Challenges to business-as-usual
A wide range of data and analytic capabilities from spreadsheets to simulations are used as part of well-defined processes to inform both investment and design decisions in transport programmes large and small. These capabilities have established themselves as business-as-usual across regional and national government and the consultant ecosystem, delivering substantial value nationwide.
However, a combination of factors is challenging business-as-usual.
Data: Building on traditional sources, the volume and complexity of transport related data is increasing exponentially, from connected vehicles, connected devices, live-streaming sensors, satellites and more. These data are not only voluminous, but they exist in many different formats and systems and are often stored in highly disconnected, sometimes proprietary silos. Attempting to translate these data into actionable insights requires teams to spend in excess of 60% (conservative estimate) of their time securely sourcing and preparing data for subsequent analysis.
Transport in a System: The context within which the case for investment exists and that must be considered during design is becoming more complex and interdependent. The demands of an ever more extreme climate, the drive to decarbonise and the availability of energy to support the rise of electric vehicles, the interaction across transport modes and promotion of active travel, emissions reduction and public health improvements, accessibility and fair regeneration, nature recovery and biodiversity net gain – these are just some of the factors that are playing an increasingly important role. Those preparing the business case or undertaking design must consider transport as part of this wide, and widening, system of policies within which it exists. However, like data, in business-as-usual, analysis tends to be siloed within individual functions and largely the domain of experts or third party consultants, making it expensive and time consuming to construct even a limited system level perspective.
Rapid Technology Change and a Skills Gap: The pace of technological change has arguably never been faster and the transport profession is impacted like all others. While AI may be being hyped as the answer to almost everything, the reality is it is here to stay and will transform many of the processes and practices that underpin transport programme analytics. However, just last year, the National Skills Academy for Rail (NSAR) produced a report for the Department for Transport (DfT) entitled “Transport Sector Future Skills Assessment” that identified Data Analytics and AI as a critical skills shortage that will be facing the transport profession by 2030.
The key imperatives
To address these challenges, it is imperative that the transport sector transforms if it is to drive down programme cost, increase productivity and ultimately deliver better, more holistic societal outcomes. While there are many areas of potential improvement, in context of data and analytics it must leverage cutting edge capabilities that are able to:
- Automatically and securely connect the masses of disconnected data, relieving teams of a large proportion of the manual tasks they perform, unlocking capacity and increasing productivity to evaluate exponentially more potential solutions.
- Integrate domain specific analytics into a systems view of place so transport programmes can be assessed for strategic or tactical purposes in context of complex interdependent policies – for example transport asset exposure to future climate risks for maintenance optimisation or road network interventions in context of housing regeneration investment.
- Democratise and make accessible the analytic technologies by lowering the skills barrier to entry and putting decision intelligence capabilities in the hands of those who need them – from policy maker to the general public. Advances in AI and large language models are maturing to enable this without compromising the role or guiding hand of the expert.
Can this be done?
Technologically this can be achieved and SimAnalytica’s software solutions are at the forefront of driving this transformation. Working with West Yorkshire Combined Authority and funded by Innovate UK’s Net Zero Data Exchange Program, our application was able to bring together disconnected data and analytics from across five functional transport teams and identify over £5M worth of public transport performance improvements. This work was Highly Commended in Prolific North’s Tech for Good awards. In a Department for Transport funded Transport Research and Innovation Board use case, traffic simulations were integrated with flood predictions to rapidly identify accessibility to vulnerable people, places and assets in a high dynamic event. Our team is now working on AI based assistants and large language model based queries to automate analytic process and the standard report generation process so a wide range of stakeholders can access, interact and collaborate with the insights they need for their purposes.
However, technology is just one piece of the jigsaw. Collectively we must continue to collaborate to demonstrate value through real world applications to overcome the organisational culture and process change resistance at the pace it needs to happen if we are to meet the biggest challenges transport infrastructure is being developed to address.
Learn more
You can learn more about SimAnalytica’s pioneering work on our website www.SimAnalytica.com or by following us on LinkedIn at www.linkedin.com/company/simanalytica.
Register here for our webinar (live or watch the recording), joint with Ordnance Survey on the topic of Transforming Transport From Planning to Operations with Cutting Edge Data Science and AI.
Robert Harwood is Chief Executive Officer at SimAnalytica
Feature Image Source: Jcomp on Freepik