Accurate Quality Data2016 will be the year that data truly breaks into quality control management and processes. The C-suite has not only had their fill of personal views and lack of insight into inspection procedures and quality planning, but have finally drunk the Koolaid on what big data can do for the bottom line. According to Dr. Suresh Gettala, a director at ASQ India, because of the availability of big data,  “most executives will rely on a fact-based approach for decision making.” It now falls on us to collectively gather that data, and put it to good use.

Quality control has long been an issue that’s needed tackling, but systems and processes just haven’t made it to the top of the pile of priorities. With new cloud-based supply chain management software, mobile technologies, and easier processes, Quality Control Analysts, Directors and Consultants are actively seeking opportunities to convert manual quality reporting processes to digital data that can then be leveraged to gain insight, improve quality and deliver to the C-suite the data, information and insights they need to make key business decisions.

This is particularly critical data for companies that are outsourcing product manufacturing to countries like China. According to the International Business Times, in 2013, China made more personal computers, mobiles phones, shoes, and pork than any other country. And many companies just don’t have insight into how those vendors are maintaining quality standards.

On the other side of the pond, manufacturers are looking for ways to compete—and offering transparency and insight into quality procedures can be the differentiator that they’re looking for. According to, China’s heavy industry and commodities are in a recession—slowing down to its weakest growth in a decade. With the economy tight, manufacturers will be looking for competitive advantages and working to maintain the business they already have—and part of this will be creating manufacturing efficiencies by converting manual processes to digital ones.

Why? Manual processes can negatively impact cost and/or quality—rather than improving it. Consider the fact that you may have tens of thousands of products and variations, along with any number of quality criteria to gauge. With manual data collection and entry processes, you might find that:

  • Manual collection of data (paper-based documentation) can lead to inconsistent collection and mis-categorization
  • Manual review of, and updates to, data result in errors
  • Manual storing and analysis of data (via spreadsheets) can be cumbersome, and doesn’t naturally lead itself to quick identification and correction of remedial quality control issues

Given this, it’s important for both product designers, creators and vendors to identify which processes can be digitized, and in what manner the data is stored and accessed to provide Analysts and Consultants with the best data in the most usable format.

Why Would You Need Accurate and Reliable Quality Control Data?

Even now, quality control is a concern for manufacturers outsourcing to vendors in countries like China—and the reputational damage has been done—both to brands AND to manufacturers in China. For proof of this you only need to look to a scandal still dragging on a US manufacturer—Lumber Liquidators. An exposé run by 60 minutes reported, this largest retailer of hardwood floors in the US…

“was selling China-made laminate flooring that contained high levels of formaldehyde, a known carcinogen. Some samples tested contained as much as 13 times the formaldehyde emissions limit set by California.”

That was 2 years ago—yet today the company is still struggling with the impact on its brand. While, according to CBS news, Lumber Liquidators will discontinue selling product from China (negatively impacting the Chinese manufacturer—and China’s manufacturing industry), customers are still confused about whether flooring is safe or not—which can negatively impact the retailer’s brand.

And it’s not just Lumber Liquidators. Manufacturers all over North America are struggling with this. A recent survey of 100 executives notes that approximately half of “their organizations had faced an issue of noncompliance resulting from a supplier.”

To solve this—it’s key that quality and standards be maintained—and that quality control processes and data be digitized so that anomalies can be quickly identified and corrected.

What Quality Control Data Should Be Digitized?

According to a report by Mckinsey, 80% of survey respondents believe that digital operations is a critical driver of competitiveness. So the understanding is there, but the actual execution may be lacking. Large enterprise-level organizations employ millions of dollars of enterprise-level applications like SAP—only to find that they are too complicated, too slow, or too costly to leverage appropriately to manage simple quality control for vendors.

So what is an organization that recognizes the need for rapid adjustment to its overseas quality control data to do? There are a handful of areas that can quickly be addressed and digitized with the goal of improving quality, increasing compliance, and lowering cost.

Inspection Procedures – Typically these are manual, paper-based processes that rely on loose guidelines and lack a solid structure for recording and transmitting results. Additionally, inspections can take weeks or months to be input into some form of reporting for a vendor—with the understanding that different vendors use different methodologies and offline systems to capture data, resulting in fragmented results and useless data across vendors.

By digitizing inspection procedures enterprises and mid-size businesses can gather and validate data immediately, allowing you to solve quality problems earlier and faster.

Quality Plans – When preparing plans for quality systems, often we rely on hard copy, spreadsheets, and even faxed documents in an effort to understand the previous year’s orders and flow. Developing an understanding of where product quality issues lie can be a Herculean task at best.

When looking at data to be digitized, inspection forms and converting subjective processes (like color authentication) are critical considerations. Digitizing these will remove the headaches, time and general inconsistencies surrounding the development of your quality plan, and help you provide the data needed to generate and monitor it across the different tiers of your supply chain.

Business Rules – Gartner recently published its Top 25 List providing insight into the behaviors of successful companies. One area of competitiveness to note is “Emerging Digital Business Models”—where organizations leverage digital capabilities to “improve broader value chain performance”.

According to the source,, the digitization of supply chain processes like inspections, quality monitoring and cloud-based supply chain data management allow businesses to predict when there will be a variance in the “current plan of record”.

It’s no question that the businesses that adopt data digitization are going to lead the market in 2016, so how is your business gaining insight into its quality control data?

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