‘In God we trust; all others bring data.” “Follow the data.” “Let the data talk.” Nice clichés, but there’s one problem... data can’t talk. In fact, data don’t say a darn thing. Data are bits of raw information. If you want to reduce product variation, improve your manufacturing processes, and increase profits, you need to interrogate and analyze your data.

It is the data analysis that provides actionable insights, and the success of statistical process control (SPC) depends on data analytics. SPC is the cornerstone of quality control and quality assurance in manufacturing processes.

SPC and Six Sigma are nearly synonymous with improving quality consistency and reducing process variation and waste. Naturally, these methods begin with data monitoring and collection—it’s the analysis stage where things can get dicey. But that’s also where data can turn into increased profits.

Listen to Doug C. Fair of InfinityQS, as he reveals the way companies are using data analysis tools to take advantage of the data they are already collecting with their quality control programs.

Just as there is more than one way to collect and store data, there is more than one way to interrogate and analyze your data, and more than one way to visualize and interpret your data. Data are seeds that hold great potential, and proper data analysis is the key to unlocking that potential.

So, you have to ask yourself, “Are the SPC methods and tools we’re using yielding actionable insights that drive improvement and profitability?”