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.
Customers benefit from lower whole-life equipment costs, lower upfront capital investments, turning CAPEX into OPEX, industry-leading equipment up time, and a more transparent pricing structure. Machine and equipment vendors can also benefit from EaaS, which can be an attractive business model for a long-term sustainable revenue stream for manufacturing companies.
Industrial manufacturing examples
More industrial manufacturing companies are analyzing this business model for machines and equipment as well as for software and digital services. Kaeser (compressors), Heidelberger Druckmaschinen (digital printing machines), and Atlas Copco (mining equipment) are three companies that have successfully applied this business model to industrial machines and equipment.
You can find more information on the EaaS model for manufacturing companies here. Many manufacturing companies plan to offer equipment-as-a-service as an additional model for selected machines and selected customers rather than entirely replacing their traditional business model.
Challenges in sales and service
Most industrial manufacturing companies that have explored EaaS understand that it will impact most lines of businesses and that implementing it requires changes along the entire value chain, from marketing, sales, and service to R&D. They can manage the financial risk of every EaaS case by:
- Conducting a solid due diligence for every customer case
- Calculating the customer-specific price points, based on a solid life cycle costing analysis
- Working out smart contracts, considering the specific customer situations
- Defining exit criteria
- Analyzing each customer case before renewing the contract
To minimize risk, vendors should also monitor each customer to get transparency on profitability and understand what needs to be adjusted or changed before contracts expire.
While this information could be managed manually using spreadsheets, companies that need to scale to a larger number of customers should consider using an EaaS management software solution.
Managing financial risk is a key priority, but other areas to consider include optimization of machine operating costs and fully automating subscription billing processes.
Manufacturing companies also need aftermarket service organizations to provide service agreements for enhanced asset performance and efficient service delivery. Predictive maintenance and service powered by IoT technologies is key for optimizing operating costs of machines and equipment, and is a primarly enabler for the EaaS business model in industrial manufacturing.
Marketing will analyze the market and competitors, identify, segment, and classify potential customers, and define the competitive solution portfolios for EaaS offerings (considering machines and equipment as well as consumables, etc.).
R&D must ensure that machines and equipment are enabled for IoT-powered service and predictive maintenance and service by leveraging latest technologies such as predictive analytics, machine learning, IoT technologies, and more.
For more on digital transformation in manufacturing, see Leveraging Emerging Technologies In Manufacturing.