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How do you summarize Lean Six Sigma data?

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Lean Six Sigma is a methodology that combines two approaches to improve quality and efficiency in processes: lean, which focuses on eliminating waste, and Six Sigma, which focuses on reducing variation and defects. To apply Lean Six Sigma, you need to collect and analyze data from your process, and then use it to identify and implement improvements. But how do you summarize Lean Six Sigma data in a clear and concise way? Here are some tips to help you.

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1 Use descriptive statistics

Descriptive statistics are numerical measures that summarize the main features of a data set, such as the mean, median, mode, range, standard deviation, and frequency. They can help you understand the central tendency, variability, and distribution of your data, and compare different groups or categories. You can use tools like Excel, Minitab, or R to calculate descriptive statistics and display them in tables or charts.

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Daniel Christiansen

Lean Operations and Process Improvement Expert | MBA | ASQ Lean Six Sigma Black Belt
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While familiar and straightforward to calculate, using descriptive statistics to summarize data to a lay audience may result in confusion or misunderstanding about the results. Whenever possible, the whole distribution should be presented to allow the audience to see the data without additional interpretation. This can be in the form of histograms or box plots, though other presentations should be considered if appropriate. If single value statistics are required, measures such as mean and standard deviation should be avoided due to the ease with which they're misinterpreted. For most use cases mode, median, or a 95/99% value are more useful. Ensure the relevance of the measure to understanding the process in question.

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Mahmoud Adel

Senior Operations Supervisor @ Teleperformance | Business Metrics, Process Improvement, MBA, LSSGB
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Overall, your article offers practical tips for effectively summarizing Lean Six Sigma data. It serves as a helpful guide for individuals looking to communicate data insights concisely and accurately. Well done!

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2 Use graphical methods

Graphical methods are visual ways of presenting and exploring data, such as histograms, box plots, scatter plots, Pareto charts, and control charts. They can help you identify patterns, trends, outliers, and relationships in your data, and communicate your findings to others. You can use tools like Excel, Minitab, or R to create graphical methods and customize them according to your needs.

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Efe K O.

Business Process Innovation @ Lucid Motors | Business Architecture | Digital Transformation | Continuous Improvement | Orchestrator | VP Membership - ABPMP
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One important use of a graphical representation of the data points in Lean Six Sigma is the Pareto 80-20 principle. It easily depicts the entire data at a glance showing that nearly 80% of the effects comes from 20% of the causes. With this, we can easily identify the common problems in our processes based on the data available.

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3 Use inferential statistics

Inferential statistics are methods that allow you to draw conclusions or make predictions based on your data, such as hypothesis testing, confidence intervals, correlation, and regression. They can help you test your assumptions, measure the significance and effect of your results, and evaluate the impact of your improvements. You can use tools like Excel, Minitab, or R to perform inferential statistics and interpret them correctly.

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4 Use summary reports

Summary reports are documents that synthesize and communicate your data analysis and recommendations, such as project charters, dashboards, and executive summaries. They can help you organize and highlight the key information, such as the problem statement, the goals, the data sources, the methods, the results, and the actions. You can use tools like Word, PowerPoint, or Google Docs to create summary reports and use clear language, bullet points, and visuals.

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5 Use storytelling techniques

Storytelling techniques are strategies that help you engage and persuade your audience with your data, such as framing, narrative, emotion, and call to action. They can help you connect your data to your purpose, context, and stakeholders, and motivate them to take action. You can use tools like storytelling frameworks, templates, and examples to craft your story and deliver it effectively.

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Kirk B.

Senior Consultant @ EY | Life Sciences | Risk, Quality & Compliance
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Storytelling is critical when it comes to using the statistical tools commonly leveraged in a process improvement project. This is due mainly to the fact that conclusions drawn from the results of a statistical analysis often do not definitively identify the exact root cause of an issue without the ability to fully re-create each variable impacting the state of a system/process at any given time. Rather, they will provide an indication of the potential source(s) of special cause variation or defects. Understanding this concept and developing the ability to tell the story as to why the statistics support the associated conclusions will certainly aid in obtaining agreement from the audience.

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6 Use feedback loops

Feedback loops are processes that help you collect and incorporate feedback from your audience, such as surveys, interviews, reviews, and comments. They can help you evaluate the quality and impact of your data summary, and identify areas for improvement. You can use tools like SurveyMonkey, Google Forms, or Qualtrics to design and conduct feedback loops and analyze the results.

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7 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?

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How do you summarize Lean Six Sigma data?

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1 Use descriptive statistics

2 Use graphical methods

3 Use inferential statistics

4 Use summary reports

5 Use storytelling techniques

6 Use feedback loops

7 Here’s what else to consider

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