Manufacturing organizations have many ways to gather data—pen and paper, spreadsheets, and quality systems software. But why do companies gather quality data?
If your manufacturing business is like most, you gather data to make sure nothing’s going wrong. That’s critical, certainly, but if you only focus on what went wrong, you’re missing the overwhelming majority of the story. Quality is more than simply checking to make sure that the final product meets specs. When it’s done right, quality can differentiate your company and make your product stand out. Quality can help build and protect your brand.
Data Has a Bigger Story to Tell
Most companies gather and analyze quality data to answer a single question: Are the products I’m making bad or good? Mostly, companies use quality data to find problems and fix them.
Quality professionals are brilliant when it comes to identifying issues. And Quality folks are superb problem-solvers. But, what happens to the data they don’t focus on? That is, what happens to the majority of data that indicates products are actually good
and within specification limits?
Typically, that data is simply forgotten. It is discarded or left to languish in databases or filing cabinets. That’s a shame, because taken together, the data you collect—especially the data that is within specs—has a story to tell. And those stories can help you make huge improvements in quality. But if that data is ignored, the biggest quality stories never get told.
My experience has been that the greatest golden nuggets of information are found in the overwhelmingly high percentage of data values that fall within specifications.
This is what sets forward-looking companies apart from their competitors: They step back once a week, once a month, or once a quarter and look at the big picture. They aggregate and summarize all
of their quality data so that they can gain operational insight into what’s happening across their enterprise and on all of their manufacturing shop floors.
Quality = Process Quality + Product Quality
Here’s an example from a company I worked with. This client, a packaging manufacturer, was going to shut down one of its plants because its quality was the worst of all 20+ operations. The closure would have put hundreds of people out of work in a small community that couldn’t afford such a hit.
We installed our quality software, and went with the age-old wisdom that if you want to improve something, you have to measure it. That’s exactly what we did in this plant, and within three months, the plant had all but eliminated defects in its finished products.
Miraculous? Not really. By gathering data and looking at the big picture, plant management discovered high-level issues—as well as lots of improvement information—which allowed them to concentrate their efforts and improve both process and product quality. The result? The plant went from “worst to first” in quality across the entire corporation. They became the model for how to dramatically improve business performance through the use of quality intelligence. It was nothing short of a transformation.
Quality Insights Deliver Real ROI
Consider another real-life example of what quality information and insights can do for a manufacturer. Managers at a large distillery were noticing volumetric fill variances in a variety of different products. Nothing was out of spec, but a lot of bottles seemed to be filled a bit more than required. And while customers might appreciate a bit more in their bottle than advertised, even a little bit of overfill is an unnecessary cost for any beverage company. In order to help reduce overfill, they asked for InfinityQS’s help.
As a test, management decided to run a pilot of our quality software on just one production line. Data was collected not only on fill volumes, but also on bottle breakage, sanitation, temperatures, and flow rates. We set up quality checks to run at specific intervals, with the software reminding operators when to collect data. Plus, operators were automatically alerted when issues occurred. They dealt with out of spec problems, statistical alarms and focused their attention on fill volumes using real time analyses.
The result? Over several weeks, the fill volume data identified manufacturing inconsistencies and variations in nozzle performance. After changes were implemented, the company estimated that volumetric savings exceeded $800,000 per year – and that’s for just one production line.
Listen to the Story Your Data Tells
Quality isn’t just about fixing issues and responding to problems. Rather, it’s about a never-ending search for information that can help reduce defects and costs while enhancing customer loyalty. When you truly listen to the stories your data are telling you – even data that is not out of specification – you can strengthen your brand, improve business performance, gain market share and create legions of devoted customers. And saving some money in the process doesn’t necessarily hurt.