Pushing Past Pilot Paralysis to Launch and Scale IIOT Use Cases

With billions of industrial IoT (IIOT) devices in place, generating massive volumes of data from “the edge,” the potential for proof of concept success for use cases in the factory can be paralyzing. While the value of this digital revolution, aka Industry 4.0, is clear, realizing the full promise has been slow. Research and real-life experience from Accenture shows that many manufacturers get stuck early on or can’t get beyond proof-of-concept pilots to scale. Pushing past the unforeseen roadblocks takes a tried-and-true combination of process, technology, and people, along with a future-forward vision.

Focus on the End Goal and Think Big

When problem-solving with technology, the default is often to kick off with assessing technical feasibility first. But whether something can be done matters little if you don’t first define what you want to accomplish. To take advantage of the IIOT, start by defining the business case. What are the pain points you want to address, and what quantitative results do you expect?

Think big here. Your proof of concept should be an application that will create broad business value which can scale even further. Involve executive leadership, and find out what’s most important to them. What use case will have the most significant impact? How do they measure success? Getting buy-in means gaining backing for your pilot and what follows, while metrics are the catalyst to improvement and expansion.

Finding the Solution

With the why and what established, you can now move on to the how. But remember that both information technology (IT) and operational technology (OT) data are needed to deliver that enterprise-wide, scalable solution that will deliver the results expected.  When it comes to this data, an edge-to-cloud solution must be capable of supporting the following: 

  •   Variety: Data comes from multiple, often disparate, sources. Can the solution process the different data sets?
  •   Volume: Thousands of sensors and machines across your ecosystem will feed the data stream. Can the solution handle the quantity?
  •   Velocity: Real-time data is the ultimate advantage of the edge. Is your solution fast enough to capture and process all the information?

Without a proper data ingestion mechanism from the edge to the cloud, the pilot won’t come to fruition.

Don’t Forget the People

Human capital is just as important as technology as you mature in your Industry 4.0 journey. A smart operation includes people, but the industry is facing a huge shortfall. A study by The Manufacturing Institute and Deloitte found that 2.4 million manufacturing jobs could go unfilled over the next 10 years, at a loss of $2.5 trillion worth of GDP. 

The three main causes are lack of awareness, skills or interest. The National Association of Manufacturing says, “Modern manufacturing careers are increasingly high-tech, high-skill, and high-pay. The possibilities in manufacturing will become even more exciting as Manufacturing 4.0 technology continues to revolutionize the industry. Tomorrow’s manufacturing jobs will increasingly rely upon irreplaceable human skills — things like creativity, critical thinking, design, innovation, engineering and finance — and, by the way, many of these careers don’t require a four-year degree or the debt that can come with it.”

Diversification and investment in reskilling or upskilling your workforce should be a critical part of your IIOT strategy.

Pushing Past Pilots

A connected, intelligent factory is known to be safer and more efficient, cost-effective, and profitable. A fully-instrumented factory provides sustained differentiation from non-automated factories, as the edge produces the most unfiltered, unmodified data that, in the end, delivers the highest resolution insights possible. In its truest form, this data is ultimately the heartbeat of Industry 4.0 operations. Unlocking its value is the key to delivering use cases that will transform your operations.

For a more technical dive into where and how to start, read our previous blog: Factory Edge to Cloud Analytics- Three Fundamental Steps to Success.

David LeGrand
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