Since 2020, Hammersmith bridge has been closed to traffic.
The lack of data quality relating to the bridge drove the wrong decisions for inspections and maintenance. This led to decades of unchecked corrosion in the cast iron pedestals before the use of sensor technology in 2018, which identified micro-fractures causing the bridge to be at serious risk of sudden collapse.
The repair bill now stands at £140m with £9m required simply to stabilise the bridge. Its ongoing closure has negatively impacted the local economy, transport routes and is now the centre of a political dispute between the Council, Transport for London, and the Government.
This could have been avoided with a simple focus on data quality.
The bridge is an asset and, like any asset, it has data on which key decisions are made, such as a maintenance schedule and costs. For that data to be useful, the asset is broken down into “features”, in this case its suspension system and the pedestals that support that suspension system. There are also data “attributes” such as the length of the bridge, its height or other key information such as the material it is made from.
By enabling that information to be available to the right people at the right time then decisions could have been made to prevent its deterioration.
This is not an exceptional example. Many organisations do not know the full extent of their asset holdings or hold any data, let alone good quality data, relating to those assets. This stifles data-driven decision-making with spiralling costs and risk of serious safety concerns.
Envitia’s Data Quality diagnostic tool helps customers quickly and easily assess the quality of their asset data and its reliability to make maintenance and investment decisions.
Contact us for a free initial consultation and Data Quality health-check: get in touch
