How Data Can Help You Optimize Your Aftersales Revenue
Many machine manufacturers are currently contending with falling demand, cost pressures, and tough competition. At the same time, their machines generate huge volumes of data, which often go unused. This data can be used to generate revenue in aftersales & service. Our blog article shows you how this can work in practice.
The skills shortage, a weak economic climate, and rising costs are posing challenges for machine manufacturers. “Without new business models, the sector is at risk of sustaining a permanent loss in competitiveness,” warned management consulting firm PwC in its German Manufacturing Barometer in October 2025. This turns the focus on an area that many companies have identified but are not yet taking advantage of: the use and monetization of their data.
Manufacturers can collect and analyze relevant operating data from their machines. This enables them to create new business models and services for customers, for example an application that can be used to plan maintenance efficiently. If this kind of data creates real added value, customers will be willing to pay for it.
In this blog article, we take a closer look at the subject of monetizing data in aftersales & service. You will learn:
- Why it makes sense for machine and plant manufacturers to monetize their data.
- The obstacles that are still keeping many companies from opting for digital and data-based services.
- How predictive maintenance demonstrably boosts revenues.
- The advantages that data monetization offers in aftersales and service.
- The tools that can assist you with the implementation.
Why machine and plant manufacturers should monetize their data now
Set yourselves apart from the competition
Regardless of the sector a company operates in, it needs to act in a data-driven way if it wants to be competitive. It’s no longer enough to impress with products alone, but many companies direct their efforts primarily at the sales of a system or machine. This is their opportunity to set themselves apart from the competition.
Generate recurring revenue
Data can be used to develop targeted aftersales services that help to stabilize revenues. This is particularly important during periods when sales of machines are fluctuating.
Leverage technology
The technology is always developing. Machines are equipped with sensors and networked; their status is monitored 24/7. Wouldn’t it be a waste not to use all this machine data for new business ideas?
Increase customer satisfaction
Machine and plant manufacturers can improve the customer experience with digitalized service and innovative business models. Customers will be favorably impressed by first-class, efficient and smooth service.
Avoid the risks resulting from inaction
Companies that fail to take on the challenge of digitalization run the risk of shortcomings in service:
- It takes longer for service staff to find the information they need
- High service costs with low margins
- Stagnating spare parts sales as a result of outdated information or incorrect orders owing to missing data
- Extra visits made by service technicians for the same job – leading to high travel costs and resources being tied up
- Low first time fix rate and falling customer satisfaction
There is therefore a need to use data as a basis for services in aftersales & service. But there are still a few obstacles blocking the way, as we will see in the next section.
Five reasons data is not being monetized in the mechanical engineering sector
Many manufacturers in the field of machinery and plant construction are not yet taking advantage of the significant revenue potential in aftersales & service. There are many reasons for this:
- Lack of know-how: There is a lack of experts analyzing data and developing effective strategies.
- Rigid silo thinking: Information is dispersed across multiple departments. Data first needs to be extracted from different systems and standardized.
- Data blindness: There is no central platform where information can be found and evaluated. This creates an additional lack of transparency.
- Limited resources: Companies are put off by the costs of implementing the software or do not have the time or human resources to do so.
- Inefficient tools: Too many features, too little flexibility: even if there is software available, many companies are not taking advantage of its full potential.
These obstacles can be overcome. With the right strategy and software, it is possible to organize and analyze vast quantities of data and ultimately use this data to create new sales-boosting business models. The following example shows how this can work.
How monetizing data generates revenue – the predictive maintenance example
Predictive maintenance involves the continuous monitoring and analysis of machines and process data to predict future maintenance requirements. This allows maintenance processes to be optimized and plant availability to be increased, while at the same time making it possible to plan downtime better and more cost-effectively.
A study on predictive maintenance produced by management and technology consultancy BearingPoint in 2021 shows that predictive maintenance is a worthwhile investment. Increases of at least 10 percent in achievable sales figures are possible here. Companies using predictive maintenance have also managed to reduce their maintenance and service costs by 17 percent.
Predictive maintenance also brings benefits for plant operators: Shorter downtime represents significant cost savings. Efficient service callouts and transparent insights into the maintenance of their system components also help to improve operators’ customer experience.
New business models: using machine data to achieve stable revenue
If machine and plant builders want to make money with data, they need to turn it into a service offering that customers can use for a fee.
More and more companies are using subscription models where customers “subscribe” to a service to monetize data. Another option is the Equipment as a Service (EaaS) model.
Under this model, plant and machinery users will no longer buy just a product in the future, but a full service package that guarantees them maximum uptime in the operation of their system. Manufacturers are thus increasingly becoming operators themselves – they no longer sell their machines and systems, but the output that can be achieved with them.
Digital spare parts catalogs offer a much easier entry into the monetization of data: they boost the spare parts business based on data and help machine and plant manufacturers to increase their sales in the aftermarket.
Five advantages of digital knowledge management and digitalization in aftersales & service
Advantage 1: Clear data reduces your costs
Predictive maintenance is just one example as there are many other business models in “Service 4.0”. For instance, a spare parts shop and the digitalization of spare part catalogs can lead to significant revenue increases. Spare parts catalogs can be created quickly and easily. The search for the right part, convenient ordering around the clock, and user-friendly and reliable order processing are sales drivers in the spare parts business.
Advantage 2: Data increases your first time fix rate
If there is plenty of data available on customers and their orders, this means field service employees will have access at all times to the key, up-to-date information needed to complete a job. This helps to optimize the planning, execution, and documentation of service orders. Combining a field service management (FSM) software package and a digital spare parts catalog boosts efficiency in service. This also improves the all-important first time fix rate and ensures customer satisfaction.
Advantage 3: Data overview improves the customer experience
Centralized and up-to-date data enables manufacturers to identify their customers’ pain points. Usage data also enables them to learn more about their own machines and systems.
Advantage 4: Data-based business models are future-proof
Modern software for data analysis and use can be connected to other tools in the company. This networking helps manufacturers react more quickly to trends and technological developments. For instance, this networking facilitates remote services, digital simulations, and a digital information twin. This enables service technicians to work even more efficiently.
Advantage 5: Data analysis in aftersales helps your customers
The Predictive Maintenance Study 2021 clearly showed that customers who proactively monitor and maintain their machines reduce downtime by 18 percent. This represents a huge advantage as downtime is costly. According to a report by Senseye, unscheduled stoppages result in 25 hours of downtime per month at manufacturing firms. Data can help here and reduce financial losses.
Conclusion: Make use of your data!
With digitalization, machine and plant manufacturers are now in a position to offer new business models in aftersales & service that are based on their data assets. This enables them to not only boost customer satisfaction but also to create new revenue opportunities. Predictive maintenance and digital spare parts catalogs are two examples showing the success of this approach.
With the right platform, you can collate your data in a central location and create real added value. Quanos has created InfoTwin for this purpose, a cloud-based solution that automatically links spare parts management, technical documentation, and data from other sources. Discover the advantages of our future-proof software now or arrange a 1:1 appointment to speak with our experts!
