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Six Sigma Projects

Blog posts and articles about using statistics and applying data analysis in Six Sigma projects.

It's been called a "demographic watershed".  In the next 15 years alone, the worldwide population of individuals aged 65 and older is projected to increase more than 60%, from 617 million to about 1 billion.1 Increasingly, countries are asking themselves: How can we ensure a high quality of care for our growing aging population while keeping our healthcare costs under control? The answer? More... Continue Reading
Earlier this month, PLOS.org published an article titled "Ten Simple Rules for Effective Statistical Practice." The 10 rules are good reading for anyone who draws conclusions and makes decisions based on data, whether you're trying to extend the boundaries of scientific knowledge or make good decisions for your business.  Carnegie Mellon University's Robert E. Kass and several co-authors devised... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

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By looking at the data we have about 500 cardiac patients, we've learned that easy access to the hospital and good transportation are key factors influencing participation in a rehabilitation program. Past data shows that each month, about 15 of the patients discharged after cardiac surgery do not have a car. Providing transportation to the hospital might make these patients more likely to join... Continue Reading
In part 2 of this series, we used graphs and tables to see how individual factors affected rates of patient participation in a cardiac rehabilitation program. This initial look at the data indicated that ease of access to the hospital was a very important contributor to patient participation. Given this revelation, a bus or shuttle service for people who do not have cars might be a good way to... Continue Reading
My previous post covered the initial phases of a project to attract and retain more patients in a cardiac rehabilitation program, as described in a 2011 Quality Engineering article. A Pareto chart of the reasons enrolled patients left the program indicated that the hospital could do little to encourage participants to attend a greater number of sessions, so the team focused on increasing initial... Continue Reading
Over the past year I've been able to work with and learn from practitioners and experts who are using data analysis and Six Sigma to improve the quality of healthcare, both in terms of operational efficiency and better patient outcomes. I've been struck by how frequently a very basic analysis can lead to remarkable improvements, but some insights cannot be attained without conducting more... Continue Reading
by Laerte de Araujo Lima, guest blogger The NBA's 2015-16 season will be one for the history books. Not only was it the last season of Kobe Bryan, who scored 60 points in his final game, but the Golden State Warriors set a new wins record, beating the previous record set by 1995-96 Chicago Bulls. The Warriors seem likely to take this season's NBA title, in large part thanks to the performance of... Continue Reading
While the roots of Lean Six Sigma and other quality improvement methodologies are in manufacturing, it’s interesting to see how other organizational functions and industries apply LSS tools successfully. Quality improvement certainly has moved far beyond the walls of manufacturing plants! For example, I recently had the opportunity to talk to Drew Mohler, a Lean Six Sigma black belt and senior... Continue Reading
‘Statistics’ is a rising star. Everywhere I turn, people are talking about data and the value of being able to analyze and act on it. As someone who’s been writing about that for years, I say it’s about time. Statistics is like a talented actress whose decades of appearing off Broadway have finally paid off. For years, her work has been enriching our lives without us knowing it. Statistics helps... Continue Reading
According to this article published on Food Tank, over 22 million pounds of food is wasted on college campuses each year. Now that’s a lot of food waste! Students all over the country are noticing excessive food waste at their schools and are starting programs to bring awareness and improve the problem. Naturally, many of these programs have roots in Lean Six Sigma. In one example, a group of... Continue Reading
By Matthew Barsalou, guest blogger A problem must be understood before it can be properly addressed. A thorough understanding of the problem is critical when performing a root cause analysis (RCA) and an RCA is necessary if an organization wants to implement corrective actions that truly address the root cause of the problem. An RCA may also be necessary for process improvement projects; it is... Continue Reading
This week is National Healthcare Quality Week, started by the National Association for Healthcare Quality to increase awareness of healthcare quality programs and to highlight the work of healthcare quality professionals and their influence on improved patient care outcomes. In honor of the celebration, I wanted to point you to a few case studies featuring Minitab customers in the healthcare field... Continue Reading
In 2007, the Crayola crayon company encountered a problem. Labels were coming off of their crayons. Up to that point, Crayola had done little to implement data-driven methodology into the process of manufacturing their crayons. But that was about to change. An elementary data analysis showed that the adhesive didn’t consistently set properly when the labels were dry. Misting crayons as they went... Continue Reading
Before I joined Minitab, I worked for many years in Penn State's College of Agricultural Sciences as a writer and editor. I frequently wrote about food science and particularly food safety, as I regularly needed to report on the research being conducted by Penn State's food safety experts, and also edited course materials and bulletins for professionals and consumers about ensuring they had safe... Continue Reading
In previous posts, I discussed the results of a recycling project done by Six Sigma students at Rose-Hulman Institute of Technology last spring. (If you’re playing catch up, you can read Part I and Part II.) The students did an awesome job reducing the amount of recycling that was thrown into the normal trash cans across all of the institution’s academic buildings. At the end of the spring... Continue Reading
This week I'm at the American Society for Quality's World Conference on Quality and Improvement in Nashville, TN. The ASQ conference is a great opportunity to see how quality professionals are tackling problems in every industry, from beverage distribution to banking services.  Given my statistical bent, I like to see how companies apply tools like ANOVA, regression, and especially... Continue Reading
by Lion "Ari" Ondiappan Arivazhagan, guest blogger.   Predicting project completion times is one of the major challenges project managers face. Project schedule overruns are quite common due to the high uncertainty in estimating the amount of time activities require, a lack of historical data about project completion, organizational culture, inadequate skills, the complex and elaborative nature of... Continue Reading
Suppose that you have designed a brand new product with many improved features that well help create a much better customer experience. Now you must ensure that it is manufactured according to the best quality and reliability standards, so that it gets the excellent long-term reputation it deserves from potential customers. You need to move quickly and seamlessly from Research and Development into... Continue Reading
by Lion "Ari" Ondiappan Arivazhagan, guest blogger.  An alarming number of borewell accidents, especially involving little children, have occurred across India in the recent past. This is the second of a series of articles on Borewell accidents in India. In the first installment of the series, I used the G-chart in Minitab Statistical Software to predict the probabilities of innocent children... Continue Reading
In part 1 of this post, I covered how Six Sigma students at Rose-Hulman Institute of Technology cleaned up and prepared project data for a regression analysis. Now we're ready to start our analysis. We’ll detail the steps in that process and what we can learn from our results. What Factors Are Important? We collected data about 11 factors we believe could be significant: Whether the date of... Continue Reading