Personalised Service Recovery

Abstract

This thesis report represents the result of a graduation project for the master programme Strategic Product Design at the Delft University of Technology carried out in collaboration with KLM Royal Dutch Airlines. This project aims to find out how to create the desired experience for KLM passengers during undesired disruptions. This problem has been tackled with the use of the Double Diamond approach enriched with the ViP approach. KLM Royal Dutch Airlines is the flag carrier airline of the Netherlands with the ambition to become Europe’s most customer-centric, innovative and efficient network carrier. To achieve this ambition, they have to make significant steps forward. KLM decided to do this by striving for operational excellence, creating a long term sustainable growth with products that both stimulate efficiency and provide customer intimacy. At their new department, Operation Decision Support, they embraced this by becoming more data-driven by creating tools to optimize the operation of KLM.
While the airline industry is progressively optimizing and KLM is facing strong competition, there is one area that remains relatively uncharted. What happens to the passengers when disruptions occur? There are many types of disruptions, varying from individual level to operational level. Unexpected mass disruptions, often caused by bad weather, are challenging to solve and result in disastrous customer experience results. During these unexpected disruptions, the Net Promoter Score, which measures the passengers’ satisfaction and thus the loyalty for the firm drops drastically. To increase passenger satisfaction, KLM should improve their service recovery when operational disruptions occur. This can be done by giving the passenger their ‘perceived justice’ which depends on the offer they get, the procedure and the interaction. Pinpointing the needs of the passenger is unfortunately very difficult since every passenger is different: they have different mindsets and travel for different occasions. With the use of a qualitative research method; adaptive storytelling, the passenger needs are found and translated to the perceived justice framework. The presented solution offering the perceived justice to the passenger is called ’Emma’, an automated, digital, ground attendant integrated into the KLM application. She enables passengers to solve their disrupted journey by pro-actively sharing information, offering solutions and giving recommendations. This application is equipped with cognitive abilities; natural language processing, machine learning and intelligent automation to create a personal and tailor-made experience via a mobile device. The application ‘Emma’ shows the potential to increase the NPS score and therefore, the passengers’ satisfaction during operational disruptions. ‘Emma’ includes many features that enable the passenger to be in control, gives them the feeling of being taken care of and shows the responsibility of KLM by giving detailed and transparent information, giving personalised rebooking options and showing tips to spend their waiting time better. Creating an application requires the involvement and resources of third parties. This takes time, and therefore, the implementation plan is separated in two years. The first year is focussed on aligning the different teams within KLM and building the features with the available internal resources. The second year, the application will be extended and further optimised with the use of third-party resources. This will enable KLM to launch a service that will be relevant in the future and give the passengers a satisfying service recovery during unexpected operational disruptions.