Unlocking new revenue streams with heavy equipment service lifecycle management

By Hendrik Lange

Technological advancements, evolving customer demands and economic pressures are driving significant changes in the heavy equipment sector. As manufacturers navigate these shifts, heavy equipment service lifecycle management (SLM) has emerged as a pivotal strategy for improving profitability, enhancing customer satisfaction and ensuring business resilience. In the podcast below, host Chad Jackson from Lifecycle Insights and industry expert Dominique Gilles from Siemens Digital Industries Software discuss these benefits and explore how new technologies will transform SLM going forward.

The business case for heavy equipment service lifecycle management

Original equipment manufacturers (OEMs) in the heavy equipment industry face shrinking margins on new product sales due to increasing product complexity, customization demands and low production volumes. In contrast, aftermarket services—such as maintenance, spare parts sales and upgrades—offer significantly higher margins and recurring revenue streams. These services not only stabilize revenue during economic downturns but also enable OEMs to monetize their products over their extended lifespans.

In addition, the growing complexity of heavy equipment, particularly with embedded software and electronics, creates a demand for specialized knowledge that OEMs are uniquely positioned to provide. By stepping into the aftermarket service space, manufacturers can leverage their deep product expertise to offer tailored solutions that meet customer needs while driving profitability.

Due to the convergence of these two trends, engaging in heavy equipment service lifecycle management is no longer optional for OEMs.

Key capabilities for success

For OEMs to thrive in the aftermarket service business, they must develop robust capabilities across people, processes and technologies. Three critical areas stand out:

Service Planning and Execution: OEMs can enhance service efficiency by leveraging their unique product knowledge. This includes utilizing digital twins—virtual replicas of physical equipment—to improve service scheduling (enabling predictive maintenance, for example) and to identify upselling opportunities. Digital twins can also feed configuration-specific documentation and interactive work instructions, enabling technicians to perform tasks more efficiently while minimizing errors.
Designing for Serviceability: As OEMs take ownership of the service process, designing equipment with ease of maintenance in mind becomes essential. To that end, a digital twin also facilitates continuous feedback loops between design, manufacturing and service teams to continuously improve product performance and serviceability.
Scalable Service Networks: While building an extensive in-house service network may be challenging due to resource constraints or talent shortages, OEMs can outsource execution to third-party providers while maintaining accountability for quality outcomes. This hybrid approach ensures flexibility without compromising service standards.

Supporting the transition to heavy equipment servitization

A growing trend in the heavy equipment industry is “servitization,” or offering Products as a Service (PaaS). In this model, OEMs retain ownership of the equipment and provide contracted outcomes—such as uptime guarantees—through comprehensive maintenance services. While PaaS generates high margin recurring revenue and enhances business resilience, it also increases operational complexity and risk for manufacturers.

To succeed with PaaS, OEMs must achieve operational efficiency in service delivery while balancing maintenance costs against contracted outcomes. Predictive maintenance powered by connected assets is crucial for optimizing servicing schedules without over-maintaining or under-maintaining equipment. Additionally, residual value considerations require precise control over servicing processes to ensure long-term profitability.

Digital planning enhances commercial offerings

Effective service planning is key to creating competitive commercial offerings that benefit both OEMs and customers. By connecting assets through IoT technologies and leveraging digital twins, manufacturers can monitor equipment performance in real time and implement predictive maintenance strategies that minimize downtime and optimize costs.

Moreover, integrating Product Lifecycle Management (PLM) systems with Customer Relationship Management (CRM) tools allows OEMs to tailor offerings based on customer-specific needs.

For example:

Sales teams can use PLM data to recommend upgrades or add-ons aligned with customers’ equipment configurations.
Service technicians equipped with relevant information can act as trusted advisors to customers, driving additional revenue opportunities directly from the field.

This interconnected approach ensures seamless collaboration across sales, engineering and service teams while enhancing customer satisfaction through personalized solutions.

Future trends in heavy equipment service lifecycle management

Looking ahead, two transformative technologies are poised to reshape heavy equipment service lifecycle management.

AI Agents: Generative AI-powered agents will extend workforce capabilities by assisting with tasks such as creating service plans, supporting field technicians with digital twin updates and providing 24/7 virtual support for customers. These AI agents will enable manufacturers to scale their operations efficiently while reducing reliance on human resources in certain areas.
Remote Connectivity: Advances in connectivity technologies like Starlink satellite internet and 5G networks will overcome challenges associated with servicing equipment in remote locations. Reliable data transfer will enable continuous monitoring of connected assets regardless of geographic constraints—a game-changer for predictive maintenance strategies.

As these innovations mature, OEMs that invest in AI-driven tools and connectivity infrastructure will gain a competitive edge by delivering faster, smarter services to their customers while optimizing operational costs.

Resilient profit centers

Heavy equipment service lifecycle management represents a critical growth opportunity for heavy equipment manufacturers facing margin pressures and evolving customer expectations. By adopting strategies such as heavy equipment servitization, leveraging digital twins for predictive maintenance, integrating PLM systems with CRM tools and embracing emerging technologies like AI agents and IoT connectivity, OEMs can transform their aftermarket businesses into resilient profit centers.

The future of heavy equipment service lifecycle management lies in innovation—both technological and operational—and those who invest today will be well-positioned to lead the industry tomorrow. Listen to the podcast above to hear more details about this innovative approach.

About the speakers

Dominique Gilles has over 25 years of experience in the enterprise software business. Prior to joining Siemens in 2024, he has been covering various management and business development roles with Salesforce, one of Siemens’ strategic partners to accelerate servitization and drive manufacturing profitability. Today, Dominique is Global Business Lead for Siemens Service Lifecycle Management solutions.

Chad Jackson is the Chief Analyst and CEO of Lifecycle Insights. He leads the company’s research and thought leadership programs, attends and speaks at industry events, and reviews emerging technology solutions. Chad’s thirty-year career has focused on improving executives’ ability to reap value from technology-led engineering initiatives during the industry’s transition to smart, connected products.