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In the industrial sector, the transition to Equipment-as-a-Service (EaaS) and Product-as-a-Service (PaaS) models presents both significant opportunities and challenges. Unlike the rapid adoption seen in consumer markets (with media, entertainment, and streaming), scaling these service-oriented offerings in industrial contexts has been notably slower. In fact, most B2B and industrial companies which have launched subscription business usually establish a target of 5% to 10% of revenues moving to the As-a-Service business model in the 3 to5 years after launch. A key challenge lies in determining the appropriate level of investment in essential technologies—such as monitoring and metering solutions, license and entitlement management, and subscription billing software—when sales from EaaS and PaaS are still in their infancy and scaling very slowly. This creates a classic "chicken and egg" dilemma: how can companies justify the investment in the necessary technology stack without substantial subscription-generated revenue, yet how can they generate that revenue without first making the investment?
The slow pace of adoption in industrial markets
Despite the broader subscription economy's growth, the adoption of EaaS models in industrial markets remains limited. Research indicates that less than 1% of equipment sales in 2023 were achieved through EaaS contracts. This slow uptake can be attributed to several factors, including the complexity of industrial equipment, long sales cycles, and the significant shift in business models required for service-based offerings (IoT Analytics). In contrast, in 2025, more than 85% of software sold today is in the form of SaaS (https://www.spendesk.com/blog/saas-statistics). Despite the attractiveness and interest in PaaS and EaaS, the transition towards the As-a-Service model is still slow.
The importance of the right technology stack
Implementing EaaS and PaaS models necessitates a robust technology infrastructure. Key components of this tech stack include:
- IoT connectivity: Enabling real-time data collection from equipment to monitor usage and performance.
- Data analytics platforms: Processing and analyzing data to provide insights into equipment health, usage patterns, and customer behavior.
- Metering solutions: Accurately measuring equipment usage to support pay-per-use/X billing models.
- License and entitlement management: Ensuring that customers have appropriate access to services and features and managing upgrades or downgrades.
- Billing and invoicing systems: Handling complex billing scenarios, including subscription management, usage-based billing, and integration with financial systems.
Building this infrastructure requires substantial investment, both in terms of capital and organizational change. Companies must carefully assess their current capabilities and identify gaps that need to be addressed to support EaaS and PaaS offerings. This “new” tech stack must also be integrated into the “legacy” stack including CRM and ERP. The complexity for IT team is enormous. But there is no other way to do it. Managing PaaS or EaaS offers in a legacy infrastructure is extremely labor intensive and error prone.
Balancing investment with revenue potential
Determining the right time to invest in the necessary technology for EaaS and PaaS is challenging. Investing too early, before sufficient revenue streams are established, can strain financial resources. Conversely, delaying investment can result in missed market opportunities and allow competitors to gain a foothold. Top management who approved the necessary investments tend to lose patience quickly and often are quick to de-invest.
One approach is to start with pilot programs that target specific customer segments or equipment lines. Some of that can be done within a digital incubator. This allows companies to test the viability of EaaS models, gather customer feedback, and refine their offerings without committing to a full-scale rollout. Insights gained from these pilots can inform broader implementation strategies and help build a business case for further investment. However, this approach remains manual and fragmented.
Overcoming the chicken and egg dilemma
To navigate the investment conundrum, companies can consider several strategies:
- Strategic partnerships: Collaborating with technology providers or other industry players can help share the investment burden and provide access to necessary expertise.
- Incremental implementation: Gradually building out the technology stack allows for spreading costs over time and aligning investment with revenue growth.
- Leveraging existing infrastructure: Utilizing current systems and upgrading them as needed can reduce initial investment requirements.
- Incubation or spin-off approach: Establishing a dedicated incubator or a separate company to develop the EaaS model outside of the main corporate structure can circumvent bureaucratic bottlenecks, foster agility, and accelerate go-to-market strategies. This approach enables a leaner, more experimental environment, free from the constraints of legacy systems and internal processes, making it easier to test, refine, and scale the new business model with minimal disruption to core operations.
By carefully planning and executing these strategies, companies can mitigate the risks associated with the chicken and egg dilemma and position themselves for success in the evolving industrial landscape. The key consideration remains: what is the right sales revenue threshold that PaaS and EaaS Product Owners need to show to go to upper management and make a business case for large investments? Of course, it depends on management’s appetite to take risks and make big bets. Large industrial companies such Caterpillar, Schneider Electric, Carrier, and others have done it.
Conclusion
Transitioning to EaaS and PaaS models in the industrial sector is a complex endeavor that requires careful consideration of technology investments and revenue potential. While the path is fraught with challenges, including slower adoption rates and significant upfront costs, the potential benefits in terms of recurring revenue streams, enhanced customer relationships, and competitive differentiation make it a compelling strategy. By thoughtfully balancing investment with anticipated returns and developing strategies to manage the risks, companies can successfully navigate this transformation and capitalize on the opportunities presented by as-a-service business models. At the end of the day, every company is different and approach investments in disruptive innovations differently. Making big bets takes management courage and ambition.
