As business evolves, so does our ability to uncover new sources of revenue, which keeps life interesting. One of the most significant contributors to business evolution in the last few decades is technology. I believe that relatively speaking, we’re still in what could be considered to be the Wild West era of technology’s impact on business. The Internet of Things (IoT) is an example of a scenario most of us couldn’t have dreamed up even ten years ago, and it’s causing great excitement at the prospects it promises — particularly within the manufacturing industry. There’s a good reason for this excitement: A recent McKinsey Global Institute report stated that the IoT could unleash up to $6.2 trillion in new global economic value annually by 2025 and that 80-100 percent of all manufacturers will be using IoT applications by then. On the other hand, right now only 10 percent of manufacturers are leveraging the IoT to improve their processes. Clearly, there is work to be done, and more importantly, there are significant opportunities for companies who use this technology to their advantage.
Before I dive into how you can derive revenue from real-time, sensor-driven data, I’d like to discuss not only how I define the IoT, but also how I think it’ll impact our business. For our purposes, the IoT is a system where physical items contain sensors that are wirelessly connected to the Internet, allowing them to connect, share, gather and transmit data. It can be applied to any number of use cases, from a home thermostat to a medical device to manufacturing equipment. When it’s applied to manufacturing, the IoT will make production increasingly connected until everything becomes linked. This means that the entire supply chain will become more dependent on coordination across every level, from logistics to suppliers and everything in between. It also impacts the customer-facing processes that can now be utilized to fight product commoditization, create deeper ties with customers and realize new sources of revenue.
What I specifically mean by this is illustrated by what GE is doing with their Jenbacher Gas Turbines, which have sensors that provide performance data back to GE and the operator. This data is used to understand maintenance requirements and real-time performance of the engines. GE also has the ability to provide service contracts to their customers so that they do not have to worry about maintaining these highly sophisticated pieces of machinery. Interestingly enough, by providing the machinery and the service, GE has formed a strong bond with their customers, and the company is viewed not just as an equipment provider but as a valued partner that provides equipment, services and insights.
GE has used this data to their advantage by setting up a way in which it can predict, in real-time, when maintenance will be needed. They no longer set up their contracts solely on a corrective or preventative basis. The data afforded them by the IoT has informed their next best step. This is brought to life by a concept and technology known as IBO or Intelligent Business Operations, which turns business insights into intelligence-driven operations. Using an IBO platform, a manufacturer blends real-time data with historical measures into a single view, provides context as the basis for intelligent action and automates processes to take intelligent “best next steps.” No matter your industry, you can’t manage what you can’t measure. The heart and soul of IBO is found in the IoT, and it is coming to a manufacturer near you.
It makes sense, then, that for complex organizations with large networks that are inter-related and reliant on the constant transfer of data — like manufacturers — the IoT is a godsend. It lends itself beautifully to Predictive Maintenance, which allows manufacturers to monitor equipment performance that leverages real-time sensor data. It gives them an understanding of historical data and current and predicted equipment availability as an overall measure of the equipment’s effectiveness. It allows the prediction of maintenance failures and provides alerts about maintenance when needed, as opposed to a suggested schedule. Using the IoT, Predictive Field Maintenance increases output quality by understanding when equipment needs repair prior to quality being degraded, and it understands repair part availability and replenishment requirements before the part is needed. Finally, it understands and manages field-based repair assets and technicians to customer requirements.
I know what you’re thinking: What if your company doesn’t provide sophisticated products like the GE Jenbacher Gas Turbines? It’s fairly easy for them to differentiate with a service contract because their product is fairly complex. What if your company provides electric motors, reducers, servo motors or even light bulbs? This is where differentiation is even more valuable. By providing products that some claim to be “commoditized,” it is imperative to differentiate and become more valuable to the customer. One way to go about this is to predict failure and intervene before failure occurs. Your customer will love you because it avoids corrective actions and is far less costly than a preventative maintenance program — because repairs are being made and components are being replaced only when needed. Best of all, repairs can be scheduled into set periods of downtime.
The next logical hurdle is the appetite, or lack thereof, to have your own dedicated services arm. Setting up this type of an operation is costly and complicated. But it doesn’t have to be, and it can be outsourced, which requires the ability to engage with a large quantity of partners, part and service suppliers, on a large scale. Again, this can be accomplished leveraging the IoT and the concepts of IBO. As an example, service partners can provide real-time position and service updates using GPS on technicians’ trucks or mobile devices. This data is continuously analyzed in real time to provide the equipment manufacturer with complete visibility, an understanding of the exceptions that are occurring and the ability to take control when they want to. It is this final portion that is pivotal in making this vision a reality, and it depends upon the ability to understand how partners, customers and the enterprise will react when an exception arises or an opportunity presents itself. This becomes even more critical when services become intertwined with performance expectations, commonly referred to as Service Level Agreements (SLAs) or as my neighbor the lawyer affectionately terms it, “Contractual Obligation Non-Performance Remediation.” Acting in concert with partners and customers in a consistent manner — every time — ensures a positive outcome.
We at Software AG call this “structured collaboration,” a model where partners and suppliers work together via information-sharing. This brings them all a clear understanding of enterprise and partner needs and requirements, as well as collaboration on event resolutions. By participating in structured collaboration, manufacturers see many benefits, including — and especially — complete visibility, so that data, exceptions and mitigating actions are all shared at varying levels, depending on the partner’s strategic impact. In turn, this contributes to consistency and shared certainty, which give manufacturers a granular understanding about how suppliers and partners react to exceptions and allows them to act with certainty. Finally, structured collaboration reduces mitigation costs, so that actions are limited to the scope in which they’re needed. To think, all this is made possible by a tiny sensor embedded within your equipment.
It bears repeating: The impact of the IoT will be significant. ERPs and MES’ — the manufacturing industry’s go-to solution for many years — cannot provide the real-time data to drive analysis and incisive, informed action. Real-time data is critical, and it positions the IoT as a significant enabler of gleaning vivid insight into real-time production performance and some really interesting new revenue opportunities. Think of the possibilities! Then add them in your comments below.
Sean Riley is director of Industry Solutions-Manufacturing at Software AG.