THE CHALLENGE

When an item returns to the service department through an RMA process, the unit must be extensively inspected by a technician. A cost estimate is then provided to the customer for repair. This must be accepted by the customer before the repair can be carried out and the work performed for the inspection, including the repair, can also be invoiced. If the customer rejects the offer, the customer service department is left to pay for the work already done.

SOLUTIONS

The aim is to minimize the time required to check returns. We achieve this in 2 ways:

• The technician is provided with a guided repair where the AI suggests how the device is likely to need to be repaired
• The AI automatically generates the cost estimate for the repair so that the device does not have to be extensively checked in advance before the customer gives his consent to the repair

USE CASES

The following results were obtained:

• 80% probability that the AI’s top 3 repair suggestions include exactly the right one
• Less than 20% variance in the deviation from the planned invoice price to the cost estimate

OUR 4-STEP PROJECT PROCEDURE

1. Initial workshop – 1.5 days effort
2. PoC (Proof of Concept – development of a first prototypical solution to validate the solution concept) – 1 week effort
3. Complete implementation of the use cases after successful PoC – 4 weeks effort
4. The solution is delivered and integrated as a microservice – 3 days effort

Results

Thanks to the trusting and committed cooperation of both companies, we were able to jointly achieve the set target of 20% variance.The investment costs for Wöhler amount to approx. 25,000 EUR – This means that break-even is reached after about 2 to 3 months.During the course of the project, data quality was improved and the customer’s understanding of the possible uses of the existing data was significantly increased. Thus, we have created a solution that can be seen as a basis for future data-driven projects.This benefits all areas of the Wöhler Group and will enable further digital innovations in the future.