To Improve ROI: Shift your manufacturing quality paradigm (Part 1)

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 paradigm

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.

Priority

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.

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.

Productivity and Quality Office