One of the buzzwords related to cloud computing that has been bandied about lately is SaaS. Software as a service (SaaS) is a software distribution model in which a third-party provider hosts applications and makes them available to customers over the Internet. SaaS is one of three main categories of cloud computing, alongside infrastructure as a service (IaaS) and platform as a service (PaaS).
In manufacturing today, the Industrial Internet of Things(IIoT) holds great potential for quality control, sustainable and green practices, supply chain traceability and overall supply chain efficiency. IIoT is the use of Internet of Things (IoT) technologies in manufacturing. It incorporates machine learning and big data technology, harnessing the sensor data, machine-to-machine (M2M) communication and automation technologies that have existed in industrial settings for years. The driving philosophy behind the IIoT is that smart machines are better than humans at accurately, consistently capturing and communicating data. This data can enable companies to pick up on inefficiencies and problems sooner, saving time and money and supporting business intelligence efforts.
As the industrial internet of things brings automation to an array of verticals, the as-a-service model is evolving to fill an emerging market for the hardware – sensors and other devices – that make up the so-called “things” in the industrial internet of things. In a recent report, this growing market is referred to as Equipment-as-a-Service(EaaS).
Equipment as a Service (EAAS)
Pay-per-use for machines and equipment (also known as equipment-as-a-service, or EaaS) has become a successful business model in various industries, including office equipment, medical equipment, jet engines, and others. EaaS front-runners in industrial manufacturing have already applied this model for new revenue streams to differentiate themselves in the marketplace and/or meet customer expectations.
Equipment-as-a-service or EaaS is rapidly moving from a specialized notion pioneered by the providers of medical and other specialized devices to general adoption. Thanks to the ease of connecting all sorts of equipment and devices in the internet of things (IoT), EaaS is also becoming more feasible and affordable. Today, EaaS is poised to make rapid inroads into complex building systems, such as high-rise elevators or HVAC, as well as manufacturing environments. While their customers benefit from lower whole-life equipment costs, no upfront capital investments, turning CAPEX into OPEX, industry-leading equipment uptime and a transparent pricing structure, the vendors of the machines and equipment can also benefit from an EaaS model. If done in the right way, it can be an attractive business model for a long-term sustainable revenue stream for manufacturing companies.
When companies look at equipment and machinery, they realize that they have static assets that need repair and servicing from time to time. What they now aim to see is services whose main value is to provide what people and companies want to accomplish, and equipment and maintenance are both a part of that. In many companies, the view of equipment and services is rapidly and dramatically changing.
The makers of high-end, business-critical equipment used, for instance, in manufacturing, oil and gas exploration, mining, and construction, have long sold equipment together with service contracts. For the customers using these machines, an interruption to their functioning would seriously compromise their ability to deliver to their customer commitments, so they pay for scheduled and emergency maintenance and repair in addition to investing in the purchase of the equipment.
EaaS takes a step beyond that with more effective operations and a simpler financial model. Companies’ primary interest is the ability, for example, to manufacture parts for jet engines. Instead of making a large investment in machinery, they pay the vendor a fee for delivering that ability at a certain service level. Equipment and equipment maintenance are essential components within that service. The vendor generates recurring revenue and may be able to build a larger business from services, parts, and materials.
In order to make this work, companies need to be able to rely on their vendor’s uncompromised uptime commitment. The vendor has to perform regular preventive maintenance, and also needs to be aware of materials and parts that are not performing to expectations and are at risk for failure, so they can be replaced or repaired. That, in turn, requires timely, accurate intel from and about the critical equipment assets. Connected sensors within the internet of things can gather and transmit detailed data that tell the service provider about the performance, material conditions, operational details, and location of the equipment, enabling proactive maintenance. If EaaS is implemented with the proper business intelligence, well-maintained equipment may be productive much longer and failures will be rare. EaaS providers will also be able to gather data from customer sites that help them improve their designs to make machinery more robust and better-performing. Equipment data will also make it easier to assess the costs and operational impact to decide how long machinery should be maintained and repaired, and when it’s better to replace it. Eventually, to the benefit of both EaaS vendors and their clients, maintenance and repair costs can go down.
