September 18, 2017
Analyzing Quality Data with the Right SPC Tools: Mastering Quality #4
Welcome to the halfway point in the Mastering Quality
series! It seems like you’ve done a lot to this point—and you have. But you’re only part of the way there. It’s not enough to collect the right data, ensure all your quality
checks are done correctly and on time, and prioritize your quality improvement opportunities. You also need to be able to take advantage of those opportunities.
In our last installment, What’s Your Priority? Use SPC to Maximize Your Impact on Quality and Costs
, we looked at how the right statistical process control (SPC) solution can help you prioritize quality initiatives at a high level in order to make the biggest positive business impact. When all your data is stored in a single, centralized repository, your data is easily aggregated, which enables you to see across your entire organization.
Only then can you generate the reports you need to visualize what’s really happening across operations. The example we used in the previous blog was the color-coded “stop light” report, which allows you to identify quality grades for plants, production lines, products, and features. These reports highlight quality priorities, so you are a step closer to the transformative initiatives that can drive big improvements to your bottom line.
To determine how to achieve those improvements, you need to dig deeper into your aggregated data. Get your “detail people”—your data experts—involved and let them do what they do best: analyze data and extract actionable information that can drive efficiency and yield improvements.
Engage the Data Experts with Easy-to-Use SPC Tools
The data experts of whom I speak are your quality professionals, engineers, and Six Sigma teams. They are the miners who extract gold in the form of pertinent information from the big quality picture—the mine. The big quality picture provides very little detailed information that can be acted upon; it’s really for guidance and prioritization about where to focus improvement efforts.
As adept as they are at extracting the details, your information “miners” first need to be directed to where opportunities for improvement lie. The prioritization you just performed—in which you aggregated all of the operations data and identified the “stop light” items—is the map that highlights opportunities for improvement and defines the spots where your analysis experts need to dig.
Dig into Continuous Improvement Priorities
In order for your data experts to perform the necessary analyses, your SPC solution should be equipped with a wide variety of statistical tools
. Those tools are a data miner’s friend. They shouldn’t require a statistician, an IT expert, or a code-writer to create.
If you are the Operations Manager who directs a team to evaluate a ton of data, you better make sure your team is properly equipped. To be successful, they’ve got to have the right tools. That means emphasizing statistical tools that are simple to manipulate and easy to interpret, yet have the capacity to powerfully uncover the valuable, actionable information you seek.
If you expect your data miners to sift through large amounts of data, those statistical tools better be up to the task. That is, the best statistical tools for mining information should easily support the analysis of aggregated data from multiple plants, product codes, production lines, and features—and place that information on one chart
Why one chart? Having critical information instantly displayed in one place makes it easy to consume and understand. Let’s not forget that your analysts may be working with massive amounts of data from disparate sources. Even then, their statistical tools should still
be easy to use.
And your team’s statistical tools need to be sophisticated enough to allow expansive sorting, slicing, and dicing of data while contending with varied numeric scales and vastly different specification limits. That’s not an easy ask. But that capability should be expected of any cloud-based quality system that is deployed across an organization.
Once properly equipped, your data experts can dig up the gold you know is hidden in your data.
Now your analysts should be able to identify process improvements that will enhance quality in a specific area and may also convey across the company.
In this way, your data miners will be able to break down your priorities into information that can be acted upon to help transform performance. Their success means that you will know exactly where the issues lie, and how to implement the most impactful improvements to benefit your operations.
In my next blog, we’ll discuss the next step: reporting and communicating the data experts’ findings to different users within your organization, from the local plant folks (plant managers, quality managers) to the “higher ups” in the board room.
Would you like to see how these techniques can be applied to your organization? Schedule a live demo
, customized to your organization and requirements.