- 10th December 2018
- Posted by: Sophie Bunker
- Category: Blog
Ian Benn, Clerk to the Shire Group of Internal Boards, and Paul Jones, Lead Water Level Management Engineer, also for the Shire Group of Internal Boards, attended the Institute of Asset Management (IAM) conference recently.
As the Institute’s unique ‘call for papers’ event, the conference is designed to cover the breadth and depth of asset management. Sessions comprised of presentations from keynote speakers, workshops, and an IAM Awards stream. Key themes covered in this year’s programme were:
- Continual improvement
- Fundamentals and lifecycle
- Tools and techniques
- Performance management value.
Some of the talks that Ian and Paul found interesting are highlighted below.
Data: the journey to digital asset management
Tim Kerskey from Network Rail presented on ‘Data: the journey to digital asset management.’ In terms of progress in creating a digital replica of their assets, Network Rail have progressed more with track than structures and earthworks.
They have realised that managing assets gives short-term quick wins, whereas asset management is a long-term whole life value realisation. A shared vision has been developed which has been useful for engaging with multiple disciplines within the company.
Intelligent infrastructure innovation – digitally enabled asset management on the Forth Road bridges
From Ewan Angus’ talk, it appeared smart assets are becoming more prominent, but there is still much room for improvement in the infrastructure industry. His session noted how Amey is using big data, advanced analytics and machine learning to provide a sophisticated and innovative asset management and Simple Harmonic Motion (SHM) tool for the Forth Road Bridges.
By digitally enabling smart asset management using machine learning techniques and algorithms, they can enable structures to carry out health checks and compare operating parameters. Using drone technology to acquire data, they have built a virtual 3D bridge which can be compared with what operatives pick up when carrying out comparative reviews.
Three kinds of assets
Thomas Smith from the University of Wisconsin-Madison told attendees that there are three kinds of assets and used the airline industry to give an example:
|Types of asset||Airline industry example|
|Core assets (CA)||Ability to charge customers and collect money|
|Strategic assets (SA)||Aeroplane route|
|Execution assets (EA)||Planes, airports etc.|
He highlighted that marketing drives companies like General Mills and Ford. It is interesting to note that Ford is no longer producing cars, they are focusing on trucks, which shows the need to understand your core assets and customers to manage change in your industries.
Bridging the data gap in asset optimisation
Sarah Noonan and Ross Fisher highlighted the importance of accurate data collection and confirming any desktop studies through eyes on the ground. Several examples were given where asset management relating to the maintenance of external electrical systems had been tagged as high-risk elements due to perceived access issues. These could, however, be downgraded after undertaking field surveys.
Monitoring the performance of asset management – the next generation of balanced scorecard
There were some brilliant learning outcomes in John Woodhouse’s talk. He believes asset management should not be a balance of requirements but a blend. Some items, i.e. safety or legislative requirements, cannot be balanced out against cost.
The time lag within systems, i.e. the cost of reducing or slashing expenditure, do not usually become apparent until three to four years later. Internal competition within a business is not always healthy as it can set teams and managers against each other.
He concluded that the importance of the sustained life cycle brings several benefits:
- Seeking optimum solutions
- Not falling into the trap of protecting the revenue of tomorrow by sweating the assets today – care does need to be taken
- Performance measurement – important to ensure suitable measures
- Useful KPIs are usually complex to measure
- KISS (keep it simple stupid) does not work for KPIs
- Low probability, high consequence failures are hard to predict/measure