Digital business models - how your entire company benefits from after-sales data

What data is generated in everyday after-sales work?

Customer queries, service calls, warranty claims, orders for spare parts, and the daily operation of machines and systems - all these touchpoints provide important data for after-sales service staff.

Manufacturers should not see this as a waste of disk space or cloud storage. Instead, they should look closely and learn from their machinery and equipment data and customer feedback.

The following overview provides examples of after-sales data and its potential uses:

• A machine sold provides operational data. This gives manufacturers insight into the performance of the machine and how the customer uses it on a daily basis. Optimization recommendations for usage can be derived from this. The information also helps manufacturers to improve their own products and services.
• The service hotline and service technicians are in direct contact with customers. The conversations provide important data on customer satisfaction and on what information operators are missing, where problems lie in machine use, or which parts need to be serviced or replaced particularly frequently.
• Customers or service technicians order spare parts and produce order data in the process. If this frequently results in incorrect orders, the spare parts business must be optimized. One solution, for example, is a digital spare parts catalog that always provides up-to-date information on spare parts.

How do other areas of the company benefit from after-sales data?

The art of dealing with after-sales data lies in deriving relevant insights from the growing volumes of data and translating them into measures. However, these measures are not limited to after-sales service alone:

• After-sales data offers great added value for marketing and sales. They provide important insights for advertising messages that strike a chord with customers. The data is also a perfect basis for optimizing sales strategies and developing new services that offer customers real added value.
• Order data for spare parts provides information on how attractive the pricing of spare parts is. If it is clear which customers order which parts for which machines, price calculations can be carried out more easily in the future.
• Order data enable forecasts and analyses of ordering behavior. They are the basis for optimizing spare parts logistics and additionally saving costs through smart and predictive inventory management.
• Service technicians gain deep insights into how machines and systems are used on site and about the problems customers encounter on a day-to-day basis. For departments such as quality management or product development, such information is worth its weight in gold.
• Technicians and engineers learn a lot about the performance of machines and systems from incidents at the customer's site and identify potential sources of error more quickly. This makes it easier to revise existing models.
• Service requests reflect customers' problems and needs unfiltered. This makes them indispensable for customer-centric offerings and services. Since a smooth customer experience must be the goal of all departments, the entire company benefits from this information.

Data that converges in After Sales can be used multiple times and improves the work of your technicians, service staff, dealers, but also the everyday life of your customers. They are the basis for new digital business models.

Examples of digital business moadels with cross-departmental data

The following cases illustrate once again in concrete terms how the multiple use of data in the company can look and how data can thereby be monetized in after-sales service.

ESTABLISHING SERVICE SALES

There is great potential for stable after-sales revenue in the sale and marketing of spare parts and services. However, in practice it is often the case that sales concentrate on primary products, which bring higher commissions compared to services.

After-sales service staff, on the other hand, are primarily concerned with solving customer problems. In contrast, they do not see selling services and passing on sales opportunities to the sales force as their job.

Data benefit: With a comprehensive and clear database, it quickly becomes apparent whether it might be worthwhile to set up a service sales force or whether the sales force should be trained to sell spare parts and services. This makes sense, for example, if customers do not have their own maintenance department or are generally happy to take advantage of additional services.

SERVICE TECHNICIANS AS "INFLUENCERS"

Data brings structure to the available information on the operation of machines and systems, on spare parts and existing maintenance contracts. All this data offers the opportunity to turn your service technicians into "influencers" for your company.

Data benefit: Service technicians are in close contact with customers and know their needs like no one else. They also have a high level of expertise and often enjoy the trust of plant operators. Their recommendations for additional services fall on open ears and, in combination with after-sales data, are accurate.

UP- AND CROSS-SELLING

Once the service technician's work is done and his mission report completed, valuable new data is generated. This can be used for up- and cross-selling activities.

Data benefit: Tailored additional services, spare parts or even new machines and components can be offered to suit a customer's individual situation.

Practical tip: From spare parts catalog to data champion

Digital spare parts catalogs are a perfect illustration of how After Sales can create new digital business models that also benefit other areas of the company. After all, the classic spare parts business is only the beginning of Service 4.0:

1. Basically, a digital spare parts catalog makes it easy to identify and sell spare parts.
2. The next step is to connect to a service information system such as Quanos SIS.one. This brings together all the service information on machines and systems that manufacturers need to digitize their after-sales service.
3. The information system lays the foundation for all further steps - for example, the use of data for applications such as predictive maintenance or remote maintenance.

The next blog articles in this series will tell you what benefits await you when you build digital business models on your after-sales data and how implementation is easy.