To earn the return on investment that a modern, cloud-based SPC software service can provide, organizations need to rethink some outdated ideas about quality.

“Quality professionals need to embrace the sophisticated, modern technologies that can allow us to easily summarize quality data across the enterprise. The result is greater information at a higher level, allowing far greater improvements in quality than were ever possible with older tech,” says Doug Fair, chief operating officer at InfinityQS. “Reviewing tons of data on a big spreadsheet is ‘old-school.’ It just doesn’t work. Spreadsheets weren’t designed to cope with lots of diverse quality data, and neither were control charts. Today’s modern quality software technologies are designed that way. And they do so with advanced, yet simple, analysis tools. Modern SPC software should allow data to be easily rolled-up across production lines, product codes, and plants so that you can view the big picture of quality across the company.”

Fair says that one of the limiting factors is that quality activities are too focused on troubleshooting and problem solving. Quality improvement activities should instead focus on proactive, company-wide quality information that can enable manufacturers to make transformative operational gains through the use of SPC software.

“Quality professionals are great at problem-solving,” he says. “But that doesn’t speak to strategic intent. For too long we have focused on firefighting, local improvements, and localized reductions in cost. Imagine if we were able to do something on a much, much larger scale. We must be able to look at quality data across the enterprise, rather than focus on fixing something that happened yesterday. If you want big gains in quality and cost, organizations need to step back and think about quality as a strategic initiative that can transform a company’s performance.”

To realize that goal, Fair walked Quality through five steps organizations can take to earn the full ROI from SPC software.

1. Step back, look at the big picture and generate quality information about the entire enterprise.

“Looking at that big picture of quality means we’ve got to aggregate data, summarize, and review a ton of data all at once,” Fair says. “You can do that if you’ve got the right tools. Our software enables us to mathematically and statistically account for differences in product code specifications, means, and standard deviations so that fair comparisons can be made across product codes and plants — even if the specs and underlying scales are vastly different. These aggregations can be made very simply, and we even use ‘stop light’ coloring to highlight exactly what quality professionals and mangers need to look at. We can do that across plants, lines, products shifts — any conglomeration or summarization you want to do, you can do it.”

2. Perform detailed, exploratory and comparative analysis of that aggregated data.

If a manufacturer has 10 plants, SPC software should allow quality professionals to look across all locations, summarize the data, and present the information for further exploration.

“We need to ask ourselves, ‘OK, which production lines have the highest or lowest parts-per-million fallout?’” Fair explains. “That will help us prioritize our quality improvement efforts specific to machinery. The same thing can be done with product-specific data, regional data, and even allow overall plant performance to be compared against one another. That is, there are a variety of SPC tools that allow for simple, yet powerful, exploratory and comparative analysis. Companies need to know which product families, machine tools, and plants have the best or worst quality performance, so that action can be taken to make the greatest improvements in the least amount of time.

“These comparative analyses can help pinpoint where organizations need to apply their quality efforts. Which regions run the same products better or worse than other regions? Where are yields highest or lowest among all products, all production lines, and all plants? What defects were present, or not present, based on production lines, region, plant, or shift? We can answer all of these questions by aggregating data and performing some simple exploratory and comparative analysis.”

3. Create a strategic list of quality-related issues that would have the greatest positive impact on the company.

“Getting back to strategy — if we put all that quality data together across the enterprise, then we’re able to highlight where the real problems are, and where the greatest opportunities for improvement exist. A list of improvement opportunities can be easily generated from aggregated data. Once the list is created, actions can be prioritized and the issues can then be attacked in a strategic manner.”

4. Direct Six Sigma teams or other quality professionals to address opportunities for the greatest cost reduction and quality improvement.

During visits to manufacturing plants, Fair says he often finds Six Sigma teams asking, “What do we work on now?” It’s the result of company leadership who do not have access to big picture quality data. Undirected Six Sigma teams do find things to work on, but their talents could be better used if pointed towards the kind of transformative projects that SPC data aggregation can identify.

“The Six Sigma folks I have worked with are dedicated, motivated, and are brilliant at what they do. My experience, though, is that they simply don’t have access to a strategic list of quality priorities that can be generated through high-level data aggregation. As a result, many Six Sigma teams are left to define their own priorities and their own projects. To best leverage their valuable knowledge and limited time, Six Sigma teams would benefit from strong leadership that can say ‘Hey, we know what needs to be worked on first, second, third, and so forth. Here is our prioritized list—based upon evidence from our aggregate data.’”

5. Perform these analyses regularly, on a schedule.

The most successful companies Fair works with schedule data analysis sessions weekly, monthly, or quarterly. The common denominator is regularity.

“By doing that, you set an expectation that it’s important to regularly review data so that opportunities to improve quality and reduce costs are uncovered. Scheduled meetings help busy quality professionals and managers to step back from the daily grind and look at the big picture of quality.’

“Every company has different preferences for how they do this. One company I worked with had a senior management team meeting every morning at 6 a.m. They reviewed aggregated data from the previous day, helping to prioritize short-term improvement actions. They also had a scheduled monthly meeting where they summarized the entire month’s quality data, allowing them to define mid- and long-term improvement projects.”

By taking the time to meet regularly, organizations can find hidden opportunities for massive cost savings and quality improvements that can maximize the value of their SPC software systems.