- By Sujata Tilak
- IIoT Insight
In recent years, every sector that needs expensive and complex assets—generator sets, jet engines, packaging machines—is looking for options that will help reduce upfront capital investments in these machines and bind machine builders and equipment suppliers to promised outcomes and services. Especially as manufacturing starts moving from mass production toward mass customization, which may be dynamically driven by end clients, such models become necessary. This is going to create an entirely new business model, which will be the dawn of a new era for manufacturers.
Looking from the supply side—from the point of view of the machine builder—this model can be termed “servitization in manufacturing.” In simple terms, servitization is a business model in which manufacturers build new revenue streams from services related to their products. In other words, manufacturers have a portfolio of integrated products, services, and outcomes related to their machines and components in a conscious and explicit strategy to create a critical differentiating factor in the marketplace when compared to similar products offered without integrated services.
From the consumption side—from the point of view of the purchaser of such a machine—the model can reassure committed partners (and not just vendors) who will have as much stake in upkeep and productivity as their clients. These partners will provide not only agile support but also outcome commitments. These of course will be driven by work discipline and associated detailed standard operating procedures that will improve overall efficiency and productivity. One of the important outcomes will be the optimized investment in capital equipment.
Levels of servitization offerings
There are different levels of servitization offerings based on the maturity of the entities involved, type of product, and technology used:
Basic-level servitization provides maintenance, repair, overhaul (MRO) and support for the asset. Most manufacturers traditionally provide these services reactively, meaning based on a customer request or at a fixed frequency (e.g., send a technician for maintenance every quarter).
Intermediate-level servitization provides similar MRO and support services proactively, and enabled by remote monitoring and diagnostic capabilities. This also means rapid and precise service to each customer rather than a vanilla model for everyone.
Advance-level servitization has variations, including:
- Product as a service (PaaS), also described as pay per use. Instead of paying for the asset, customers pay for use of the product or per unit of service provided by the asset.
- Availability and/or quality service level agreement (SLA). Manufacturers take contractual responsibility for asset availability and/or output quality.
- Outcome-based model. Original equipment manufacturers (OEMs) sell business outcomes, rather than the asset. This can be looked at as a combination of PaaS and SLA.
- Advisory services. Advisory services for asset/process optimization with outcome-based revenue including benchmarking and other inputs.
IIoT makes servitization possible
An obvious question: What is driving the change that makes this new business model a possibility? As you can see, being connected to the asset and being able to access operational and diagnostic data in real time is critical to every level of this model. You cannot and will not want to depend on manual reporting for outcome-based models or SLAs that are legally enforceable. Thus, sensors, the Industrial Internet of Things (IIoT), and advanced analytics platforms are the keys to servitization. These are the technology enablers that collect real-time data, allow access to the asset in real time, and evacuate data to analytical tools to deliver value insights to all stakeholders in real time.
Let’s explore how IIoT enables delivery of the different servitization models described earlier, and see some examples. For intermediate-level services, OEMs provide support and maintenance proactively before a fault or a breakdown. OEMs use remote asset monitoring to continuously monitor asset health and intervene if a problem is building up. Techniques like condition monitoring and machine learning–based predictive algorithms are used.
For example, a maker of expensive paper-processing machines uses the PlantConnect RAMS product from Ascent Intellimation (AIPL). The machine maker uses the RAMS product to monitor these complex machines for customers across the globe and avoid breakdowns with proactive intervention and advice. The customers also use the same data to enforce best practices of usage and enforce operator behavior.
One game changer in this will be to make the asset itself smart so it can run its own systemic checks and algorithms. This will reduce dependence on support center teams and help reduce the cost of support. An example of what is possible is a technology-enabled car that sends alerts to the service center when maintenance is required, based on various sensors that are monitoring the car.
PaaS is possible if the product itself is smart and keeps detailed records of its output. Some asset types where PaaS is used are generator sets, pumps, compressors, and jet engines. Nonindustrial examples include photocopy machines and coffee machines.
Advanced examples of servitization
A more advance level of proactive maintenance is a service level agreement that guarantees a certain percentage of availability and/or quality of output generated by the asset. Technologies like digital twins are used to monitor the asset in operation and keep it available and in top condition through remote and on-site services. Using advanced analytics, the manufacturer is continuously improving the asset and deploying these upgrades in the field. Needless to say, these improvements are software driven. These contracts also include a specific operating environment, trained operators, etc. Examples include some high-end medical equipment manufacturers who offer such SLAs.
Some OEMs use outcome-based models that guarantee certain levels of outcome and pay-per-use pricing. An example is an automotive OEM that offered buses with defined operating performance to a public transportation authority. The authority purchased mileage rather than the bus itself. Here, the OEM has to deploy continuous monitoring of not only the asset, but the operating conditions as well.Advisory services can be some of the most advanced. Manufacturers feed continuous production data to advanced analytics models using artificial intelligence and machine learning algorithms that advise on performance improvements, fuel savings, safety, energy optimization, etc. Deep expertise of the product and customer domain is essential to build these analytics models. Some examples are vibration analysis for turbines, fuel efficiency advisories for ships and airplanes, route advisories for ships and airplanes, and energy optimization services for entire plants. One company uses PlantConnect RAMS to provide advisory services for boiler performance optimization, while another is using AIPL’s MarineIoT to provide fuel efficiency and route advisories for maritime vessels.
Pros and cons
Servitization can present a win-win opportunity for both supplier and customer. For the supplier, benefits include higher and recurring revenue, a continuous relationship with the customer, the supplier moving up the value chain, and higher sales of spares and consumables. For the customer, benefits include a product bundled with reliable and high-quality service; higher availability, quality, and guaranteed outcomes for assets; and a CapEx to OpEx accounting model.
On the other side, there are many challenges to a servitization arrangement, especially when it comes to asset availability/quality SLAs and outcome-based models: The contracts are tricky; creating a measurable success metric acceptable to both parties is not easy; and premiums to be paid for servitization make sense only if the product is critical to the customer and/or is of high value.
Overall, technology alone is not enough for building a successful servitization portfolio. What is needed is deep understanding of a customer’s needs and a willingness to constantly adapt and evolve the asset and services to achieve desired outcomes. This is not easy. It needs a high degree of flexibility in the design, manufacturing, and delivery of the asset. It also needs very high quality, reliability, and robustness in the asset itself, and doing all this in a cost-effective way to remain competitive in the market. In other words, the manufacturers themselves have to adopt Industry 4.0 and smart manufacturing as a way of operating.
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