Using nonparametric analysis to visually manage durations in service processes

My main objective is to encourage greater use of statistical techniques in the service sector and present new ways to implement them.

In a previous blog, I presented an approach you can use  to identify process steps that may be improved in the service sector (quartile analysis). In this post I'll show how nonparametric distribution analysis may be implemented in the service sector to analyze durations until a task is completed.

Knowing how much time you need to complete a task may be very useful when assessing process efficiency, and is an important factor in many businesses.

Consider a...

Gauging Gage Part 1: Is 10 Parts Enough?

"You take 10 parts and have 3 operators measure each 2 times."

This standard approach to a Gage R&R experiment is so common, so accepted, so ubiquitous that few people ever question whether it is effective.  Obviously one could look at whether 3 is an adequate number of operators or 2 an adequate number of replicates, but in this first of a series of posts about "Gauging Gage," I want to look at 10.  Just 10 parts.  How accurately can you assess your measurement system with 10 parts?

Assessing a Measurement System with 10 Parts

I'm going to use a simple scenario as an example.  I'm going to...

Lessons in Quality During a Long and Strange Journey Home

I didn’t expect that our family trip to Florida would end with me driving a plane load of passengers nearly 200 miles to their homes, but it did.

Yes, it was a long and strange journey home. A journey that started in the tropical warmth of southern Florida and ended the next morning in central Pennsylvania, which felt like the arctic wastelands thanks to the dreaded polar vortex.

During this journey, I didn’t just experience temperature extremes, but also extremely different levels in the quality of customer care. Working at Minitab, I'm very aware of the quality of service because quality...

Setting the Stage: Accounting for Process Changes in a Control Chart

When looking at a control chart, it’s important to know that the data we are looking at is accurate. Let’s face it, if the control limits we are looking at don’t really reflect what’s actually happening in our process, what does it matter if our points fall within the limits, or a little bit outside?

Let’s take a trip down to the widget factory, where widgets are being produced in all shapes and sizes. We’re going to take a look at one particular widget, and the time it takes for that particular widget to be produced (in minutes).

In a Minitab Statistical Software datasheet, we have two months...

Applying Six Sigma to a Small Operation, Part 2

In my previous post, I shared a case study of how a small bicycle-chain manufacturing company in India used the DMAIC approach to Six Sigma to reverse declining productivity.

After completing the Define, Measure, and Analysis phases, the team had identified the important factors in the bushing creation process. Armed with this knowledge, they were now ready to make some improvements.

The Improve Phase

In the Improve phase, the team applied a statistical method called Design of Experiments (DOE) to optimize the important factors they'd identified in the initial phases.

Most of us learn in school...

Applying Six Sigma to a Small Operation

Using data analysis and statistics to improve business quality has a long history. But it often seems like most of that history involves huge operations. After all, Six Sigma originated with Motorola, and became adopted by thousands of other businesses after it was adopted by a little-known outfit called General Electric.

There are many case studies and examples of how big companies used Six Sigma methods to save millions of dollars, slash expenses, and improve quality...but when they read about the big dogs getting those kind of results, a lot of folks hear a little voice in their heads...

Creating a Shatterproof Process: Students Use Six Sigma to Improve Window Manufacturing

I had the opportunity to speak with a great group of students from the New Jersey Governor’s School of Engineering and Technology—a summer program for high-achieving high school students. Students in the program complete a set of challenging courses while working in small groups on real-world research and design projects that relate to the field of engineering. Governor’s School students are mentored by professional engineers as well as Rutgers University honors students and professors, and they often work with companies and organizations to solve real engineering problems.

The team of students...

Fix Problems in Regression Analysis with Partial Least Squares

Face it, you love regression analysis as much as I do. Regression is one of the most satisfying analyses in Minitab: get some predictors that should have a relationship to a response, go through a model selection process, interpret fit statistics like adjusted R2 and predicted R2, and make predictions. Yes, regression really is quite wonderful.

Except when it’s not. Dark, seedy corners of the data world exist, lying in wait to make regression confusing or impossible. Good old ordinary least squares regression, to be specific.

For instance, sometimes you have a lot of detail in your data, but not...

The Value Stream Map: It's Been Around Longer than You Think

In looking for the answer to an unrelated quality improvement question the other day, I ran across a blog post that answers a question I'd had for a while: what's the origin of the value stream map? 

A value stream map (VSM) is a key tool in many quality improvement projects, especially those using Lean. The value stream is the collection of all of the activities, both value-added and non-value added, that generate a product or service that meets customer needs. The VSM shows how both materials andinformation flow as a product or service moves through the process value stream, helping teams...

Avoiding a Lean Six Sigma Project Failure, part 4

In my first post in this series, I mentioned that we reached out to our customers who are practitioners in the field of quality improvement to better understand how they complete projects, what tools they use, and the challenges and roadblocks they come across in achieving success with quality initiatives. One area quality leaders said they were struggling with was the training aspect of their programs—actually getting their belts and/or project team members up to speed with adequate training to complete projects independently.

Insufficient Training

They told us projects were failing because of...

Understanding ANOVA by Looking at Your Household Budget

by Arun Kumar, guest blogger

One of the most commonly used statistical methods is ANOVA, short for “Analysis of Variance.” Whether you’re analysing data for Six-Sigma styled quality improvement projects, or perhaps just taking your first statistics course, a good understanding of how this technique works is important.

