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Rob Harrison

Quality Insider

Why Quality Management Leaders Need an IoT Strategy Now

Get out in front before it’s too late

Published: Thursday, January 22, 2015 - 13:48

A recent survey conducted by LNS Research revealed that 43 percent of manufacturing professionals don’t understand the Internet of Things (IoT). Although this may be cause for some concern, it’s not entirely surprising. There is something important lurking behind the fact that although most have heard of this ubiquitous term—it’s hard to have avoided it by now—a significant number of quality executives persist in misunderstanding its import.

In this article we intend to take the discussion to the next logical stage, beyond the smart manufacturing plant and over and above servitization (service as an added value to a company's products)—both of which are very important topics and warrant attention. But we also need to examine the practical challenge that manufacturers face based on the assumption that more information is a good thing. With that challenge, executives are becoming hard-pressed to answer the following questions:
• What’s in store for the quality management closed loop when the information bombardment begins?
• How do we prepare for the vast pipeline of potentially actionable data returning to the organization?

When the DRIP becomes a flood

From laggards to leaders, many organizations fail to truly exploit all the data they have available today. Yet galloping towards us is a promised explosion from big data and the potential offered by the insight revolution. What quality management has to gain from IoT is the most formidable closed-feedback loop leap to date.

The reality of connected, smart products will deliver concrete, objective, and potentially continuous-use performance and reliability data. There is realistic potential that the overhead of complaints could shrink to a minimal and occasional blip, therefore eliminating in many cases the huge overhead of a traditional investigation for a field failure, or, if the predictions are accurate, preventing them before they occur.

The challenge, though, will be that organizations already have more information than they know what to do with. Most are facing significant challenges already with regard to being data rich and intelligence poor (“DRIP”s so to speak). The most adept are those organizations with an architecture conducive to managing pre-architected closed-loop quality processes across the value chain—the very chain that will be the recipient of this feedback boost.

Some organizations have already deployed and embedded enterprise quality management software (EQMS), either by expanding on ERP, PLM, MOM, or deploying a dedicated quality-hub platform. These organizations may still have some work to do, but they are significantly better placed than those without any such extant systems. Many have utilized the correct metrics to measure quality and/or are on the right path to do so, but the next wave is something entirely different than the health and performance of the quality management system (QMS). The next wave is actionable data direct from the product in the field.

The new intelligence paradigm

Every organization with awareness and understanding of IoT wants to know how to capture, process, and derive meaningful intelligence from this stream. This is reasonable as there will be significant volume looping back. However, this is not big data per se, because it is not unstructured—quite the opposite, in fact. The incoming stream is by design and is therefore structured originally by original equipment manufacturers. The real challenge is to take the stream and drive accurate and meaningful outcomes in the form of improvement.

The answer is to approach the IoT with the mindset that it will supercharge the quality management system by tightening the closed-loop approach so that engineering is more closely connected with the rest of the value chain. Improvement action, or corrective and preventive action (CAPA) as we know it today, becomes the vehicle for designing for quality based on the new channel of intelligence. Agility will be an explicit requirement of this new dawn and building a strategy or laying the foundation for the advent is critical to success.

The opportunities in IoT are accompanied by some level of threat too. There are some privacy and security issues with regard to smart, connected products and the data relating to performance and use—analogous to location services and other “personal” information freely shared with application providers by the 1.75 billion smartphone owners globally. Feedback can be used (and therefore misused) for derived as well as literal intelligence. It will be important to articulate the value and terms of use of the data (in the context of product monitoring and improvement). Specifically, using data for improvement and demonstrating openly that such data is captured and managed in a harmonized, traceable, secure, and accountably driven EQMS is a reasonable proposition.

Assess your current state

IoT will increase the amount of data coming from Internet-enabled manufacturing processes, manufacturing workers, manufacturing assets, components, finished products, and customers. If all of this data is to be used intelligently (i.e., proactively instead of reactively) it has to be collected by a single system with harmonized processes, and the insights have to be driven back upstream for improved product and process design. This cannot be established when a company has multiple CAPA systems (i.e., separate systems for engineering, manufacturing, and the field) and when engineering is not connected to the results of the CAPA process.

Being prepared includes assessment of the current capability of the quality management system. Does the infrastructure already creak under the weight of manual processes? Does the traditional interface between departments exist as a silo? If so, this is likely to cause a buckling scenario as new demands become our new reality. Connected and smart products will demand that our quality management processes mature and are better connected. Key to this is tracking the actionable content derived from the ubiquitous product cloud. Get ready or it’s possible you may be left behind.

Interested in learning more about the IoT and how it will affect quality operations? Read LNS Research’s new free report, “The IoT Revolution and the Connected Value Chain.


About The Author

Rob Harrison’s picture

Rob Harrison

Rob Harrison is a research analyst at LNS Research covering enterprise quality management software, environment, health and safety, and sustainability. He is responsible for quantitative and qualitative research projects to provide industrial executives with tools and knowledge to improve overall business performance. He has a deep understanding of the business value of investing in software solutions. Harrison’s experience includes product management, global product marketing, software engineering, and environment, health and safety management system implementation. Harrison has a bachelor’s degree in marine environmental science and a master’s degree in interfacing and software application.