Hannover Consulting were engaged to:

• Support the development of a fair and competitive fare structure based on international benchmarking for demand model testing
• Assess the feasibility of proposed dwell time goal for Fast rail services
• Unpack and understand forecast demand datasets
• Complete Service Planning and Capacity Analysis

Our team approached the project with an evidence-based methodology, while maximising use of existing data.

This involved:

• Conducting fare benchmarking by collecting data on a broad range of services from around the world and comparing them using regression analysis to identify a fare structure that would fit the proposed service (for demand model testing only).
• Examining existing studies to identify what factors affect dwell times; comparing previously proposed methods for estimating dwell times and applying up-to-date assumptions about service attributes to evaluate dwell times in the absence of any other information.
• Developing a list of targeted recommendations to help achieve dwell time goals.
• Identifying, and advising on, the most appropriate and valuable metrics for analysing demand data. This included engaging and accessible ways to showcase that information, enabling the client to make informed decisions.

The fare benchmarking provided the client with a better understanding in their development of a  fare strategy . The dwell times analysis informed the establishment of a feasible dwell time goal for a new type of rail service. The demand data analysis enabled the client to make informed decisions about their rail service and a corresponding train concept. The outcome of Hannover’s work was successfully implementing the client’s Network Development Plan.