Where traditional methods fail, use local data to prove project viability

Alternative modelling tools can highlight the best investment opportunities, says Mott MacDonald's Paul Hammond.

Traditional cost-benefit analyses provide a macro (national) level view of project spend against returns on investment. But they are poor at considering the impacts of a new scheme at the micro (local) level, meaning many worthy projects fail to receive political backing or funding. 

We developed the transparent economic assessment model (TEAM) which highlights the local economic impacts of a scheme, such as job creation, access to housing, education, healthcare and resultant improvements in local value, salaries, and gross value added (GVA) to the local economy. Although these factors are normally mentioned in the business case for a new project, quantifying them via an independent modelling tool can persuade investors of the value of the new scheme. The model is compliant with the UK Government’s Green Book on appraising proposals and follows government and industry best practice guidance. 

TEAM has led to a number of projects receiving local backing and investment which would otherwise have been withheld. These include a project to develop the Norwich Northern Distributor Road and Postwick Hub A47 junction. Although this project initially returned a negative cost-benefit ratio, the local economic benefits identified through TEAM included the creation of 5230 net additional jobs, £1bn net additional GVA spread over 30 years and £966M in associated investments.

How it works

TEAM is an Excel-based modelling tool. It is linked to local datasets from sources such as the Office for National Statistics (ONS) detailing local economic structure, salaries, demography and travel behaviour. These datasets can be overridden if more accurate information for the area is available.

And by incorporating ecosystems data and assigning financial values to ecosystems and natural services the economic impact of a project on the environment can also be quantified. 

Advantages of a digital model

-Bypass primary research: All local and national datasets housed in the model are taken directly from ONS, reducing the need for primary research.

-Compare model outputs: TEAM enables different project options to be systematically and consistently compared.

-Understand where the results come from: The datasets and methodology behind TEAM are open-source. This helps clients to evaluate projections made by the system and to understand the processes behind them (in contrast to other economic tools).

-Model theoretical scenarios: TEAM can be updated with alternative basic data to visualise the economic effects of new projects under different conditions. This is useful for modelling future scenarios, taking into account population changes or new adjacent developments.

-Model with ‘live’ data: Models can be linked to adjacent digitised data sources, allowing it to take account of real time changes, such as currency fluctuations, for up-to-the-minute projections.

Local and regional success stories

So far, TEAM has supported the development of more than 50 projects in the UK. Doncaster Council and Sheffield City Region partners bid for £30M of investment to establish the High Speed Rail College, a new further and higher education facility to develop skills for the development of High Speed 2. Using TEAM, we found that after 15 cohorts have graduated we can expect £150M a year of extra GVA to the Sheffield City region. The economic case for extending high speed rail services from London St Pancras to Hastings and Bexhill was also highlighted by TEAM, showing that the investment in the service would lead to an additional 629 jobs and £350M of GVA over the next 30 years.

TEAM has also provided the business case for important climate resilience schemes by assessing the effect that flood mitigation and alleviation work would have on economic activity in Lowestoft, Great Yarmouth, Huddersfield and Hull.

Clients in Canada, Australia, South Africa and the USA have expressed interest in developing bespoke versions of TEAM for their markets, while in New South Wales and California, the model has been calibrated using local, regional and national datasets in order to apply the intelligence to infrastructure investment. 

The success of TEAM shows there is an urgent need for alternative models to assess wider economic benefits of development work and to support planning decisions worldwide where traditional cost-benefit analyses fail to highlight local benefits.

Paul Hammond is head of economic social development, Integrated Transport Division, Mott MacDonald