Infrastructure and asset investments deliver strong returns with relatively stable risk profiles. However, according to the experts at McKinsey & Company, the industry is experiencing some turbulence due to declining equity markets, growing interest rates, and significant inflation.
Along with shifts in the market, the article points to energy, mobility, and digitization as influencing these changes. In response, investors are actively reviewing their existing portfolios to ensure their investments’ risk/return ratio is correctly rated.
When building accurate risk/return ratios, you need data and plenty of it. While most dynamic assets are well documented as individual line items within a fixed asset register, there are many layers of granular data associated with each asset that must also be factored into the analysis.
In this blog post, we examine the value of accessing all available asset data to optimize the accuracy of your risk/return ratios. Insights generated from a broader data view help inform your decisions and ensure the strongest possible returns on your investments.
Data collection & analysis
While a visual inspection helps determine the current condition of your assets, when assigning a risk/return ratio, you must also consider the entire asset lifecycle. Not just in terms of past failures or other performance issues but to determine where the asset is in its maintenance cycle, what repairs have been made, whether any components have been replaced or retrofitted, and other considerations that impact performance and overall value.
Data access and collection is not easy and is often the most time-consuming aspect of acquiring and selling dynamic infrastructure and assets. While every investor understands the need to perform appropriate due diligence, the resources and time required to collect data from multiple systems are staggering.
This is because asset information is stored across multiple systems that rarely interact. Inventory and parts are managed separately from maintenance and service. Operational data, for example, asset performance, downtime, and other metrics, are also stored in different systems.
As a result, collecting asset data when acquiring and offboarding assets—especially historical information—requires significant effort by many humans over many weeks (and often months). In a business where accuracy and speed are critical to profit margins, shortening this window provides your portfolio with meaningful upside.
A streamlined data model
IFS Cloud EAM allows you to easily collect and analyze data from all points across the entire lifecycle of every asset. This includes asset hierarchies, maintenance (historical and planned), operational records, and service work, down to individual repairs, hours spent, and parts used.
With IFS Cloud EAM, you can:
- Access and analyze data from every asset in your existing portfolio to inform risk/return ratios
- Onboard and ingest data from new assets
- Cleanly extract data when transferring the assets to another owner
An asset’s capacity to perform and the cycles of maintenance needed to keep it performant are essential factors when building a risk/return ratio. While real-time productivity is relevant, you must also examine how an asset has performed historically and the time and costs invested.
This data supports critical business KPIs that help measure asset performance. Examples include:
- Asset lifecycle cost: The total cost of an asset throughout its lifecycle, including acquisition, operation, maintenance, and disposal
- Mean time to repair: The amount of time to repair an asset and whether this is increasing over time, perhaps signaling the need to retire the asset
- Mean time between failures: The amount of time that passes before an asset fails, used to inform the cadence of maintenance cycles and as a flag for when failures are occurring more frequently
- Mean time to failure: Estimate of when an asset will fail, typically for components that cannot be repaired, used to determine if assets were installed correctly and functioning according to specs
Data from maintenance and repair activities, such as the number of service calls, parts used, technician hours, and other granular information, provide accurate insights into the state of every asset in your portfolio.
While business models may differ, every IFS Cloud EAM customer is an investor in their infrastructure and assets. With access to reliable, accurate data, these organizations can achieve and increase profitability via asset investment.
Whether building a risk/return ratio, acquiring, or offboarding assets for your dynamic infrastructure and asset portfolio, IFS Cloud EAM seamlessly collects and delivers real-time asset data, replacing manual workflows and dozens of resources with just a few clicks. To learn more, download our paper: Asset Management for Dynamic Asset Owners.
SOURCE : Beemsterboer, B. (2023b, October 20). Dynamic Infrastructure & Assets: The Devil’s in the Data. IFS Blog. https://blog.ifs.com/2023/10/dynamic-infrastructure-assets-the-devils-in-the-data/
