2025: Rethinking transport data for real-world impact
1. Introduction
This roundtable brought together voices from across the transport data space—consultants, local authorities, policy experts, and tech innovators—to talk candidly about where we are, where we’re stuck, and where we could go next. The focus was clear: how can we better use data to understand how people travel, what they need, and what will help them make more sustainable choices?
2. Core Themes from the Discussion
2.1 Passenger Insight: Beyond the Numbers
It’s not just about how many people travel or when, the why matters too. There’s growing recognition that understanding behaviour, attitudes, and perceptions is just as important as having hard stats. People don’t travel in neat segments or for a single reason. To plan better, we need to see the full picture: end-to-end journeys, context across a whole day, and the personal motivations behind travel choices.
2.2 Smarter, Joined-Up Data
Traditional datasets aren’t cutting it. Participants stressed the need for richer, more diverse data, and better ways to stitch it all together. That might mean crowd-sourced inputs, lightweight qualitative research, or tapping into everyday tools like Google Maps. Integrating different sources is key, and contactless data is seen as a big opportunity.
2.3 The Standards Problem
One major blocker is the lack of standardisation. Data is often locked away in silos, formatted differently, or not easily shareable across organisations. Without a shared approach, it's tough to compare, combine, or scale up insights. There’s appetite for change, but we need better frameworks, shared infrastructure, and a user-driven approach to how data gets collected and used.
2.4 Turning Data into Strategy
It’s not enough to collect data; we need to do something with it. The group discussed the importance of linking data to tangible outcomes: making the case for investment, designing better schemes, and encouraging modal shift. Insights matter more than raw detail, and there’s still a widespread lack of understanding about the value that data can unlock.
2.5 Filling the Gaps: Who Are We Missing?
A recurring concern was the gaps in current data, especially when it comes to underrepresented groups like children, older people, or those with specific needs. If we’re going to build an inclusive transport system, we need to understand the barriers different groups face. That calls for better segmentation, more thoughtful design of data tools, and asking the right questions from the start.
2.6 Motivating Change Through Knowledge
People are more likely to change their travel behaviour if they understand their options and feel informed. That means feeding insights back to users, not just collecting data from them. Different audiences need different formats, and there’s a clear need to make information more transparent, practical, and empowering.
2.7 Cultural and Organisational Shifts
A lot of the issues come down to culture. Internally, many organisations are still fragmented, with poor communication and no clear data strategy. Externally, there’s hesitation to share data; whether due to commercial concerns or a lack of clarity about who’s responsible. Building a healthier ecosystem means encouraging collaboration, being clear about roles, and backing innovation.
2.8 Making the Business Case
It’s widely accepted that transport data has value; but turning that value into funding remains a challenge. The cost of collecting, processing and analysing data is significant. Who pays? How do we prove the return? There’s a strong sense that we need clearer business cases that link data use to real-world benefits.
3. Where Do We Go From Here?
The group highlighted several practical opportunities:
Establish clearer standards and frameworks to enable data sharing.
Use AI and LLMs to simplify access to large or complex datasets.
Create stronger foundations internally, better training, better knowledge-sharing.
Focus on outcomes, not just outputs; what’s the question we’re trying to answer?
Bring in ideas from outside the sector - especially SMEs and innovators.
4. Final Thoughts
There’s no shortage of data in transport. What’s missing is the clarity, collaboration, and confidence to use it well. This roundtable made it clear that we’re at a turning point. If we can shift the culture, break down silos, and stay focused on real-world outcomes, there’s huge potential to deliver smarter, more inclusive transport systems.
Notes:
This session explored how personal mobility data is transforming urban transport and improving user experience. Participants delved into innovations, challenges, and opportunities in data-driven transport optimisation.
Discussion:
The role of personal mobility data in optimising public transport
How data-driven insights are improving the passenger experience.
Challenges in data collection, integration, and utilisation.
Case studies of successful implementation in urban transport.
How data can improve intermodal interchanges between bus, tram, train, and active travel modes.
Key themes:
Passenger perceptions, attitudes, behaviour – this type of data of growing interest
Meet policy, motivate change
Role for us as consultants to work with data to easily unveil insights and evidence
Explore new methods
Need for richer data or combine data sources (crowd sourced)
The why is becoming important - not just quantitative data
End to end journeys of interest
Reaching different groups of people - delivering data as well as collecting it
Lack of standards a challenge
Insights are key for clients
There is a lack of understanding of the value of data
Interchange Round Table:
How do people want to travel, what are the barriers to using data, who needs to use it
Huge volumes generated, how to harness this
Link data to strategy e.g. modal shift
Need data for business case to spend public money
Currently doesn’t go far or deep enough – move away from traditional data
Use of data at beginning of strategy
Contactless data an opportunity
Need a fully integrated view of journeys from OD
Behaviour across a whole day
Integrate data sources
Why are people travelling
Tension between personal characteristics and anonymity (challenge)
Leads to generalisation
Data is generated e.g. Google maps but people are hesitant to share it
Nudge behaviour without making it commercial
Gaps in representation
Children, older people
Putting the pieces together to capture more groups
People sharing data without realising
Commercial operators don't like to share their data
Acknowledgement that collaboration is key
Give people information back for their travel benefit
Knowledge is power
How to motivate people to make a change
Lack of knowledge about benefits
Need to share info so people can react
Not just about collecting data, but making it available
Different people require it in a different way – how to convert this into insights
Lack of standardised data across companies a challenge
Not comparable
What's the balance
How different groups interact with transport, their barriers
Lightweight qual data is very powerful
More info should be provided to users – multimodal agnostic
Different questions for different areas with their own demographics
Important to understand private transport too and why that's being used
Need a standardised way of understanding context of LAs, what’s happening
Greater reliance on crowd sourced data e.g. Waze, Facebook
Cost and effort of processing large volumes of data
Who foots the bill?
We know there is value in this data. It's about the business case
Where is the money being spent
Insights v detail – balance
User segments useful for this
Access to data a challenge for LAs
What data do clients actually need? Varies by e.g. public v private sector
Data is scattered and siloed
Benefit of data is not well understood
Data users should drive how data is collected and processed
Data exists, hard to break down silos
What questions do we want to answer
Breaking Down Data Barriers:
ODI - Data Spectrum
Shared, interoperable data in the middle
Data required for growth
Transport is way behind
Tangible outcomes – delivering more for less, choosing schemes with the most impact
Culture and ecosystem is the challenge
Power of LLMs - make data more accessible
Lack of strategy in some places
So many datasets, how do we bring them together to get benefit
Who is the responsible body
Don't understand the value of data
Lack of internal collaboration and communication
Outcomes and use cases
Choice – genuine choice hasn’t been grasped
WHY and HOW do people want to travel
Exists but for different purposes – surveys at end of trips
Who's got what? What insights can you share? etc
What are the problems?
Look outside the transport sector
Innovators, SME
Solid data foundations
Need use case and people who are interested in the outcomes
Problem of internal knowledge
Not yet data but should be data