Paradigms are those powerful frameworks that shape how we think about the world. They are often so deeply embedded in our psyches that we don’t even consider that there might be a different way to frame our understanding.

But paradigms can and do shift. And sometimes, those shifts are essential to foster progress. Think about a well-known example:

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  • Ptolemy: The Earth is the center of the universe.
  • Copernicus: I think the sun might actually be the center of the universe.
  • Galileo: Hey, my telescope shows that Copernicus is right.
  • (Church: Galileo, you are going to jail.)

That last line, of course, is a reminder that paradigm shifts are not easy, and they may come with a cost. But what is the greater cost of not changing our thinking?

The paradigms that have been built up around manufacturing quality are sagging under the weight of modern technology and applied statistics. And a fresh look at how we manage quality in manufacturing can reveal opportunities for tremendous progress.

Manufacturing Quality Paradigms

The word paradigm has been overused in modern discourse. But in this context, we're talking about paradigms that may be holding manufacturers back. Today, what is possible in modern manufacturing quality is vastly different from what was possible in the quality world of the past. We need to identify those manufacturing quality paradigms that are really no longer true, or even applicable, and create a new frame of understanding.

SaaS is a Paradigm Breaker

Here’s the way we used to think: If I’m going to make improvements in my manufacturing processes, then those improvements will be localized, right? That is, I can make an improvement at a production line, or for a particular product code, at a single plant—and those changes take place only at the plant level.

Software-as-a-Service (SaaS) has shattered that paradigm. Modern statistical process control (SPC) software delivered in a SaaS model provides manufacturers with the capability to have data collection and visibility across the entire enterprise. SaaS enables our quality improvement experts at the corporate level (from anywhere around the globe) to sort, slice, and dice data any way they want across plants, across departments, across the enterprise, across regions. When you can see all the data in one view, there are no limitations.

Quality Paradigm Broken. Now What?

So, when we have embraced the power of modern, cloud-based SPC quality systems to enable unprecedented visibility and information, what can we do next? This paradigm shift opens up a range of opportunities to use data differently: aggregation, prioritization, and best practices.

Data Aggregation

If you can collect data from across your enterprise, and aggregate that data in one centralized, unified data repository, you can compare information about operations in plants, processes, products, even individual lines. You now have the ability to see where your operations are working the best, and where the biggest problems lie. Not only at the plant level, but across the entire company.

And if you know where the biggest problems are hiding, or where the most waste occurs, or where the most defects are happening, then you can prioritize your quality improvement efforts.

Prioritization

In this context, what does prioritizing quality improvement mean? It means you can look across your entire enterprise and say, “Over there, in region three, that is where the most waste is occurring.” Then, you can put your quality improvement team to work discovering the root cause of that waste and making improvements that will most positively affect the bottom line—in the shortest period of time.

Let’s say your organization is interested in reducing overall costs. Your Six Sigma team can be deployed to any and all areas of your company that are veering off course and enact changes with just that cost focus in mind. Or, perhaps your organization is more interested in the consistency of the products you ship to reduce defects and recalls. Again, your Six Sigma team can take that aggregated data, see across the enterprise, and pinpoint where products are being produced inconsistently.

They may discover that your products aren’t out of spec—but where is the data inconsistent? Where does it vary from line to line? Shift to shift? Your quality pros become proactive agents of change for your organization, not just firefighters dealing with the constant barrage of daily fixes.

Likewise, your organization’s upper management—C-level execs, VPs, directors—may want to take a strategic look at improving market share, or shipping costs, or the organization’s overall bottom line. Whatever the issue, with a global view of your enterprise, upper management can prioritize where they want to deploy the quality professionals.

Best Practices in Quality Manufacturing: Share that Knowledge

Think about that opportunity. We couldn’t do that just a short while ago. Every company with a quality solution had to deal with localized plant-specific software. There were no cloud-based solutions. When a company wanted to make improvements, it had to do so at the plant level.

Well, not anymore. A single cloud-based deployment of a quality solution can touch plants all around the globe. And you can take things a step further. Now that you’ve deployed the quality team to attack a certain problem and they’ve returned with lessons learned, you can leverage that knowledge to create best practices that you can share with the entire company.

If you have best practices across your entire company, then the chances are good that product inconsistencies will diminish—perhaps even become a thing of the past.

That might be the biggest paradigm shift of all.

Time to Think Big

You’ve improved a portion of your business that sorely needed it. That information is vital to your organization’s growth. You now pass the best practices you’ve developed to every other section of your company and the enterprise-wide improvements impact your bottom line.

So, you can see how paradigms are shattered, how organizational improvement is within your grasp, right? You have taken aggregated data, turned it into actionable information, from which you prioritized the improvements you want to make. You can plan exactly the improvements you need to be successful and highly competitive—not just in the short run, but also in the mid-term and in the long run.

Get on a Schedule, Transform Your Organization

The most successful manufacturing organizations today are already using this approach, scheduling regular data evaluations. Some organizations have monthly sessions, some quarterly or weekly. Whatever it takes. They make it a priority, and it shows.

It seems like a big commitment, but when you think about how this sort of activity can directly affect your organization’s bottom line…well, maybe it’s not such a big commitment after all. It’s a way to change your organization for the better. Is it time for your organization’s paradigm shift?

To learn more about how you can re-imagine quality and transform your business, visit the InfinityQS website.