Implementing an equipment-as-a-service (EaaS) model allows you to acquire the latest hardware and software while ensuring peak performance through ongoing support services. Companies that provide these services can help develop a comprehensive approach that enables manufacturing companies to address global coverage requirements, accelerate technology migrations and take advantage of new advancements.
Industrial Manufacturing Examples
More and more industrial manufacturing companies are analysing this business model for machines and equipment, as well as for software and digital services for their machines. Companies like Kaeser (compressors) and Atlas Copco (mining equipment) are prominent examples of successfully applying this business model for industrial machines and equipment. Of course, manufacturing companies are not planning to replace their traditional business model and will continue to sell their machines and equipment, but plan to offer “Equipment-as-a-Service” as an additional model for selected machines and selected customers.
Challenges in Sales and Service
Many industrial manufacturing companies who had a deeper look in EaaS as a new business model have realized that it is not easy to provide this new model to each of their customers in a profitable way: it has an impact on most lines of businesses of the company and requires changes along the entire value chain, mainly across marketing, sales, service, and R&D.
Industrial manufacturers need to manage the financial risk of every EaaS case:
- conduct a solid due diligence for every customer case
- calculate the customer-specific price points, based on a solid lifecycle costing analysis
- work out smart contracts, considering the specific customer situations
- define exit criteria
- analyze each customer case before renewing the contract
To minimize the risks and to ensure a profitable EaaS contract, the vendor needs to monitor each customer case to get the required transparency on the profitability and to clearly understand what needs to be adjusted or changed when the contract will expire and needs a renewal.
All these points could be covered with spreadsheets and manual work. However, when scaling this business model to a larger number of customers, manufacturing companies should consider a proper software support through an EaaS management cockpit in their sales organizations.
Managing the financial risk is a key point for many manufacturing companies who embark on an EaaS journey, but there are other key topics to be managed: the optimization of the operating costs of the machines and fully automated process for the subscription billing. Manufacturing companies need the right aftermarket service organizations to provide the required service level agreements for an enhanced asset performance and an efficient service delivery for an attractive cost model to their customers. Predictive maintenance and service powered by IoT technologies is a key point for the optimization of the operating costs of the machines and equipment – an enabler for an EaaS business model in industrial manufacturing.
As always, marketing will analyze the market and competitors, identify potential customers, segment and classify them, and define the competitive solution portfolios for the EaaS offerings (considering machines and equipment as well as consumables etc.). And of course, R&D needs to ensure that the machines and equipment are enabled for an IoT-powered service and predictive maintenance and service, also leveraging latest technologies such as predictive analytics, machine learning, IoT technologies etc.
Imagine the scenario where companies can spec out their gear and pay a fixed dollar per month for use of the equipment. At the end of term, they can spec out the replacement, tweak the payment and keep on keeping on. This is the basis of Equipment as a Service (EaaS). The above concept does seem like what we call leasing today. But clients don’t really think of it quite that way. Most end users, manufacturers and dealers still see the process as one of formally obtaining financing where the EaaS feels far more like a “subscription” of sorts.
EaaS opens the door to a whole new way of thinking. More than finance, it would be a total cash flow approach to acquiring, paying for, managing and disposing of equipment. The life cycle management may be the major plus point but it also ensures a truly integrated customer experience. The agreement might even include maintenance, service, asset tracking or other value-added life cycle management things. Customers will get so used to the operational subscription-based approach, that haggling over implicit rate or spread will not even be a thing.
To fully benefit from the new technology, industrial organizations need to rapidly move away from the current practice of fixing equipment only after failure, or at pre-determined intervals. Remote diagnostics and maintenance solutions are a key factor in enabling original equipment manufacturers to offer equipment-as-a-service models. Early adopters are likely to benefit from the predictive maintenance that EaaS promises to offer.