outcomes are where you start to see the impact of your outputs on your broader goals.

  • Impact: Impact is the long-term effect of your work—the broader influence and significance of your outputs and outcomes over time. Impact looks at how your activities and outputs contribute to larger goals, like organizational growth, market influence, or social change. This is the stage where you evaluate the ultimate success of your efforts.

Monitoring and Evaluating

Together, monitoring and evaluation provide a comprehensive view of organizational performance. Monitoring ensures that the present is under control, while evaluation helps ensure that the future is bright. By understanding and effectively managing both, organizations can optimize their operations, improve outcomes, and achieve long-term success.

  • Focus of Monitoring: All about real-time, day-to-day oversight of your processes. It’s mainly concerned with the activities and outputs stages—making sure that resources are being used correctly and that activities are being carried out as planned. The primary goal of monitoring is to ensure that everything is functioning smoothly and efficiently on the ground level. Typically, the focus of monitoring falls to frontline managers, supervisors, and team leaders. These individuals are directly responsible for the day-to-day operation of resources and activities. Their job is to ensure that everything is running according to plan and to address any issues as they arise.

  • Focus of Evaluating: All about taking a step back to look at the bigger picture. It’s concerned with the outcomes and impact that result from your outputs and activities. Evaluation is typically conducted after processes have been completed and focus on understanding the effectiveness and efficiency of the entire operation. This evaluation is typically the domain of executive management, strategic planners, and external auditors or evaluators. These individuals are responsible for analyzing the results of operations to ensure they align with the organization’s long-term goals. They use evaluation to make decisions about future strategy, resource allocation, and process improvements. Their role is to understand whether the organization is on the right path and how it can improve moving forward.

Leading and Lagging Indicators

A critical part of performance evaluation is understanding the difference between leading and lagging indicators. These indicators help you track and predict performance, enabling you to make informed decisions at every stage of the process.

  • Lagging Indicators - Measuring Current Conditions: Lagging indicators are typically output-oriented, meaning they measure the results of processes that have already taken place. These indicators provide a clear view of what has happened, allowing you to confirm trends and patterns within your manufacturing operation. They are easier to measure but harder to influence, as they reflect the end results of your efforts. n a manufacturing setting, a common lagging indicator might be the total number of units produced in a month. This tells you how much was accomplished but doesn’t give insight into what might affect future production. Another example could be the defect rate, which measures the percentage of products that fail to meet quality standards after they’ve been manufactured. This indicator helps confirm the quality of your output but doesn’t help you prevent defects before they occur. Lagging indicators are essential for understanding how well your operation has performed in the past. They provide valuable data that can be analyzed to identify areas for improvement. However, since they report on what has already happened, they do not offer the ability to influence future outcomes directly.

  • Leading Indicators - Predicting Future Trends: Leading indicators are more predictive in nature. These indicators provide insights into future performance by analyzing current conditions and activities. While they are more challenging to measure, leading indicators are easier to influence, giving you the opportunity to make adjustments before issues arise. n manufacturing, a leading indicator might be the frequency of equipment maintenance. Regular maintenance can predict and prevent machine breakdowns, which in turn can reduce downtime and improve overall production efficiency. Leading indicators are valuable because they allow you to take proactive steps to influence future performance.

  • Balancing Leading and Lagging Indicators: In a well-rounded performance evaluation strategy, both leading and lagging indicators play vital roles. Leading indicators help you forecast and shape future performance, while lagging indicators allow you to confirm and analyze past results. For instance, if your goal is to increase overall equipment effectiveness (OEE), you might use leading indicators like the frequency of preventative maintenance or the rate of employee training on new machinery. These actions can help you improve your OEE over time. The lagging indicator in this scenario would be the OEE score itself, which reflects how well the equipment performed after all activities have been completed.

References:

Jeff Winter
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