How do you analyze the root causes of variance and implement corrective actions to improve yield?

2 Why is variance analysis important?

Variance analysis is important because it helps you monitor and control the performance and quality of your process, and identify opportunities for improvement. By analyzing the variances, you can find out the root causes of the deviations, and take corrective actions to eliminate or reduce them. This way, you can improve the efficiency and effectiveness of your process, and increase the yield and profitability. Variance analysis also helps you evaluate the impact of external factors, such as market conditions, customer demand, or supplier performance, on your process, and adjust your plans accordingly.

3 How to perform variance analysis?

In order to perform variance analysis, you must first define the standards or targets for your process, such as desired output, quality, cost, or time. Then, collect the actual data for your process and calculate the variances by subtracting the actual results from the standards. Further, analyze the variances by breaking them down into their components or sources and identify the root causes of the variances with tools such as fishbone diagrams, Pareto charts, or 5 whys. Finally, implement corrective actions to address the root causes and prevent or minimize future variances.

4 What are some examples of variance analysis?

Variance analysis is an important tool for manufacturers to monitor their production and identify areas for improvement. For example, a car manufacturer can compare the actual number of cars produced in a month with the planned number, and calculate the production volume variance. Then, they can analyze the reasons for the variance and take actions to fix them. Similarly, a bakery can compare the actual quality of its bread with the standard quality and calculate the quality variance. After that, they can analyze the factors that affect the quality and make adjustments to improve them. Lastly, a clothing factory can compare the actual cost of making a shirt with the budgeted cost and calculate the cost variance. They can then analyze the components of the cost and find out ways to reduce them.

5 What are some best practices for variance analysis?

Making your variance analysis more effective and efficient requires following certain best practices. One should set realistic and achievable standards or targets for the process, based on historical data, benchmarks, or customer expectations. Additionally, accurate and timely data for the process should be collected with reliable and consistent methods and tools. Furthermore, it is important to analyze the variances regularly and promptly, reporting them to the relevant stakeholders. The focus should be on the significant and actionable variances, prioritizing them according to their impact and urgency. Lastly, involving the process owners and operators in the analysis and improvement process is essential, as well as soliciting their feedback and suggestions.