Thanks to the Internet of Things, the next product you design could be a service. Find out how companies are building continuous revenue streams by delivering products as services.
Product-as-a-Service (PaaS) is a business model that allows customers to purchase a desired result rather than the equipment that delivers that result. For example, a manufacturing operation may need to have two pieces of metal welded together. In the traditional purchasing model, the manufacturer would buy a welding robot. In the PaaS model, the company would purchase a certain number of welding operations, not the robot itself—in effect, paying for repetitions instead of robots. This model offers benefits to both the customer and the provider. Some examples of products as a service, which shift the risk of performance from the customer to the manufacturer, include jet engines, compressed air, valves, robots, water pumps, smart lighting systems, and even passenger trains.
In the research report The Next Product You Design Might Be a Service Thanks to IoT, engineering.com interviewed companies on the leading edge of implementing products as a service, with a view to describing and categorizing the types of products that can be delivered as a service and the technologies that make this possible.
Background
The Internet of Things (IoT) enables PaaS thanks to low-cost sensors, powerful embedded controllers and wireless communication. PaaS combines remote monitoring with data analysis, which facilitates predictive maintenance, reduces machine downtime, and optimizes productivity.
Machine learning algorithms give a more in-depth data interpretation, often providing clients and manufacturers with insights into a products’ use, performance, and environmental conditions. This leads to design and implementation changes that can increase efficiency and reduce costs, delivering additional value to both customers and providers.
PaaS platforms include off-the-shelf and customized applications that alleviate the need for manufacturers to build everything from scratch. In many cases, providers can convert their products to services in just a few months with no investment in infrastructure and minimal risk. Custom dashboards are created with a drag-and-drop interface that often requires no coding skills, enabling engineers to easily monitor equipment in the field through secure Internet channels using any connected device.
Clients, Manufacturers, and Providers
A PaaS relationship typically involves agreements among three entities: the client, who purchases the service; the manufacturer, who delivers the product and its associated services; and the PaaS platform provider, who handles the infrastructure, including data collection, transmission, storage, security, and analytics.
State of the Industry
PaaS is still in its infancy. A few manufacturers are in the early adoption phase, while most are still trying to figure out how to leverage the new model to their advantage. PaaS platform providers, such as Siemens MindSphere, PTC ThingWorx, and Aras PLM, have complete suites of tools at the ready, waiting for manufacturers to take advantage of their features.
To help with the transition, platform providers are helping manufacturers ease into the PaaS model by delivering value-added services to existing products. Machines can be outfitted with sensors, embedded controllers, and communication gear to allow manufacturers to monitor a product’s performance in the field. A manufacturer can then use that information to help its client operate more efficiently, and it can also use the information to find ways to improve the product itself. Siemens, which is both a manufacturer and a PaaS platform provider, now includes IoT capabilities in its factories, recording and analyzing critical sensor data that enables engineers to prevent problems and optimize operations.
Clients are still trying to understand what data they can collect from the PaaS model and how that information might help them to get more value out of the product they purchased. As clients begin to see the added value that the services provide, they become more willing to purchase a PaaS. This, in turn, will likely convince manufacturers that they can make money by delivering products as services under a new business model.
Manufacturers are beginning to realize that the PaaS model can help them to differentiate themselves from their competitors by offering more value to their customers than just the product itself could deliver. Remote monitoring is a starting point, but the significant increase in value will come from advanced data analytics.
The Benefits of PaaS
PaaS offers advantages to both clients and manufacturers. For clients, PaaS transforms large capital expenses into smaller operating expenses, allowing them to amortize the cost of the product throughout its life cycle. Additionally, the client no longer assumes the risk of product failure or the responsibility for maintenance, as both are typically included with the service. Further, PaaS can help a client optimize its own use of a product. Finally, PaaS helps ensure that the client won’t be stuck with obsolete equipment since the service includes upgrades. We already see this in the smartphone industry where users subscribe to a cell phone plan that includes annual upgrades to the latest and greatest phone, the cost of which is rolled into their monthly fees.
On the manufacturer’s side, PaaS delivers a consistent revenue stream, which is a more sustainable business model. It also allows them to see how the product is being used in the field, which could offer insights into product reliability, design, and potential feature enhancements. Manufacturers can use data analytics to find ways to enhance the value that customers receive, which ultimately provides additional revenue for both the client and the manufacturer.
Making a Product-as-a-Service
Before creating a product as a service, or even converting an existing product to the PaaS model, manufacturers need to analyze customer needs and ascertain what additional features clients are willing to purchase. The focus must be on the value that the service provides above and beyond the product itself.
On the business side, the PaaS model will affect revenue flow, customer support, liability, and marketing strategies. It’s important to have recent product statistical data to ensure that the added service can be delivered at a profit. This information will help determine the nature of the contract between the manufacturer and the client.
Next, one must determine what type of data needs to be collected, which sensors will measure those quantities, and how that information will be processed. Some sensors include embedded microcontrollers, which can handle much of the data processing right at the product level. In manufacturing facilities, a gateway computer may perform the data analysis. Both are examples of “edge processing,” where the number crunching occurs on-site rather than in the cloud. Periodic snapshots of data can be sent to the cloud for further analysis and secure, off-site storage. This is where PaaS platform providers earn their keep—they can help manufacturers determine the logistics of data collection, storage, security, and analysis.
The addition of sensors, communication, and computers implies that even a strictly mechanical product will become an electromechanical device in the PaaS model. Engineering design tools that mix electronic and mechanical design are gradually evolving to facilitate this integration.
PaaS also affects product design. Manufacturers need to consider the entire product life cycle, even beyond the warranty period. In fact, there is no warranty, per se, since the manufacturer technically owns the product. So, the manufacturer, not the client, must assume responsibility for maintaining the product throughout its life, as well as handling the proper refurbishing, recycling or disposal of the product.
Data Collection and Analytics
So, you’ve attached sensors to gather data. Now, what do you do with it? At the lowest level, sensors and IoT allow engineers to remotely monitor a product, which turns preventative maintenance into predictive maintenance. Rather than replacing parts at statistically determined intervals in order to prevent failure, predictive maintenance lets us know when component failure is imminent so that parts can be replaced on a “just-in-time” basis.
A more challenging issue is establishing added value beyond the maintenance aspect. For example, aircraft engine manufacturers don’t sell engines, they sell propulsion by the hour. The engine’s sensors are designed and located so they not only facilitate predictive maintenance, but they can also help the airline improve its fuel efficiency. That saves the client money, which helps to justify its contract with the manufacturer.
Case Studies
The report includes detailed case studies of three companies—one in high-tech manufacturing, another that helps ensure clean water in developing nations, and a third in the mass transportation industry. We explore their reasons for delivering their products as services and examine the processes by which they moved to that business model.
Download the complete report here: The Next Product You Design Might Be a Service Thanks to IoT.