Part 1: Introduction and questionnaire
Let’s begin this series on industrial IoT enablement and practical business transformation with a question. Which statements best describe your digital ambitions? First, you’re exploring industrial IoT and analytics for efficiency gains and cost savings. Therefore, you’re looking for ways to connect machines to on-premises or cloud monitoring and analytics services and dashboards. Second, you’re evolving the organization into a digital industrial enterprise. As such, you’re evaluating ways to harness data from across your enterprise, operations, and supply chain for new opportunities and business models. There are tools and vendors to help achieve either vision. Furthermore, when planned well, both goals start increasing enterprise value in a relatively short period of time.
But now, a word of caution. Bold claims from IoT consultants, eager internal teams, and purveyors of machine learning and artificial intelligence services create challenges for those on the second path. Solutions for this group must provide much more flexibility than many tools designed for the first can provide. Therefore, any product, vendor, or internal development approach must be thoroughly vetted. The differences aren’t always apparent in the initial pilot project. Often, critical limitations aren’t revealed until after investing in the wrong process or platform.
This series will help product owners, influencers, and key stakeholders improve their abilities for analyzing options to build and buy tools, applications, and services related to connected product systems and digital transformation initiatives.
Machine uptime is a trap
To begin however, let’s consider whether the first path toward incremental efficiency is a viable digital success plan at all. Yes, machines running more efficiently enable higher yields at lower cost. With this in mind, the industrial internet of things provides a path for increasing output without adding capital equipment. Asset monitoring provides a measurable return on investment. So it’s no surprise so many equipment providers, manufacturers, and facility operators choose machine uptime as the focus of their first industrial IoT system. That’s fine. You can get some quick wins here. Unfortunately, most systems can’t take you much further.
Beyond industrial asset performance
Here’s why that’s a problem. In this accelerating age of Industry 4.0 and artificial intelligence, now improved uptime and OEE are mere table stakes. They’re no longer differentiating. Even more problematic, many companies view remote monitoring as a pure technology play. What platform or devices can I plug into my things? Don’t get me wrong, such functionality absolutely creates business value through operational efficiency. But if all you do is adopt new technology, what happens when your competitors find similar technology to match your gains?
The commodity problem
Eventually you’ll all hit the same wall. Industrial equipment can only operate 24 hours a day. Furthermore, no matter how “smart” your machines are, eventually the laws of physics kick in, capping performance for everyone in the same competitive universe. You’re not strengthening your position in the value chain. You’re still playing the same role. Just faster. Still a commodity. Machine uptime is important. However, it’s not nearly enough to win in a connected world.
Transforming industrial data
Part of the problem is you’re only addressing part of the problem. Sure, collecting machine data and sharing it with operators, data scientists, and analytics tools is a good start. Machine learning and AI tools, applied solely to asset performance at the edge, is a big deal. Whether running on-premises on edge gateways or via cloud services, models and logic can help optimize asset performance. But your equipment is just one side of the overall business machine. What really fuels your digital rocket is when you create a system for bringing together information from your mechanical systems – the physical world – with your business systems and applications – your digital enterprise.
The new core of the industrial enterprise
Data collection enables remote monitoring and machine learning, which enable predictive maintenance and asset performance optimization. However, market dominance comes from leveraging these building blocks to create end-to-end automated systems and workflows. Digital industrial leaders operate differently. They change the game. They bring together the physical world with the digital enterprise and transform data into business value.
These organizations remotely monitor and automatically replenish consumables, more efficiently manage warranties and maintenance contracts, increase worker productivity, and dramatically deepen supply chain integration. New technologies make this transformation possible. However, putting this technology to use and bringing about the organizational change required to transform this potential into value requires both system integration and business realignment. We’ll dive deeper into proven methods for solving the whole problem in Part 2.