The ability to develop optimal investment strategies for meeting
performance and risk level targets over the long term is crucial
in high capital industries. To be successful, organizations with a
significant asset base need to find effective ways to forecast using
enormous volumes of asset data, and integrate multiple, sophisticated
management policies into a global strategy.
Over the past two decades, many asset-intensive organizations have
been investing in enterprise asset management (EAM) systems and,
more recently, asset performance management (APM) tools to help
improve asset performance, reduce operating costs, and enhance
maintenance planning. However, when making important asset
investment decisions, many organizations still use a combination of
home-grown capital planning tools and Excel spreadsheets.
The main limitations with current approaches to asset planning is that
they provide organizations with only a static view of the state of their
assets. In addition, spreadsheets can quickly reach their data cap and
asset inter-relationships based on procedural code are very difficult to
manage.
One of the main reasons of adopting an AIP solution is that
organizations can use data already contained in their EAM systems
and APM tools to plan when and where to invest capital in their
infrastructure over the long term. By using data from their existing
asset management systems to develop strategic investment plans,
organizations can improve efficiency, reduce costs, and, even
experiment with alternative revenue streams.
There are a wide variety of benefits associated with adopting an AIP
solution. One of the top benefits is that AIP allows organizations to
move away from the traditional, reactive approach towards a longterm, more strategic asset management roadmap for infrastructure
spending. This results in more effective resource planning and a better
understanding of which investments are ideal over the long-term.
By extracting data from asset management systems and leveraging
business analytics, AIP solutions are a crucial tool for helping
organizations justify planned capital expenditures on infrastructure.
This approach to asset management provides a repeatable, credible,
and highly-accurate methodology that relies on data for planning
infrastructure spending, thereby reducing the possibility of human
error and bias in large capital investment decisions