Ian Farrel Series

Reducing Customer Complaints

Part 1 of 5


Videos in Ian Farrel Series

Episode 1 - Reducing Customer Complaints
Watch Time: 9:00
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Episode 2 - Assignable Cause & Corrective Action – Good Data In, Good Data Out
Watch Time: 10:56
Episode 3 - Reasonable Limits & Data Entry Errors
Watch Time: 11:29
Episode 4 - Overfill & Product Giveaway
Watch Time: 11:20
Episode 5 - 5S Your SPC Projects
Watch Time: 13:40

Video Transcript:

Quality Management: Reducing Customer Complaints - Episode 1

Welcome to InfinityQS’ “Tales from the Trenches.”  In this video series we present real-life quality professionals discussing how they solved important quality control and process problems at their manufacturing facilities. These quality professionals get into the details and show how they leveraged InfinityQS software to solve the problem, including how they identified the root cause. Happy customers are vital to any business.

In today’s episode, quality control manager Ian Farrell will discuss how he used InfinityQS software to reduce customer complaints and save money at the same time. We hope you enjoy the video.

Hello, I’m Ian Farrell, and for the last 18 years I have worked as a quality manager in the food and manufacturing industries.

In this “Tales from the Trenches” episode, I will show you how I have used SPC tools to reduce customer complaints, not just by identifying nonconforming product, but by reducing variation within specification limits.

We all understand how to reduce customer complaints by identifying nonconforming product, but I want to show you how I was able to reduce them further by using SPC to reduce variation within specification limits.

I will introduce and contrast two quality assurance concepts, the Taguchi Loss Function and Crosby’s goalpost theory to show how customer satisfaction is driven by more than just in-spec versus out-of-spec data.

Lastly, using examples mirroring my experiences, I will show you how I used InfinityQS SPC software as a tool to improve customer satisfaction.

To do this, I’ll introduce and contrast two quality assurance concepts, the Taguchi Loss Function and Crosby’s goalpost theory.

Few things are as frustrating as customer complaints on products that meet specifications. Customers are unsatisfied with the product, resources are devoted to investigating the root cause of the incident, and management is unhappy with an investigation that yields no clear opportunities for improvement. 
Nobody wins.

Across manufacturing, this is an all-too-common story repeated by frustrated quality assurance professionals.Wouldn’t it be great if there was a way to not only understand what was happening, but to prevent it from happening in the first place?  Well, I found a way of using InfinityQS SPC software to help minimize customer complaints.

I know first-hand how frustrating it can be to have customer complaints on in-spec product. I want to take a couple of minutes and present examples that demonstrates the problems I’ve faced and how I used SPC tools in operations management to tackle those issues.

In the 18 years I’ve been a quality professional, I’ve learned first-hand how frustrating it can be to have customer complaints on in-spec product.

One experience that stands out in my mind has to do with the use of a processing aid used to improve process consistency.

Let me use an example, like popcorn, to illustrate my point.

In making popcorn a butter-flavored oil is used to help keep the popcorn from sticking to the sides of the filling hoppers and only minimally adds to the flavor and texture of the final product.

As with most processes, the application of the oil was controlled by testing oil content against an established target with upper and lower specification limits. This data was recorded in our ProFicient software but was primarily reviewed as it related to product costs, not as it related to product quality.

It would have never occurred to me that it could be driving customer complaints. From time to time, I would get customer complaints for product texture and I could not find the root cause. Every sample I evaluated was in-spec and passed sensory evaluation.

It was not until I looked at the control chart data that I found a commonality between my repeated customer complaints: They were always in zones A and B of the x-bar chart, near the specification limits of the butter flavored oil. Even though the product was in-spec, the customer was not happy with it. It turns out what I had was a classic example of the Taguchi Loss Function.

Let us take a moment and go over a few quality concepts.

Cost of Quality is the idea that products with poor quality are more expensive to produce. While the basic cost per unit may be low, when you factor in scrap, rework, returns, and lost sales, the cost of a low-quality product quickly eclipses the cost of a well-produced item.

Phillip Crosby introduced the idea that specification limits are what really matters – Quality is Conformance to Requirements.

Crosby’s focus on specification limits can be viewed through a sports lens.  A field goal counts 3 points if it is between the uprights, and 0 points if it is outside the uprights.  Crosby’s Conformance to Requirements philosophy is often referred to as the Goalpost Theory for that reason.
Crosby's Goal Post Theory Illustration

It is a binary version of quality assurance.

Genichi Taguchi, considered Japan’s Father of Quality Engineering, had a different approach to Cost of Quality. For Taguchi, deviation from target was the driver of the cost of quality for a product. The farther from target, even within specification limits, the higher the cost of quality for the product.

The Taguchi Loss Function shown here, displays the increased cost of quality the further a process deviates from target.
Taguchi Loss Function Graph
Customers, especially retail consumers and end-users, are not likely to understand if a product is in spec or out of spec. They will recognize variation in repetitive purchases, however, and will move to other brands that exhibit consistency over those that exhibit too much variation.

Now let’s see how I used these concepts and SPC software to reduce customer complaints with in-spec product. My approach was not to just address out-of-spec product, but by utilizing the right SPC process improvement rules, alarms, and notifications, to drive processes back toward the target before a spec limit violation occurs.

This proactive centering of processes goes beyond the Goal Post theory and leverages Taguchi’s principles of the relationship between variation and quality to improve customer satisfaction, lower cost of quality, and even reduce costs in a host of other ways.

Using ProFicient, let’s see a quick example of how to enable the features that support Taguchi’s approach to customer satisfaction.

From the alarm rule assignments screen, you can select the rules that will help you drive your process to target.  Remember, every product produced closer to target is one that is more likely to be enjoyed by your customer.

After you’ve selected the rules that best suit your process, head over to the Special Preferences/Events screen to make sure you’re set to email, print to printer, write to event server or whatever method you use to alert the team of an event.

ProFicient has many ways to communicate outside of itself, and the options to utilize one (or more) of them are easy to set up.

Many companies utilize the E-mail alarm notification functionality of ProFicient.  If your company is using it, the next step is to set up the email alerts to send to the right people. From the Options menu, select E-mail and configure email alerts for the Part/Process/Test combinations you are monitoring.

ProFicient is highly configurable and can get you information when it happens in whatever format suits your team best.

By using the ideas of Cost of Quality and the Taguchi Loss Function, I was able to reduce my customer complaints. By implementing an aggressive suite of SPC process improvement rules, I converted our mindset away from “run in spec” and toward “run to target”.

This resulted in fewer complaints, but it also had some other benefits:We had less rework because we were staying further away from our spec limits so when those inevitable process upsets occurred, they did not push us out of spec anymore.The biggest hidden benefit, though, was purely financial.  To stop running at the high end of the specification, we turned down the application pumps for our processing aid.  Eventually we even upgraded the pumps to units with better consistency and control.
In the end this had tremendous cost savings.  In fact, the ROI on the pumps alone was less than a year.  Add to that the reduction in usage of the processing aid, and what started as a mission to reduce customer complaints had positive impacts across the organization.

Let me tell you, not only was there tremendous satisfaction in a solution that improved both customer experiences and company profits, but it helped reinforce the quality department’s reputation as an advocate for both customer satisfaction AND profitability.

We hope this episode of “Tales from the Trenches” has motivated you to tackle customer complaint issues using InfinityQS software at your company.

InfinityQS is always there to help. We have application engineers ready to assist you in getting the most value out of your InfinityQS implementation. Reach out to your sales representative for information and pricing.

Thank you for watching and check back soon for our next episode of “Tales from the Trenches.”

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