I’m Jim Brown, President of independent research firm Tech-Clarity, and I have a question. We publish buyer’s guides to help companies understand what they should look for in a solution to improve business outcomes. One of our most recent guides, Seven Keys to Improving Service with the IoT, focuses on helping manufacturers and service companies get the most out of machine monitoring. The guide, our second revision, offers seven considerations for companies to consider when they target service transformation.As I publish this guide, I wonder if writing about “how” to improve service and the system capabilities it requires is enough. Are most companies aware of “why” they should be doing it in the first place, and how it can positively impact their business? If so, why isn’t everyone doing it successfully now that barriers to implementing machine monitoring through the industrial IoT (IIoT) have dropped?
The new buyer’s guide offers requirements checklists that go beyond software functionality to cover factors important to implementation, adoption, partner choice, and more. To summarize the guide, it makes the following seven suggestions:
For each of these areas, it offers practical steps people can take and factors they should consider in their software selection. As you can see, we’ve added some of the “why” at the beginning. Based on the progress we’ve seen in the industry, and in particular some of the false starts we’ve observed, we added “set your business targets” as a first step before connecting equipment. Even though our guides are focused on how to execute a strategy, we believe it’s important to share “why” to adopt new processes and technology, and not just “how.”
For example, do service companies want to increase their own service revenue? Or do they want to focus on improving outcomes for their customers like increasing manufacturing efficiency or decreasing equipment downtime? That makes a difference, right? They need to know their goals to determine what data they need to collect, for example production levels, downtime data, or runtime parameters, and what insights and understanding they want from the data. But is that overkill for a buyer’s guide, assuming that companies have already set a strategy?
If companies know what they want to accomplish, what’s holding them up from reaching their goals? And what’s taking them so long? I believe at this time that the business value is proven. There are a lot of great examples to learn from, and many pioneers to follow. Further, there is a lot of help available between independent consultants and software companies’ professional services staffs. Improving service with machine monitoring is no longer on the bleeding edge, as it was a decade ago when I was learning about M2M (machine to machine) initiatives to monitor machine performance.
Companies still have old equipment and connectivity issues, may struggle to implement meaningful analytics, or have other challenges. But for the most part, it’s gotten easier (and faster) to get going. Nobody should have to start from scratch anymore. They don’t have to build a platform themselves or assemble solutions from a toolkit. Leading solution providers now share knowledge and best practices through education, adoption services, and solution templates. These provide starting points on what to do in addition to how to do it. But they also leave room so companies can tailor them to their unique needs. This makes implementation easier and faster from a business perspective to catch up with the advances that have already made it easier from a technical perspective.
So, what do companies need to get the value available from IoT machine monitoring? The barriers have dropped, but we find companies don’t know where to start. They need to find a practical problem that’s worth solving. Based on this, my belief is that the first step, setting goals, is possibly more important than the detailed requirements on how to support the process. From my observation, business issues have been more of a barrier to success than technology.
What’s your experience? What do companies need to know in order to get away from the status quo of low value proof of concept (POC) projects and failed initiatives?
Jim Brown is the President of Digital Innovation Research for independent research firm Tech-Clarity. He covers the digital enterprise, PLM, PDM, IoT, portfolio management, digital manufacturing, and other solutions for manufacturers.
Jim founded Tech-Clarity in 2002 and has over 30 years of industry experience in the manufacturing and software industries. He began his career in manufacturing engineering and software systems at GE before pursuing management consulting at Andersen Consulting (Accenture). He subsequently served as a strategy, marketing, and product development executive for software companies specializing in ERP, PLM, Supply Chain, and related manufacturing solutions. He has a BS in Mechanical Engineering from the University of Maryland, College Park.
Jim is actively researching the impact of digital transformation and technology convergence in manufacturing. His research analyzes the business value available from new initiatives and technologies including cloud computing, advanced analytics, product innovation platforms, service transformation, augmented reality, the digital twin, and the digital thread.
Mr. Brown is an experienced author and speaker and enjoys engaging with people with a passion to improve business performance through digital enterprise strategies and supporting software technology. When he’s not focused on technology, he is a scuba instructor and plays in an old guy ice hockey league.