National Underground Asset Register (NUAR) - Economic Case Summary

Question 1

Underground assets: the case for change

Accepted Answer

Every construction and infrastructure project must source information on buried utility assets, such as cables, pipes, sewers, ducts, when preparing ground investigation and excavation work e.g. digging. This data helps avoid costly damage to assets, and improves safety for workers and the general public.

The current process by which underground asset data is shared across the UK could be improved as it is currently fragmented and inefficient. At the moment, in preparation for works taking place, multiple organisations have to be contacted who then deliver data of varying quality: data comes in multiple formats and scales, information is on multiple base maps, has varying levels of accuracy, may be incomplete, and is collected at different frequencies. These inconsistencies make it challenging for all relevant underground asset data to be reconciled into a single plan on asset locations, increasing the risk of accidents and mean projects take longer, cause more disruption to the public, and cost more.

Fixing the issues with data sharing and quality isn’t easy, and there are no direct incentives for businesses that own and use this information to improve their data at the scale required for a full solution. For example, there is no case for businesses to individually invest in reform where many of the risks and costs will be felt by other organisations, such as other utility providers.

However, the government is able to centrally co-ordinate and invest upfront in wholescale data transformation where there is clear evidence of value to the UK economy, and it can also ensure appropriate safeguards are in place to address commercial and security concerns of efficient, digital data access. Underground asset data is one area where this is the case.

The Geospatial Commission has made an economic case for improvements in access to data on the location of underground utilities assets through a more centralised data access model, and carried out research to estimate the scale of the cost savings that could be achieved through creation of a centralised platform. A conservative estimate of the benefits of a national approach to digitalising underground asset data calculates £30 worth of benefits for every £1 invested, which is an extremely high rate of return for any government programme. This calculation has informed the creation of the National Underground Asset Register (NUAR) programme.

We are publishing the approach taken to estimate the relevant benefits in order to support other organisations that need to build an investment case for data sharing and coordination.

Question 2

Benefits calculation approach

Accepted Answer

A range of different methods have been used for the benefits calculation, to account for the complexity of estimating savings across a vast number of organisations and projects. The starting point for the analysis is a comparison of NUAR to the current system for data access, looking at how it could change processes and reduce risks.

The estimated total monetized benefit of the NUAR programme is £3.4bn, which is £347m per year over ten years. This is based on three estimated benefits:

Savings from reduced utility strikes, saving £240m/year
Reduced costs of sharing data, saving £91m/year
On-site efficiency improvements for projects, saving £16m/year

Question 3

Savings from reduced utility strikes

Accepted Answer

Many of the benefits of a more centralised approach come from reducing the number of utility strikes, where pieces of infrastructure are damaged by mistake e.g. while digging. Firstly, a literature review was used to understand the scale of potential benefits.

The review identifies the average cost of a utility strike, breaking down cost components into direct costs (for example, repairing damages) and indirect costs (such as project delays and extended road closures). The literature shows that there’s variations in costs for each utility category - for example, strikes to high voltage cables and fibre optic cables have a far higher cost than strikes to telecoms equipment. These variations in cost are used to model the average direct cost per strike, which we estimate at £3,371 per strike. The literature also estimates the indirect costs based on a series of industry case studies. Indirect costs are, on average, 29 times larger than direct costs, so this scale factor is applied to estimate the full scale of utility strike costs.

A widely reported industry statistic of 60,000 strikes per year on buried service pipes and cables per year was used as the basis of the strike reduction benefits. The economic costs of utility strikes alone are therefore estimated at £2.4bn a year. A significant challenge has been identifying what proportion of strikes could be avoided with better data. Industry incident reports (Utility Strike Avoidance Group from 2014 - 2018), categorise strikes into groups based on the cause of the incident. Those linked to inadequate plans and on-site procedures for using data made up around 30% of total incidents: this is the central estimate for the proportion which could be avoided.

Question 4

Reduced costs of data sharing and onsite efficiencies

Accepted Answer

Additional data needed to be collected to understand how a new model for data access could make working processes more efficient. The Geospatial Commission therefore commissioned a survey of those involved in different aspects of excavation to understand the time and cost of gathering data, both following ‘business-as-usual’ processes and those that will be in place once NUAR is delivered. This approach identified the actions that data users take, and showed the steps in that process that would reduce cost. The findings and data from this work were averaged and then scaled up to the whole sector. This data was also used to estimate the scale of savings from reducing the number of times unexpected underground assets were found on site and meant plans had to change. This includes assets which are not on record or on record but not in the place shown by the plans. These savings are still significant although much smaller, as only a subset of projects are delayed or abandoned for these reasons.

Question 5

Accounting for bias and uncertainty

Accepted Answer

This project used the best available credible evidence sources, and commissioned new evidence where there were gaps - but there will always be some uncertainty estimating benefits for a future programme which changes how things are done. A number of sensitivity tests were therefore carried out to understand how the benefits change under different assumptions. These show that in all of the scenarios tested, the NUAR programme represents good value for money even when the assumptions about the scale of the benefits are significantly reduced. Detailed modelling and assumptions have been published separately.

There are also other benefits of the programme which aren’t currently quantifiable, such as more strategic improvements to street works coordination and subsurface planning. There is therefore a very high level of overall confidence that the NUAR programme provides value for money, and this will be validated with a detailed evaluation plan.

The value of other potential use cases, such as using NUAR to deliver efficiencies in the planning process and new construction has not yet been quantified.

Further details are available in the ‘NUAR Economic Benefits paper’ (pdf, 341 KB).

Question 6

References in Economic Case:

Accepted Answer

Beck, A.R., Fu, G., Cohn, AG et al., 2007. A framework for utility data integration in the UK. In: Rumor, M., Coors, V. and Fendel, E.M., (eds.) Urban and Regional Data Management: UDMS 2007. 26th Urban Data Management Symposium, October 10-12, 2007, Stuttgart, Germany. Taylor and Francis , pp. 261-276. ISBN 9780415440592