Entering The Era Of Intelligent Asset Management
For many manufacturers today, the focus of their business is not so much “making stuff” as it is delivering better business outcomes for their customers through asset-as-a-service offerings. What’s enabling this new business model is the evolution of enterprise asset management (EAM).
From preventative to predictive
In the past, the best companies approached EAM as planned or preventative maintenance. Now, leading organizations use an intelligence-based approach, where maintenance teams monitor conditions in real time.
Real-time condition monitoring requires asset intelligence, which in turn requires asset connectedness. Fortunately, in today’s world of pervasive Internet of Things (IoT) technology, almost every asset deployed in the field is designed and manufactured with built-in sensors to provide data on equipment status and health. With the ability to analyze this data within the context of their business, leading companies can now predict issues before they arise — and take swift action to remediate them.
No longer do companies need to waste money on scheduled maintenance procedures that may or may not be needed. Instead, they can perform maintenance only when required — maximizing the lifetime value of parts, optimizing the technicians’ time, and delivering a great customer experience.
Blurred boundaries and new business models
For asset manufacturers, real-time analytics and predictive maintenance create the opportunity for entirely new business models. In the past, manufacturers made the assets and customers operated them. Today, these boundaries are blurring as manufacturers leverage new asset-as-a-service business models and deliver outcomes rather than just the physical assets.
Think about what customers actually want. Do they want shiny new HVAC machines sitting on the roofs of their factories? Or do they want temperature-controlled plants and facilities that enable equipment and people to work at the best of their ability?
If it is the former, you (the manufacturer) design, build, and sell the HVAC machine — but the sale is a onetime deal. If it is the latter, you still design and build the HVAC machine — but now you deliver it as-a-service. What’s changed is that uptime and availability (or the ability to continuously control the temperature of plants) is your responsibility. For you to get paid, the machine needs to work.
If your revenues depend on uptime, you may want to optimize maintenance as much as possible. This is where predictive analytics comes into play. With the ability to analyze incoming sensor data in the context of historical performance data, for example, you can strike a balance that optimizes maintenance and drives down costs. This is what makes the asset-as-a-service model attractive to both the customer and the manufacturer.
Moving up the value chain
Because the responsibility for asset management and maintenance shifts to the manufacturer, there are now far more chances for collaboration with the customer.
Closer collaboration yields opportunities. Perhaps the asset intelligence that you’ve gathered as the manufacturer provides insights into how to improve the design of a future asset — or how the asset can better interact with the customer’s business processes to create more value.
Now, as the manufacturer, you’re moving up the value chain — engaging with the customer to ensure business success.
Predicting the future and helping the world run better
Take, for example, a large manufacturer of agricultural machinery that is using IoT technology to transform its business. With tractors and other equipment connected through onboard sensors that monitor a wide variety of metrics, this manufacturer can collect real-time data about planting, soil preparation, fertilizing, harvesting, and more.
Increasingly, the farming companies who use these IoT-equipped tractors depend on the data generated to manage their farm better. For example, the manufacturer can now help determine the exact amount of fertilizer to apply to each section of farmland, helping to reduce the cost of operations by conserving fertilizer while maximizing yields by optimizing its application.
This sounds quite close to what might be called a valued business partner — all with help from intelligent asset management.
Integrated intelligent asset management capabilities are essential to reduce unplanned downtime and improved asset performance. To learn more, download this new white paper from ARC Advisory Group.