A lot of concepts are involved in any analysis using ANOVA and its subsequent interpretation. You’re going to have to grapple with terms such as Sources of Variation, Sum of Squares, Mean Squares, Degrees of Freedom, and F-ratio—and you’ll need to understand what statistical...

Process Capability Statistics: Cp and Cpk, Working Together

Capability statistics are wonderful things. These statistics tell you how well your process is meeting the specifications that you have. But there are so many capability statistics that it's worth taking some time to understand how they’re useful together.

Two capability statistics that are hard to keep straight are Cp and Cpk. Their names are different by only a single letter. A single letter that, by the way, doesn’t really explain anything about how these two statistics are different.

Definition of Cp

The equation for Cp is often written ET / NT. ET stands for Engineering Tolerance, which is...

The Three Coolest Things You Didn't Know about Histograms in Minitab

Not too long ago, I observed that one number is rarely adequate to describe data. Means and medians can disagree, and it’s important to know whether different groups of data have similar spreads. A great tool for displaying a more complete representation of the data is the histogram. Histograms are an easy way to summarize a lot of statistics. If you’re not convinced, take a minute to explore some. For example, Katherine Roswell can give you an example of how to use a histogram to identify the best opportunity for improvement in hospital patient readmissions. Histograms are great.

And the...

How Data Analysis Can Help Us Predict This Year's Champions League

by Laerte de Araujo Lima, guest blogger

A few weeks ago, my football friends and I were talking about the football in the UEFA Champions league (UEFA CL), and what we could expect for the 2013-14 season.

Some of us believe that the quality of the football played in the UEFA CL has improved in the last few years, as evidenced by more goals per match, more teams with strategies based in the attack and, finally, more show games. Others disagree, arguing that the teams were pursued defensive strategies with consequently fewer goals per match, more faults per game, and less effective use of game time...

Use Analysis of Means to Classify Baseball Parks

When I first got interested in looking at baseball park factors, I only wanted to know which parks benefited hitters and which benefited pitchers. Once I got started, I got interested in the difference between ESPN's published formula and its results and whether there were obvious reasons for the variation in park factors from year-to-year.

But today I’m returning to the original question: which parks are hitters’ parks, and which are pitchers’ parks?

We already know that the mean and median are inadequate by themselves. For example, consider AT&T Park, where the mean suggests a pitchers’...

Avoiding a Lean Six Sigma Project Failure, part 3

In previous posts, I’ve outlined some reasons why a Lean Six Sigma project might have been deemed a failure. We’ve gathered many of these reasons from surveying and talking with our customers.

I’d like to present a few more reasons why projects might fail, and then share some “words of wisdom” from Minitab trainers on how you can avoid these project failures.

Forcing Projects into DMAIC

Certain quality improvement projects were never meant to be Six Sigma projects that fit neatly into the DMAIC (Define – Measure – Analyze – Improve – Control) methodology. Examples include:

1. Selecting a vendor...

Kickoffs into the End Zone: To Return, or Not to Return?

In the world of Six Sigma, we’re always looking to improve our process. Whether it’s increasing the strength of building materials or improving the way calls are processed in a call center, it’s always a good idea to use a data-driven analysis to determine the best solution to your process.

The same is true for the NFL. Two years ago, the NFL decided to move kickoffs up from the 30 yard line to the 35. This has resulted in more kicks traveling into the end zone. So NFL coaches have a decision to make on their kick return process:

  • Should I have my player take a knee whenever he catches the ball...

Avoiding a Lean Six Sigma Project Failure, part 2

In a previous post, I discussed how to avoid a Lean Six Sigma project failure, specifically if the reason behind the failure is that the project solution never gets implemented.

In this post, let's discuss a few other project roadblocks that our customers cited when we asked them about the challenges they come across in completing projects. I’ll also go into detail about suggestions our industry-seasoned trainers at Minitab offer to avoid these failures.

Is the project scope too large?

One common reason quality improvement projects get started on the wrong foot is that their scope is too large.


Avoiding a Lean Six Sigma Project Failure

Failure. Just saying the word makes me cringe. And if you’re human, you’ve probably had at least a couple failures in both your work and home life (that you've hopefully been able to overcome).

But when it comes to Lean Six Sigma projects, there’s really nothing worse than having your entire project fail. Sometimes these projects can last months, involve a large project team, and cost companies a lot of money to carry out, so it can be very upsetting for all involved to know that the project failed (for whatever reason).

At Minitab, we’re always talking to our customers and practitioners in the...

Warning: Failing to Display a Pareto Chart May be Hazardous to Your Health

Defects can cause a lot of pain to your customer.

They can also cause a lot of pain inside your body. The picture at right shows my broken right clavicle. Ouch!

You might think of it as the defective output from my bicycling process, which needs improvement.

Sitting around all summer cinched up in a foam orthopedic brace hasn’t exactly been wild and wacky 50s-style fun at the beach.

But the injury has had its perks (a box of mouth-watering dark chocolate ganaches from kind Minitab coworkers, for example!)

It’s also provided me with a rare commodity in the year 2013: Plenty of time to think.