Introducing Lifecycle Data Continuity
Over $100bn every year is invested in buildings and infrastructure in Australia, and more than 15% is wasted effort across the whole of asset lifecycle with lost data as the primary cause. This lost data across the life of the assets drives major long term inefficiencies and results in additional unplanned asset expenditure and infrastructure failure.
Data creation and availability at each major stage of the lifecycle of an asset or infrastructure can often be robust, with specific teams leveraging their own equipment, expertise and data warehousing to gather relevant data and insights from own and external resources. This data is often shared and viewed between departments, stakeholders and vendors. But traditionally each stage of asset management and the infrastructure lifecycle remain as independent silos.
Within these silos, far too often asset data isn’t being transitioned along the value chain after it is captured at the relevant source. This leads to an invisible cost burden at each later stage in the asset's lifecycle. These junctions and transitions between the stages of the asset as it moves through its lifecycle are creating lost opportunities. Valuable data from feasibility and planning, through design and construction, all the way to maintenance and then disposal fails to be centralised, analysed and interpreted.
What happens to asset data in your organisation when an asset passes into a new stage of its life?
Imagine choosing the correct asset you need to upgrade or divest, and having all of its data at your fingertips. Imagine understanding it from implementation to maintenance and then to disposal. How would that change your planning process? Where could you save more? Plan better? Where could risk be removed?
The answer is Lifecycle Data Continuity. Bridging across silos to create a data that flows on from each stage of an asset’s life, without the need to recreate data sets. Using a centralised platform coupled with a Data Continuity Framework can ensure data integrity through the life of assets and infrastructure and delivers cumulative value across stages. This empowers and inspires stakeholders throughout the value chain, and across these silos to contribute creatively and collaboratively.
How much of your data has not been transitioned as an asset moves from one stage to another?
Lifecycle Data Continuity introduces an end to end approach bringing together data and intelligence from all stages of an assets life to create value through accessible, meaningful data.
Imagine the power of understanding your assets, all of their data, across their entire life. This would bridge from feasibility and planning through development, operations and eventually replacement. All at your fingertips.
What happens to Asset Data?
Feasibility and planning data around projected costs and maintenance, expected lifecycle, assumptions, variations and choices drive decisions and influence the design and construction phase. Yet when assets pass into the next stage, new stakeholders emerge. Decisions reform, additional data is gathered, previous data may not be transitioned and new assumptions are made. Data may also be created at the next phase, and new analysis undertaken. This duplication may not capture requirements for subsequent stages and so analysis may not be complete, and costs of data acquisition will be higher than they should be if data was utilised from stage to stage.
As an asset enters into operation, ongoing data collection informs maintenance costs, future replacement and upgrade, and decision and structure on future asset and infrastructure development.
What is your infrastructure budget for the next 5 years? How would cost savings affect your decisions?
Our industry has an issue where assets pass through stages of lifecycle, but the data associated with that asset does not. Each stage works effectively in a silo without regard for the next function. A large portion of the problem is a lack of prioritisation and understanding of this issue, and also of job function. In most organisations, the role, job or function to centralise and maintain asset data across the varied stages of its life simply doesn’t exist.
A disconnect exists between how an asset is treated and operated, and the immense value of its data. With haphazard treatment across silos, different priorities for which data is obtained or maintained and there is often poor or no transition to the next stage.
Asset data is itself an asset, and an opportunity exists for data ownership to straddle all stages of lifecycle, and to be owned by everyone across the Lifecycle.
“In technical, large-scale systems, big data and analytics can really shine, in applications such as predictive maintenance. Predictive analytics ensures smooth operations; rather than wait for a mechanical breakdown to occur, predictive maintenance prevents problems and avoids downtime.”
What’s the risk?
A failure to use and leverage asset data continuously across silos and business units is an issue that creates multiple problems within the business.
Wasted dollars
A lack of data can lead to direct cost increases through poor or ineffective decision making. Without being able to effectively make evidence-based decisions, strategies may be undertaken that have larger implications to the asset, and the asset portfolio. Bad decisions can have knock on effects for substantial periods of time.
