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Machine-As-A-Service – Business Model Evolution in Capital Goods Industry

Nitin Karn
18 Apr 2023

The success of the revolutionary As a Service (AAS) model or Servitization, in industries such as software, media, telecom, automotive etc., has led to its entry into the Capital Goods industry.

Industry is experiencing a shift from traditional service models to a smart connected product and service-based offering, typically Machine-As-A-Service (MaaS). Traditionally OEMs (original equipment manufacturers) and customers focused on the traditional “make-sell-ship” business model; today customers want a focused approach in order to minimize capex with utmost inclination on productivity.

With the emergence of micro, small, and medium enterprises (MSMEs), usage-based service models came into play. It helped MSMEs to scale up faster with lower capex, and avoid ownership issues while OEMs enjoyed a continuous connect and flow of revenue. Overall Equipment Effectiveness (OEE) remained a challenge for MSMEs. OEMs also wanted more operational connect than having a mere transactional connect with the customers.


As per a Capgemini Research Institute (CRI) survey, 62% of organizations surveyed are struggling to scale IoT applications due to cybersecurity and data privacy threats.

Backed with technology and reduced cost, Product-As-A-Service (PaaS) model provided some of the answers over the traditional usage-based models. After-sales service, condition monitoring, predictive maintenance fall into this category. OEMs were now more operationally connected to the customer, positively impacting their market share. Customers could anticipate the machine breakdown and plan the maintenance in advance and experience a better control on the machines to reason out the OEE effectively.

Leveraging cybersecurity, the customers were provided with the product insights in a secured environment while shielding the machines from cyber attacks. With the data hosted in Cloud, OEMs and customers could receive real-time machine insights anytime anywhere.

The key growth drivers are the falling cost of sensors and data storage, availability of data storage and connectivity. The IT-OT convergence is enabled via rich source of ready-to-use applications, API interfaces, and emergence of standard communication protocol. The low-code/no-code platforms enable MSMEs to scale rapidly without requiring coding talent as was needed previously by early adopters.


Leading OEMs are realizing that customers no longer need products or services but need outcome/productivity; this has paved the way for Outcome-As-A-Service (OaaS) model. This business model would allow customers to pay only for machine output/productivity while requires OEMs to carefully study and capture the performance via key performance indicators (KPIs). This highlights the need for machine data reliability as the OEM’s revenue is integrated with the machine’s performance.  Traditional contracts do not provide enough conviction on data reliability. Also, organizations may be reluctant to share certain information.  

Reliability of machine data depends on three factors– low latency, no data loss, and immutable data (which cannot be edited once captured). The emergence of 5G and Blockchain would jointly enable the machine data reliability and immutability. Machine data would be stored in Blockchainsmart contracts. The smart contracts would automate the month-end invoice consolidation based on various KPIs and contract conditions.

Immutable machine data will now be the single source of truth for equipment lifecycle. OEMs would enjoy a transparent picture of usage and health across all the “performance” buyers along with clear insights on the resale value.

To summarize, traditionally industrial manufacturing industry transitioned to usage-based model, a shift in the ownership model from customers to OEMs, thus transitioning customers from CapEx to OpEx approach. Post that, machine availability and performance monitoring enabled customers to have a better control over the process and ROI. Technologies such as IIoT, cybersecurity, Cloud, and analytics were critical enablers. In the future, customers will seek to pay based on KPIs such as performance, availability etc. giving rise to the Outcome-As-As-Service (OaaS) business model. This approach needs integration of service with the OEM’s revenue model. Data reliability and challenges due to low latency, data loss, and immutability, sit at the core of it. Adoption of technologies such as 5G and Blockchain would help ensure data reliability and enable this business model for the NEXT evolution in the ecosystem.

Download the full infographic to find out more about – Machine as a Service business model in Manufacturing industry.