Unlocking 40% revenue growth: McKinsey’s framework for aftermarket services
What is McKinsey’s aftermarket services framework? Core concepts and principles
Manufacturers of industrial machinery have long focused primarily on designing, building, and selling new equipment. However, aftermarket services represent a substantial untapped opportunity. McKinsey’s framework for aftermarket services offers machine builders a structured approach to capitalize on this potential by developing comprehensive service offerings beyond the initial equipment sale.
At its core, the framework identifies three maturity levels for aftermarket service providers: basic parts suppliers, value-added service providers, and performance solution partners. Each level represents increasing service sophistication and customer value. The basic level includes spare parts provision and break-fix repairs, while advanced levels incorporate preventive maintenance, performance optimization, and outcome-based service models that guarantee specific production results.
| Maturity Level | Service Offerings | Value Proposition |
|---|---|---|
| Basic Parts Supplier | Spare parts, reactive repairs | Equipment functionality |
| Value-Added Provider | Preventive maintenance, retrofits, training | Equipment reliability and efficiency |
| Performance Solution Partner | Predictive maintenance, performance guarantees, outcome-based contracts | Production optimization and business outcomes |
Why aftermarket services can drive 40% revenue growth: The economic opportunity
The economic case for developing aftermarket services is compelling. According to McKinsey’s research, industrial equipment manufacturers can achieve up to 40% revenue growth by optimizing their aftermarket operations. More importantly, aftermarket services typically generate profit margins 2-10 times higher than new equipment sales, creating significant financial incentives for machine builders to expand these offerings.
What makes aftermarket services particularly valuable is their stability. While new equipment sales often fluctuate with economic cycles, maintenance and service needs remain relatively constant, providing consistent revenue streams even during downturns. For every percentage point of service growth over product sales, McKinsey notes a corresponding 50% increase in enterprise value—highlighting the outsized impact of aftermarket operations on company valuation.
For machine builders, a well-executed aftermarket strategy transforms the traditional build-and-sell model into an ongoing customer partnership that generates recurring revenue throughout the equipment’s lifecycle—often spanning decades.
How to implement the McKinsey framework: A step-by-step approach
Implementing a comprehensive aftermarket services strategy requires a systematic approach. The first critical step is developing detailed visibility into your installed base—knowing exactly what machines are deployed, where they operate, their configurations, component details, and maintenance histories. This foundational knowledge enables all subsequent service activities and business model innovations.
Next, machine builders must segment their customer base according to service needs and potential value. Different industries, company sizes, and equipment applications require tailored service offerings. Once segmentation is complete, develop a progressive service portfolio that aligns with each segment’s requirements—from basic maintenance packages to advanced outcome-based services.
| Implementation Step | Key Activities | Expected Outcomes |
|---|---|---|
| Installed base mapping | Document all machines, configurations, and component details | Complete visibility of service opportunities |
| Customer segmentation | Group customers by industry, needs, and value potential | Targeted service offerings |
| Service portfolio development | Create tiered service packages with clear value propositions | Progressive revenue opportunities |
| Digital capabilities integration | Implement connectivity, data analytics, and service platforms | Operational efficiency and new service models |
Overcoming aftermarket service transformation challenges: Solutions for machine builders
Machine builders often encounter significant obstacles when transforming their aftermarket operations. One common challenge is the transition from a product-centric to a service-oriented organizational mindset. This requires cultural change and new incentive structures that reward service excellence rather than focusing exclusively on new equipment sales.
Another frequent challenge is developing the digital infrastructure necessary for modern aftermarket services. Many OEMs struggle with suboptimal service processes and limited access to machine data, especially when end customers restrict connectivity. Solutions include implementing purpose-built aftermarket service software—like specialized CRM systems for machine builders—that can manage the installed base, streamline maintenance operations, and facilitate data collection without requiring expensive custom development.
How can machine builders address these challenges? By starting with quick wins that demonstrate value and build momentum. Begin with better spare parts management and preventive maintenance scheduling before advancing to more sophisticated predictive services requiring extensive digital capabilities.
The future of aftermarket services: Digital transformation and advanced service models
The future of aftermarket services is being shaped by accelerating digital transformation. IoT connectivity, advanced analytics, and AI are enabling predictive maintenance models that identify potential failures before they occur—dramatically reducing downtime and maintenance costs. Progressive machine builders are leveraging these technologies to shift from selling equipment to selling guaranteed production outcomes.
Beyond predictive maintenance, innovative OEMs are creating new revenue streams through data-driven services. By analyzing machine performance data across their installed base, they can offer benchmarking services, process optimization, and even performance guarantees. Some are exploring subscription-based “Machine-as-a-Service” models that align provider incentives perfectly with customer success.
These advanced service models require sophisticated data management systems that can collect machine data locally, analyze it for anomalies, and securely transfer relevant information for further analysis when needed. As connectivity and analytics capabilities continue advancing, the line between equipment provider and production partner will increasingly blur, creating new opportunities for machine builders who effectively leverage their aftermarket potential.