Lack of transparency of asset performance
Understanding asset performance can also drive poorly informed decisions regarding when to intervene and can increase the risk that the asset will fail or cause a safety issue.
Mismanagement of assets
Mismanagement of assets is an easy trap without continuity of data. Without clear insight and visibility of data generated from each stage of the assets life, future decisions, and ongoing strategy in the maintenance, retirement and replacement of an asset may be made poorly.
Duplication of significant data acquisition costs
Data acquisition costs are frequently duplicated across silos. Essential data to develop, maintain, use and even retire an asset may already be available from another stage of its lifecycle, or from a peer asset. Duplication of data acquisition costs is a common and resolvable symptom of a lack of Lifecycle Data Continuity.
Increases in costs over the entire Lifecycle
Finally, without Lifecycle Data Continuity, increases and over expenditure in costs occur in all stages, which leads to a reduction in efficiency in each stage.
How can Lifecycle Data Continuity help?
Lifecycle Data Continuity requires an understanding of the various requirements and needs across siloed functions. Identifying how data fits, how it will be used and leveraged by each business function.
As an industry we need to recognise and adapt the benefits of an Asset Information Strategy or ‘master plan’ for our asset data. Or to advocate and champion Lifecycle Data Continuity to be business as usual - just part of what we plan at the beginning of an asset’s life.
AssetFuture is working towards this vision. Towards a future with this overarching solution in place. Imagine, all of your asset data available across silos, between business units, creating consistency and transparency throughout the life of an asset. The data is freely available to all functions and is guiding decisions throughout the asset’s life.
Prioritising Lifecycle Data Continuity
As an industry, there are some steps we can take to prioritise Lifecycle Data Continuity:
Who would maintain compliance with an Asset Data Format Framework in your organisation?
Where would Data Continuity Leadership best sit within your business?
1: Data Continuity Leadership (and management on larger projects)
Asset data ownership from a cost and decision perspective is important question. In organisations with large and often geographically dispersed teams, ownership of asset data can cross silos and fall within multiple business units.
We need to consider:
Decision-making authority on Data Continuity
Authority over asset data from all stakeholders
Ensures benchmark compliance for data requirements
2: Data Format Framework
Implementation of a data format framework can be a large undertaking, but over time brings responsibility across business units to comply. With each segment of the business facing their own goals, objectives and challenges, the issue of ownership and accountability needs to be considered. Suggested considerations would be:
Complete data management plan - from stakeholder input, specifying all operational constraints and business drivers
Dictate data capture standards - ie structured hierarchy and item level location details
Ensures satisfactory interfacing and handover of workable data
Agreed KPIs for satisfying stage to stage data transition
3. Centralisation of asset data and information
Creation of a centralised point for asset data collection and storage is fundamental for Lifecycle Data Continuity. With the Data Format Framework complete, this would enable:
Stakeholder accessibility and data currency
Creates transparency
Ensures data accuracy
Eliminates duplication between silos
4. Asset data - treat it as an asset
Asset Data being nurtured and maintained as a built asset would is a new concept that will push an organisation’s thinking and prioritisation of data currency and sovereignty. Concepts to consider:
Maintain data currency via a bespoke program and operational delivery
Enables data evolution for future decision making
Generate a return on investment on your data when making informed decisions, and improving performance while reducing cost and risk for the asset portfolio
Lifecycle Data Continuity starts the conversation in our industry about how we currently treat asset data and how we should be treating it. Migrating to this way of thinking and working will bring new challenges and questions, and will require changes to internal processes and systems.
Given the value we place on being able to understand closely the cost, risk and performance of assets, shouldn’t we give ourselves the challenge to see the full picture?
Who are we?
AssetFuture is a company focused on data. We’re more than just a platform. Our cloud-based technology leverages terabytes of data to categorise and model components, asset systems and drive decisions across the lifecycle of assets large and small. Our team of consists of asset management specialists, technology experts and data scientists working together to deliver results.
Asset Intelligence is about analysis. It’s deep data on your assets throughout their lifecycle driving the decisions you need. Asset Intelligence leads to significant business benefits. Cost savings, decreases in risk, and an enhanced ability to make strategic decisions for the entire lifecycle.