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Doing IoT for IoT’s sake? It’s time to rethink your approach
HPE Chief Technology Officer for Manufacturing, Automotive and IoT
When I talk with industrial companies about the Internet of Things (IoT), there is a lot of excitement. Whether it’s automated QA on the factory floor or sensored pumps driving the refinery of the future, it’s hard not to get excited about industrial IoT. At many firms, business leaders may feel compelled to do something with IoT, even if it’s not clear what that something should be.
But launching an industrial IoT project just for the sake of doing IoT is unlikely to lead to tangible benefits. Indeed, there is a real risk of introducing technology that ends up dragging down teams and leading to negative outcomes. Outright failures are a real possibility.
So, how should companies approach IoT? I believe there are several key elements to any digitization initiative:
- There must be a focus on improving products and services, and providing real business value.
- People have to be engaged and believe in the project’s goals.
- IoT is not just about things; it’s also about data and extracting value from that data.
It’s easy to underestimate the importance of this last point. Of course, IoT sensors, applications, and devices generate data which can make industrial operations more efficient, power new types of automation, or provide insights that let managers and operators make more informed decisions. This represents real business value.
But that’s just the beginning. IoT data often has value beyond the task or function it was explicitly created for. That said, imagining how data can be leveraged for other purposes, or even applied outside of the business unit that “owns” it, can be difficult. Sharing data is not only unfamiliar, it’s also frowned upon, thanks to the all-too-common tendency for modern enterprises to operate as a collection of data silos that discourage collaboration.
A new framework for managing data
Fortunately, there’s a framework called closed-loop manufacturing that can help managers see the big picture when it comes to the role of IoT and other types of data across an organization.
For instance, at a car manufacturer, instead of keeping data within the groups that created it (R&D, design & prototyping, production, and aftermarket services), the framework would have data move back down the cycle to give other departments new insights and make better decisions.
This represents a major change. Within the aftermarket group, sales and service departments have direct contact with customers, yet the other groups traditionally only get heavily filtered snapshots of inventory or sales metrics. Consider the potential impact of introducing the closed-loop manufacturing framework:
- If the R&D and design groups can access more detailed types of data relating to preferences and buying trends, designers and engineers will be able to more quickly implement updates and features that better meet the needs of the marketplace.
- If the production group can get better insights into the problems that the aftermarket service teams are dealing with, that can help them more quickly identify and correct issues on the assembly line or with suppliers that contribute to problems or defects.
Practically speaking, this could mean sensors measuring how long it takes paint to dry on a new auto component not only inform nearby operators, but also materials engineers in the R&D department. Or, data coming out of emissions tests at a service center can be used to identify production problems for a certain type of exhaust system.
Thinking big, starting small
When it comes to implementing IoT or applying a dynamic new data management framework, you can’t simply overturn the existing order and insist on implementing big changes across the entire organization. There would be chaos and widespread resistance, not to mention enormous cost outlays.
What I like to tell industrial companies is that while it’s important to think big, tangible progress must be made. That means starting with smaller projects, such as identifying a use case for IoT that delivers real value, and implementing it on the plant floor. Or, taking the first steps to connect some of the silos that had previously been walled off from one another in order to enable new feedback loops. Such projects are not only easier to plan, it’s easier to build buy-in and deliver real value.
Successes may be relatively small at first, but they can give people real credibility within their own organizations … and set the stage for larger projects.
At the upcoming HPE Discover event in Las Vegas from June 19 to 21, there are a slate of demos and information sessions covering various aspects of industrial IoT and digital transformation. Be sure to add them to your event calendar:
- Technical session: AI-powered, big data analytics: From the manufacturing edge-to-core
- Digital transformation panel: Put IoT into action: What five trailblazers learned on their IoT journeys
- Business outcomes panel: Accelerating innovation in the Industrial Internet of Things (IIoT)
- Factory optimization with HPE Edgeline
- Accelerating manufacturing with HPE Edgeline
- Leveraging IoT for real-time condition monitoring with HPE Edgeline