Transforming Manufacturing: Navigating the Servitization Journey
Many manufacturers recognise the value of shifting from product sales to service-based revenue, but fewer know how to make the transition. This article introduces the four stages of servitization maturity and the technologies that enable each step.
Traditional manufacturing is under strain: saturated markets, rapid technological change, rising customer expectations, and stricter sustainability rules have made unit sales less reliable. Service-led models offer a more resilient alternative, strengthening customer relationships and generating predictable recurring revenue.
Servitization turns one-off sales into long-term service contracts. Instead of selling equipment, manufacturers deliver outcomes — taking responsibility for performance, maintenance, and optimisation over time.
Once limited to large enterprises, servitization is now accessible to mid-sized manufacturers, thanks to affordable IoT, AI, and cloud platforms. Success, however, depends on deliberate planning and a clear understanding of your organisation’s current maturity level.
Servitization Maturity Model
Every company’s servitization path looks different, shaped by its products, processes, and business model. Yet successful transformations tend to follow the same underlying patterns. At a high level, the shift from product sales to service-driven value can be mapped across four stages of maturity.
Stage 1: Product Manufacturer
Most manufacturers begin — and many still operate — in this stage. The model is simple: build equipment, sell it, and move on to the next order. Revenue depends on production volume and cost efficiency, and customer relationships typically end after the sale, except for occasional repairs or the need for spare parts.
At this point, products function as standalone units with no built-in connectivity. Manufacturers focus on mechanical improvements rather than cloud integration or customer data. Performance insights are limited to basic reactive metrics such as MTTF and MTBF.
While this model worked for decades, it no longer aligns with today’s market realities. As a result, many traditional manufacturers are beginning their transition.
One example is Carrier Global Corporation, a long-established manufacturer of HVAC products. In 2022–2023, the company began adding IoT sensors and connectivity to its commercial systems and introduced the i-Vu connected building platform. This enabled remote monitoring, predictive maintenance, and energy-performance guarantees — significantly strengthening customer loyalty and marking the start of Carrier’s servitization journey.
Stage 2: Value-Added Manufacturer
The first real shift toward servitization is a change in mindset: companies begin viewing themselves not just as equipment producers, but as service providers. They start layering services on top of their products, typically through extended warranties, service plans, and scheduled maintenance — keeping customer engagement alive long after the initial sale.
At this stage, manufacturers also begin to build basic IT service capabilities and collect simple operational data. However, the technology stack is still limited and cannot yet support predictive maintenance or advanced analytics.
Maintenance becomes a recurring-revenue opportunity rather than a reactive obligation, encouraging companies to expand and refine their service offerings as they move toward higher maturity.
A well-known example is Cadillac’s Book program, which offered customers access to any Cadillac model for a monthly fee. The subscription bundled insurance, maintenance, and registration, and allowed up to 18 vehicle swaps per year. More than 7,000 people joined the waitlist, demonstrating the strong customer loyalty generated by integrated service experiences, rather than occasional big-ticket purchases.
Stage 3: Full-Service Provider
At this stage, companies use connected devices, IoT sensors, and data analytics to deliver predictive services rather than reactive ones. Equipment issues are identified before failures occur, making maintenance faster, more reliable, and more cost-efficient.
Technology becomes the core of operations. IoT sensors stream real-time performance data, while cloud analytics platforms interpret this data to detect patterns, forecast failures, and optimize equipment remotely. Full-service providers develop robust data science capabilities and implement advanced monitoring systems that continuously track asset health, establishing a feedback loop for ongoing product improvement.
With this level of reliability, manufacturers can offer uptime guarantees and outcome-based service models. A clear example is Siemens Healthineers, which provides hospitals and clinics access to advanced medical equipment through subscription or pay-per-use arrangements. Healthcare providers receive up-to-date imaging and diagnostic systems, while Siemens Healthineers oversees maintenance, upgrades, and performance optimization. Their cloud-based monitoring platform tracks device conditions in real time, analyzes operational data, and automatically triggers service interventions when needed.
Stage 4: Servitization Leader
At this stage, companies fully reinvent their value proposition. Instead of selling equipment, they deliver outcomes and operate within connected ecosystems. Customers pay for usage or guaranteed performance, and revenue is tied to measurable results rather than product volume.
This level of maturity is enabled by a comprehensive manufacturing IT ecosystem that integrates suppliers, technologies, and service operations. Servitization leaders rely on AI-driven optimization, predictive analytics, and autonomous systems capable of self-diagnosis and continuous improvement. Digital twins replicate customer environments, allowing manufacturers to optimize system-wide performance, identify bottlenecks, and resolve issues before they impact operations.
Rolls-Royce’s TotalCare program is a leading example. Airlines pay based on engine flying hours, while Rolls-Royce uses IoT-enabled sensors to monitor engine health, durability, and reliability. Data-driven insights allow the company to optimize maintenance timing — extending engine life by roughly 25% between overhauls. The model has proven its value; for instance, Saudia Airlines recently extended its TotalCare agreement through 2030.
In the next article, we’ll explore why and how companies should approach servitization step by step.
About the author
This article was written by Natalya Zheltukhina, Partner Network Manager at Sigma Software Group, DACH Region. Natalya is responsible for growing Sigma Software Group’s business on the DACH market, with a dedicated focus on the Automotive, Logistics, and Industrial Manufacturing Sectors.