Pay-per-Use for machines and equipment (EaaS, Equipment-as-a-Service) has been a successful business model in different industries, mostly known for office equipment such as printers and copier machines, medical equipment and jet engines. EaaS frontrunners in industrial manufacturing industries have already applied this business model for new revenue streams, to differentiate in the market place or to meet the expectation of some of their customers.
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.
Industrial Manufacturing Examples
More and more industrial manufacturing companies are analyzing this business model for machines and equipment, as well as for software and digital services for their machines. Kaeser (compressors), Heidelberger Druckmaschinen (digital printing machines) and Atlas Copco (mining equipment) are prominent examples for successfully applying this business model for industrial machines and equipment. For more information on the EaaS model for manufacturing companies please read my blog “Digital Transformation & Customer Centricity for Industrial Manufacturers – Part Four: New Business Models”. 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. For more information on the impact of the service organization please read my previous blog on this topic.
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 need 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.
I am very interested in other thoughts on “Equipment-as-a-Service” for industrial manufacturing companies! Any ideas, experiences, best practices or concerns?
Please share concrete examples on how manufacturing companies leverage EaaS business models for machines and equipment to grow their businesses and attract their customers.
Dietmar Bohn is a Vice President in Industry Solutions Management at SAP SE, focusing on customer centricity and digital transformation. He brings more than 15 years of CRM experience from both outside and inside SAP and more than 25 years of industry experience. Dietmar has held various executive roles spanning CRM strategy projects, CRM implementation projects, CRM development and CRM product management. Before joining SAP, Dietmar has held different management positions in R&D, IT and Global Sales & Marketing organizations at Heidelberger Druckmaschinen AG. Dietmar holds degrees in Electrical Engineering and in Telecommunications.