Asset data – an overlooked benefit of supply chain transformation

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Utility companies spend millions of pounds each year attempting to reactively improve their asset data through ad-hoc projects. Does the digital transformation of the supply chain present an alternative way to address this issue?

An overlooked benefit

 When a field team member of a utility company comes across a broken piece of equipment which requires replacing, what are their immediate wants?

Well it’s likely that their overriding want is for the equipment/asset to be up and running again as soon as possible. If this requires a replacement, then this generally entails:

  • Raising the issue
  • Getting the request to replace it approved
  • Ordering the right equipment
  • Getting that equipment promptly installed
  • Having it thoroughly tested and commissioned

All of these are aspects which the digital transformation of their organisation’s supply chain can enable, yet there is an additional key benefit which is often overlooked and undervalued: providing corporate systems with updated asset information about the failed equipment and its replacement.

How important really is asset data?

 Utility companies spend millions of pounds every year performing site and asset surveys in an attempt to achieve the ‘holy grail’ of having up to date asset data, yet these projects are often inherently flawed, providing only a short-term fix for their asset data issues. To the field teams on the ground who are often engaged to deliver such projects, the question may also be ‘what’s in it for me?’, with the extra pressure of laboriously reading, noting and verifying asset nameplate data seemingly returning little benefit to the running of their sites.

The risks associated with having poor/outdated data should not be understated though. For example, if a pump is replaced with a new model which requires a different maintenance plan, yet the replacement data never makes it back into the system responsible to generating these plans, the lifespan of the asset could be significantly reduced, or worse, it could pose a risk to health and safety.

Additionally, being unable to accurately report on the lifespan of assets and their failure rates cripples any attempt to perform meaningful analysis which can in turn inform procurement decisions and standard ‘go-to’ products when assets fail.

In summary, poor asset data can be difficult to remedy, pose risks to service and health and safety, and hinder attempts to make informed business decisions.

So how can digital supply chain transformation resolve asset data issues?

 Using examples from a recently delivered project, opportunities to fix asset data present themselves at every step in a remodelled digital supply chain process:

  • Raising the issue – utilise an intuitive mobile solution to submit the issue and supporting evidence, requesting that relevant data about the failed asset is collected when the issue is raised. Machine intelligence can then employ this information to determine cause of failure and build a better understanding of what a standard replacement may be.
  • Approving the request – use system logic to auto-approve simple needs, or route complex requests to the relevant approvers, providing an opportunity for reviewers to check the submitted information and question any inconsistences in collected asset data.
  • Ordering the right equipment – use standard products and suppliers to enable ‘one-click’ ordering of the correct equipment, mandating that suppliers provide all the required new asset information. By creating a standard data model which specifies the properties required for each equipment type, vendors can provide this data as soon as the asset is shipped (e.g. providing equipment name and model numbers, kW ratings, maximum flow etc. for a replacement pump).
  • Getting equipment promptly installed – tracking notifications can be used to highlight that the equipment has arrived on site, making it is a simple task to check whether the data matches the information which the supplier provided and whether there are additional details which could be scanned/catalogued.
  • Having it thoroughly tested and commissioned – checklists and photo/video uploads present not only an additional opportunity to provide evidence of the asset in-situ and pass this back to corporate systems, but also the opportunity to upload guidance documents or augmented reality scans for future use.

 Once this process has been established, it provides a self-sustaining method of ensuring that corporate asset data is kept up to date. Whilst it may potentially take several years for all assets to go through a replacement cycle to get their data updated, this approach is still significantly more effective than attempting to manually collect data from sites on an ad-hoc basis.

By developing this approach to digital supply chain transformation, utility organisations can therefore not only optimise the process for replacing equipment, meeting the engineer’s initial wants to get equipment operational as soon as possible, but also unlock all the potential benefits which come as a result of leveraging accurate asset data.



Luke Matcham

Luke is an experienced senior consultant within the Utilities Assets NSO, which forms part of the wider Operations Transformation team within Capgemini Invent. He specializes in the digital transformation of water utility companies and some of his main interests include improving asset data, customer experience and water efficiency initiatives.

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