Tales from the Trenches – 1: Reducing Customer Complaints

Tales from the Trenches is an ongoing series of blogs and videos designed to help manufacturing quality professionals deal with the issues that arise on the plant floor—no matter what industry you are in—with InfinityQS quality management software.

What’s the most vital aspect of your business? Is it product presentation, how it looks on the shelf? Is it repeat customers? Is it profit margin? Or is it perhaps the number of items sold per [enter any time period here]? I would argue that all of these boil down to one thing: making customers happy.
 
Happy customers are repeat customers. They may buy your products because the packaging is just right, or flavor is consistent, or they may be loyal to your brand for any number of other reasons. But the important point here is that they are happy with whatever it is you are producing. And how do you keep customers happy and coming back? Consistent quality!
 
If the quality of your products is consistent and kept to a high standard, then there is really no reason for your customers to look elsewhere. But, if you are plagued by customer complaints, your day-to-day operations can become a headache. Customer complaints show you that your customers are finding flaws in your product. You need to pinpoint the origins of those flaws, stop the customer complaints, and get things back on track.
Reduce Customer Complaints 
InfinityQS quality management solutions can help. Specifically, your use of statistical process control (SPC) with InfinityQS software can help you reduce customer complaints and save money at the same time. And who doesn’t want that?

Working SPC into Your Operations

For the past 18 years I’ve worked as a quality manager in the food and manufacturing industries. In this first blog in our Tales from the Trenches series, I’ll explore how I have used SPC to reduce customer complaints with InfinityQS quality software—specifically, with ProFicient—by identifying nonconforming product and by reducing variation within specification limits.
 
In this article, I’ll 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 vs. out-of-spec data.
 

The Right Tool for the Job

Few things are as frustrating as customer complaints on products that meet specifications. Have you ever experienced that before? I have, and I know it can be mind-numbingly frustrating.
 
Your customers are unsatisfied with the product, you’ve devoted resources to investigating the root cause of the incident, and management is unhappy when the initial investigation yields no clear opportunities for improvement. Nobody wins and no one is happy.
Customer Satisfaction is Key 
Across manufacturing, this is an all-too-common story repeated by frustrated quality assurance professionals. Wouldn’t it be great if there were 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' ProFicient SPC software to help minimize customer complaints. Let’s dive in.
 

In-Spec is Sometimes Not Good Enough

An experience that stands out in my mind has to do with the use of a processing aid used to improve process consistency. Let’s look at an example to illustrate my point—a company that makes popcorn products.
 
Multi-Head WeighersIn 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. I know what you're thinking: the image on the right is not popcorn, but those are filling hoppers (close enough for our purposes). 
 
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 InfinityQS’ 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, we 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.
 

Beyond Charting

It was not until I looked at control chart data that I found a commonality between the 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.
x-bar Chart 
Even though the product was in spec, the customer was not happy with it. It turns out what they had was a classic example of the Taguchi Loss Function.
 

A Few Quality Concepts

This seems like a good time to 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.
 

Quality Heavyweights

Philip CrosbyPhillip Crosby introduced the idea that specification limits are what really matter—Quality is Conformance to Requirements.
 
Crosby’s focus on specification limits can be viewed through a sports lens:
 
In American football, a field goal counts 3 points if it is between the uprights, and 0 points if it is outside the uprights. 
Conformance to Requirements 
Crosby’s Conformance to Requirements philosophy is often referred to as the “Goalpost Theory” for that reason. It is a binary version of quality assurance.
 
Genichi TaguchiGenichi 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 below, displays the increase in cost of quality the further a process deviates from target.
Taguchi Loss Function
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.
 

Beyond Out-of-Spec

So, how did I use these concepts and SPC software to reduce customer complaints with in-spec product? Time to dive deeper.
 
My approach was to go beyond simply addressing out-of-spec product, to also utilize the right SPC rules, alarms, and notifications—to drive processes back toward the target before a spec-limit violation occurred.
 
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.
 

Striving for Customer Satisfaction

Using ProFicient, let’s look at an 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. 
Alarm Rule Assignments
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. 
Events
ProFicient has many ways to communicate to your team, and the options to utilize one (or more) of them are easy to set up. Many companies utilize the Email alarm notification functionality. 
 
The next step is to set up the email alerts to send to the right people. From the Options menu, select Email and configure email alerts for the Part/Process/Test combinations you are monitoring.
Email Configuration 
ProFicient is highly configurable and can get you information when an event occurs—in any format that best suits your team.
 
By using the ideas of Cost of Quality and the Taguchi Loss Function, I was able to reduce my customer complaints. 
 
And by implementing an aggressive suite of SPC rules, I moved our company’s mindset away from “run-in-spec” toward “run-to-target.” This resulted in fewer complaints, but it also had some other benefits.
 

Results are What Matter

As a result of my work with ProFicient, our company had less rework because we were staying further away from our spec limits—so when those inevitable process upsets occurred, they no longer pushed us out-of-spec.
 
A benefit we didn’t expect, though, was financial. To stop running at the high end of the specification, we turned down the application pumps for the butter-flavored oil, our processing aid. Eventually, we even upgraded the pumps to units with better consistency and control. In the end, this had tremendous cost savings.
 
The return on investment the company experienced on the pumps took 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.
 
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.
 
Thanks for joining me for this first Tales from the Trenches blog. Please come back for more tales.
 
For the purposes of this blog, we did not go into details regarding the software. To see step-by-step details of the ProFicient software in action, please check out the Tales from the Trenches video series here.
 

Feel free to check out the other blogs in this series:  
Take advantage of the technology at your fingertips today: contact one of our account managers (1.800.772.7978 or via our website) for more information.
 
Ian Farrell
By Ian Farrell
Lead Consultant, Key Performance Quality Consulting, LLC
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