How do you measure your manufacturing process?

1 Key performance indicators

Defining key performance indicators (KPIs) is one of the first steps in measuring your manufacturing process. KPIs are quantifiable metrics that reflect your strategic goals and objectives, and should be chosen based on the SMART criteria. Examples of common manufacturing KPIs include throughput, yield, downtime, waste, and customer satisfaction. It is important to align KPIs with your vision, mission, and values, and to communicate them clearly to your team and stakeholders. Doing so will help ensure that you are able to track the progress of your manufacturing process effectively.

2 Data collection methods

Once you have your KPIs, you need to collect data to measure them. Different methods and tools are used for data collection, depending on the type and source of data. Manual data collection involves using paper forms, checklists, surveys, or interviews to gather data from people or processes. This is simple and inexpensive but can be prone to human errors, biases, and delays. Automated data collection uses sensors, scanners, cameras, or software to capture data from machines or systems; although fast and accurate, it can be costly and complex to implement and maintain. Hybrid data collection combines manual and automated methods to collect data from different sources; this is comprehensive but requires more coordination and integration. When choosing a data collection method, consider what best suits your KPIs, resources, and capabilities. Additionally, ensure your data is reliable, valid, and consistent.

3 Data analysis techniques

After you collect your data, you need to analyze it to extract meaningful insights and trends. Depending on the type and purpose of data, there are different techniques and tools for data analysis. Descriptive analysis involves summarizing and visualizing your data with charts, graphs, tables, or dashboards to understand the current state and performance of your manufacturing process. Diagnostic analysis uses statistical methods, such as correlation, regression, or hypothesis testing to explore the causes and effects of your data. Predictive analysis uses machine learning, artificial intelligence, or simulation to forecast or estimate the future outcomes of your data. You should choose the data analysis technique that best suits your KPIs, questions, and goals. Additionally, it is important to ensure that your analysis is objective, transparent, and actionable.

4 Data presentation methods

The final step in measuring your manufacturing process is to present your data and analysis to your audience, such as your team, management, or customers. There are various methods and tools for data presentation, each with its own purpose. Reports provide a detailed and structured description of your data and analysis, with text, images, tables, charts, or graphs. Presentations offer a concise and engaging overview of your data and analysis through slides, videos, animations, or interactive elements. Dashboards are interactive and dynamic interfaces that provide a real-time and customized view of your data and analysis. To ensure the most effective presentation of your data, you should choose the method that best suits your data, audience, and purpose. Additionally, you should be sure that your presentation is clear, concise, and compelling.

5 Tips and best practices

Measuring your manufacturing process can be a challenging and rewarding task, but it can also be improved and refined over time. To measure your manufacturing process effectively, you should clarify why, what, how, and when you want to measure it, as well as the resources, time, and budget available. It is important to involve your stakeholders throughout the project and consult them for feedback and suggestions. Following the PDCA cycle (Plan-Do-Check-Act) is essential for planning data collection and analysis, checking results and outcomes, and acting on findings and recommendations. Benchmarking and comparing your performance with industry norms or competitors' can help you identify strengths and weaknesses as well as opportunities and threats. As your manufacturing process evolves, it is important to review and update the measurement project accordingly. By using these methods and tools, you can measure your manufacturing process effectively while continuously improving it for greater quality, efficiency, profitability, customer satisfaction, and loyalty.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?