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Artist's rendition of Industry 4.0

Equipment-as-a-Service is on the IIoT Path

May 23, 2022
Predictive maintenance and new technologies change the model for OEMs.

The digital business transformation requires new thinking and methodologies which lend themselves toward growth and resilience. However, this encompasses more than the trendy terms such as the Industrial Internet of Things (IIoT) and Industry 4.0. Before developing the strategies for future-proofing a business, it’s important to understand what’s driving the digital transformation.

While many factors could illustrate the potential of Industry 4.0, one focus is Total Cost of Ownership (TCO), which includes the cost of machinery along with maintenance, operations, consumables and other related costs. For many machine operators, a buying decision will hinge entirely on TCO. This is a domain where Equipment-as-a-Service (EaaS) and predictive maintenance can significantly impact the business case for operators and create opportunities for machine builders and operators alike. Equipment-as-a-Service (EaaS)

EaaS is a business practice where equipment, machinery and/or production systems are offered by an OEM via a variable consumption or usage model. The form can vary, but often is based on factors such as usage, output and availability. While this may sound like a lease, EaaS is quite different. Think more along the lines of managed services.

In a typical purchase-to-own model, customers make a one-time equipment purchase that may last a minimum of 10 to 15 years. In many circumstances, OEMs have little visibility as to how equipment is being used once it leaves the warehouse. Many OEMs fail to find substantial after-market opportunities with equipment operations. OEMs might receive additional revenue from service calls throughout the machine’s lifecycle, but that’s different from an ongoing, deeper relationship built through a service model. 

EaaS business models flip the traditional purchase model. Instead of customers buying the machine outright in a single transaction, they pay solely based on other factors such as consumption or usage. OEMs or third-party financing partners retain ownership and, as such, absorb the responsibility for either providing or managing maintenances service, repairs and parts replacements.

Utilizing EaaS, OEMs can achieve a continuing flow of revenue and the opportunity to uncover new revenue streams based on dormant machines and underutilized services. They’re also able to foster a more consistent relationship with machine operators, as they’re in constant contact with machinery and customers. This model also allows for deep learning based on vast amounts of collected data, which impact everything from operational processes to predicting when a machine will need servicing or replacement.

Customers also can focus on their core businesses and get what they need most: reliable machinery, producing the parts or outcomes they desire, managed and upgraded when necessary. Their equipment expenditures also transition to being an operating expense rather than capital expenditures, which have a greater negative cash impact, require upfront investments and crowd their balance sheets.

This model improves operations, revenues and resiliency for all. However, for most industrial companies, a key success factor with EaaS is the optimization of TCO for machine operators through the reduction or elimination of downtime or optimization of planned maintenance costs through predictive maintenance. Predictive Maintenance Predictive maintenance (PdM) is an enabler of EaaS. It uses historical data, combined with sensor data, domain know-how and artificial intelligence, to detect anomalies that inevitably lead to a breakdown and downtime. The system then either creates an alert for servicing or automates a fix. These capabilities help to:

  1. Prevent and minimize unplanned downtime (lowering business interruption)
  2. Reduce planned repair and maintenance cost
  3. Enable compliance guarantees and maintenance warranties
  4.  Provide the possibility for remote monitoring and operation

Another way to contextualize PdM and condition monitoring is by understanding its predecessors (and sometimes former extremes): the “run to failure” and preventative maintenance models. Both are unpredictable and inefficient when it comes to planning.

Condition monitoring enables more proactive management which can be enable guaranteed outcomes and real-time systems monitoring. True PdM can build upon this level of maturity and even lead to an understanding of remaining useful life.

Consider these statistics from the US Department of Energy’s report on “Achieving Operational Efficiency.” An investment in predictive maintenance can yield ROIs of up to 10×. Savings can come from several areas including reduction in maintenance costs ranges at 25-30%; 70-75% savings from elimination of breakdowns; 35% to 45% savings in reduction of downtime; and 20 to 25% savings in increase to production.

So, what does all of this mean for OEMs and their customers? Better machine performance, greater uptime and resiliency, and increased revenue.

Predicting the Path Forward

Whether utilizing the services or providing them, a digital transformation is an entirely new way of doing business that impacts your people, planning, research, development, manufacturing, marketing, sales and services. For these reasons, your strategy must be spot-on. Here are some best practices to consider:

  • Internal alignment is required. To get company-wide buy-in, it’s essential to approach digital transformation as a CEO-driven agenda. This approach will be the guiding principle for the entire organization from the top down.
  • Remember why your business exists. Take note of the clients you’re serving today, and zero in on some you’d like to bring in as future customers. A focused approach means you won’t be everything to everyone. 
  • Establish the outcomes you want to see. Allow business goals to dictate strategic moves and the technology used. Don’t deploy a new technology for the sake of adopting technology. Be sure your strategy is sound before making any moves that could influence what’s important to your business.
  • Clearly define what success means for everyone. Create an operational definition of success that everyone can easily understand and move toward together. Each scenario is unique, and success may look different to different entities.
  • Assess possible risks. Proper risk management is always better than complete risk aversion. Risks may emerge at any step. Risk management may even become a business practice all its own, so you’ll want those strategies in place before any making big moves.
  • Stay flexible. Calculate customer-specific pricing models based on known or expected lifecycle costs and apply them to contracts and agreements. Contextualizing a customer’s specific situation lets them know you understand their business well.
  • Organized change needs a reliable cadence. Your strategy should address the entire ecosystem instead of single initiatives, pilot programs or start-and-stop processes. Build in micro-goals along the way. These incremental checkpoints help you make sure everything is going as planned, allow adjustments as needed and give your team moments in time to celebrate.

Getting the Digital House in Order

This type of digital transformation creates a new environment that requires different ways of thinking and operating internally.

A partner can help focus the digital transformation efforts. The best partners not only provide guidance and counsel but can also serve in a conductor-type of role where they expertly bring all the moving parts and pieces into harmony. Prioritize a partner that has proven experience helping industrial companies implement EaaS business models and offers insurance-backed guarantees on their work. Digital transformation also has transformed the way equipment outcome is managed. Embracing EaaS with PdM is a win-win model, and the machine world should consider it a viable alternative to business as usual. So that leaves one question: Is your digital house in order?

Krishna Yarramasu is the vice president of strategy at relayr, an Industrial Internet of Things company focused on solutions for risk-free digital transformations.

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