Transport and Mobility

Better return on investment thanks to digital consulting

RhB Innotren

  • The RhB Rail Service Call Centre will now also handle enquiries about the Glacier Express 

  • The Zühlke analysis shows that the optimisation potential lies in inefficient processes 

  • With simple measures the complexity of the system landscape is reduced and sub-processes are automated 

RhB wants to free up resources in its Railservice call centre with the introduction of a chatbot. Zühlke validates the project and checks the business case, thus maximising the ROI for RhB.

Freeing up RhB call centre resources by chatbot

The Railservice call centre of RhB is now to also handle requests for the Glacier Express. The company plans to cover the expected additional work with the existing team. To reduce employees’ workload and increase efficiency, a chatbot is to be introduced. At the same time, RhB wishes to look at the establishment of innovation labs. Zühlke is commissioned to demonstrate this cooperation model to RhB, check the technical feasibility of the chatbot solution, validate the economic benefits of the idea, and implement a prototype. 

The right decision thanks to an interdisciplinary team

An innovation team consisting of RhB and Zühlke specialists from the fields of Customer Experience, Data Science and Business Consulting takes a close look at the chatbot project. A contextual inquiry in the call centre, the analysis of the quality of data gained from customer inquiries as well as the evaluation of the potential cost and benefit effects make clear: a chatbot would only be able to answer a fraction of the inquiries. The investment is therefore not worthwhile at the current stage. 

Michael Kästler Rhätische Bahn
' We highly appreciated Zühlke’s recommendation not to implement the chatbot technology in the proposed business case. This saved us money. '
Michael Kistler
Head of Marketing, Communication and E-Business

Tackling the problem at source

Zühlke’s analysis reveals that the greatest optimisation potential lies in the inefficient processes. With simple measures, it is possible to reduce the complexity of the system landscape and automate sub-processes. This improves the structure of the data, making it possible to introduce a chatbot in a next step. An innovation workshop based on Design Thinking Methodology, which Zühlke conducts in tandem with RhB, opens up further areas of application for the chatbot.