Statistics Article

Eric Weisbrod’s picture

By: Eric Weisbrod

In recent months, we’ve learned that manufacturing during a global health crisis puts organizations under immense pressure to maintain operational efficiency while upholding product quality and employee safety.

Initially, organizations focused simply on taking the steps required to survive. However, as organizations around the globe have pivoted to overcome those initial challenges, manufacturers are taking the opportunity to explore how they will not just survive but become more resilient—even thrive—going forward.

Recent operational challenges have shined a light on existing process weaknesses and technology limitations. Manufacturers are taking their cue and proactively identifying opportunities to optimize processes, empower workers, and make operations across the organization more effective.

Enact, InfinityQS’ cloud-native quality intelligence platform, offers plant leadership a variety of ways to make their operations more effective. Here are six Enact benefits that can help your organization make critical shifts that are necessary for the future of manufacturing.

Dirk Dusharme @ Quality Digest’s picture

By: Dirk Dusharme @ Quality Digest

It’s been 40 years since “If Japan Can, Why Can’t We?”, W. Edwards Deming, and total quality management. More than 33 years have passed since the release of the first iteration of ISO 9001 (remember checklists?). For four decades the importance of building quality into processes rather than trying to “inspect in” quality has been pounded into our little quality management brains. Proactive good, reactive bad. We get it.

Or do we?

Despite “risk management” or “risk-based thinking” becoming part of everyday quality parlance, quality on the ground is still largely reactionary. Tactical rather than strategic. In short, we still seem to be just “doing” quality rather than mastering it, i.e., we are using traditional quality processes and tools at only the shop-floor level rather than using next-generation enterprisewide quality tools throughout our entire organization.

Taran March @ Quality Digest’s picture

By: Taran March @ Quality Digest

In the intro to this series we noted that, too often, quality tools and the data we glean from them are used only to solve immediate, mostly shop-floor problems. These gold nuggets of opportunity aren’t used in an equally valuable way to address a company’s strategic goals.

Here we’ll consider how to master quality at the shop-floor, tactical level. More than just byproducts of the production process, quality data are the vital signs that determine if individual processes—and by extension, the entire production system—are healthy. That information can in turn help drive business strategy.

It starts on the shop floor

For most companies, learning to use data to their best advantage entails drifting between visionary potential and problematic reality—the strategic vs. tactical tension. As part of this inevitable tug-of-war, data are rounded up, variability is tamped down, and quality anxiously measured.

Ryan E. Day’s picture

By: Ryan E. Day

If you're involved in business you know: Strategy matters. Your strategies guide you to reach your objectives. Behind every successful business are purposeful strategies. Then again, as Alvin Toffler said, “The absence of strategy is fine if you don’t care where you’re going.”

We’re talking specifically about data-driven strategies like using “improving operational efficiency” to support a goal of increasing your profit margin. Or “improving product standardization” to increase international market share. The question is, how do you support your data-driven strategies? Where do your data come from?

Many leaders don’t realize they are probably sitting on a gold mine of data just waiting to be transformed into actionable information to support their strategies. I’m talking about the quality control data that are collected every day on the shop floor.

Multiple Authors
By: Betsy Mason, Knowable Magazine


This story was originally published by Knowable Magazine.

Imagine a science textbook without images. No charts, no graphs, no illustrations or diagrams with arrows and labels. The science would be a lot harder to understand.

That's because humans are visual creatures by nature. People absorb information in graphic form that would elude them in words. Images are effective for all kinds of storytelling, especially when the story is complicated, as it so often is with science. Scientific visuals can be essential for analyzing data, communicating experimental results and even for making surprising discoveries.

Visualizations can reveal patterns, trends and connections in data that are difficult or impossible to find any other way, says Bang Wong, creative director of MIT's Broad Institute. "Plotting the data allows us to see the underlying structure of the data that you wouldn't otherwise see if you're looking at a table."

And yet few scientists take the same amount of care with visuals as they do with generating data or writing about it. The graphs and diagrams that accompany most scientific publications tend to be the last things researchers do, says data visualization scientist Seán O'Donoghue. "Visualization is seen as really just kind of an icing on the cake."

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Paul Laughlin’s picture

By: Paul Laughlin

This month I read Andy Kirk’s absorbing Data Visualisation 2, or to give it its proper title Data Visualisation 2nd Edition. The subtitle for this book is A Handbook for Data-Driven Design, which hints at how this is packed with advice.

Although the paperback version is a comfortable weight, it is astonishing how much it contains. This really is a guide for practitioners and one they will want to refer back to.

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Ryan Ayers’s picture

By: Ryan Ayers

Data are valuable assets, so much so that they are the world’s most valuable resource. That makes understanding the different types of data—and the role of a data scientist—more important than ever. In the business world, more companies are trying to understand big numbers and what they can do with them. Expertise in data is in high demand. Determining the right data and measurement scales enables companies to organize, identify, analyze, and ultimately use data to inform strategies that will allow them to make a genuine impact.

Data at the highest level: qualitative and quantitative

What are data? In short, they are a collection of measurements or observations, divided into two different types: qualitative and quantitative.

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Davis Balestracci’s picture

By: Davis Balestracci

“With data from an epidemic there is no question of whether a change has occurred. Change is everywhere. The question is whether we are getting better or worse. So while the process behavior chart may be the Swiss army knife of statistical techniques, there are times when we need to leave the knife in our pocket, plot the data, and then listen to them as they tell their story.”
Dr. Donald J. Wheeler

I agree with Dr. Wheeler’s comment about process control charts. Yet, I’m seeing far too many of them being inappropriately used as naïve attempts to interpret the mountains of questionable Covid-19 data being produced. I’ve done a few charts myself out of curiosity but none that I feel are worth sharing. Dr. Wheeler’s two recent, excellent Quality Digest articles have been the sanest things written—with nary a control chart in sight.

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Jeffrey Phillips’s picture

By: Jeffrey Phillips

Throughout human history we’ve constantly sought out tools and capital to make us more productive. From the formation of basic tools to assist in farming to real cultivation and shaping of the land for greater yields, humankind learned to grow food. Further research into genetics, fertilizers, and pesticides enabled us to rapidly scale food production. From early sweatshops to almost fully automated factories, we’ve learned how to scale manufacturing and get far more productivity from fewer workers and more machinery and automation.

In this manner, we’ve learned to improve the deployment of human labor, land, tools, machinery, and other capital to improve our quality of life. Now, we must fully engage the asset that we have the most of that is producing the least for us: data. It’s time to put our data to work.

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Donald J. Wheeler’s picture

By: Donald J. Wheeler

The daily Covid-19 pandemic values tell us how things have changed from yesterday, and give us the current totals, but they are difficult to understand simply because they are only a small piece of the puzzle. This article will present a global perspective on the pandemic and show where the United States stands in relation to the rest of the world at the end of the third week in June.

Here we will consider 27 countries that are home to 5 billion people (67% of the world's population). According to the European CDC database, which is the source for all of the data reported here, these 27 countries had more than 75 percent of the world’s confirmed Covid-19 cases and 86 percent of the Covid deaths as of June 20, 2020. So they should provide a reasonable perspective on the worldwide pandemic. Figure 1 lists these countries by region and gives the relevant Covid-19 counts and rates as of June 20, 2020.

Figure 1: Countries used for global summary

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