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Asset Management Ecosystem


Enterprise asset management (EAM) systems help organizations in the design, construction, commissioning, operation, and maintenance of their assets. These systems allow them to create better budget projections, more effectively manage inventory, work orders, and billing, determine the future state and continued reliability of an asset, and improve the efficiency of technician workflows.

Organizations with a significant asset base, including utilities and governments, began deploying EAM systems approximately 20 years ago as a cost-effective way to manage the lifecycle of their physical assets, including buildings and equipment.

Whereas maintenance is the primary goal of an EAM system, an asset performance management (APM) tool improves operations and prioritizes inspection and other activities on assets that are critical to daily operations. By using data capture, visualization, integration, and analytics, an APM allows organizations to reduce unplanned repair work, increase asset availability, minimize costs, and reduce the risk of failure.

Asset investment planning (AIP) is the next phase in the evolution of asset management solutions. AIP leverages data from existing EAM systems and APM tools to analyze alternatives or different strategies for spending limited capital on the entire portfolio of assets. This allows organizations to make objective, data-driven decisions that optimize costs and minimize operational risk over the full investment lifecycle of an asset.

How is AIP different from APM?

AIP and APM often utilize the same data and similar analytic techniques but perform very different functions. While APM tools help with the short-term management of assets, including operation and maintenance, AIP solutions are designed to support long-term capital investment decisions.

Frequently used by local governments and regulated utilities, AIP solutions analyze data related to asset condition, maintenance costs, criticality, budgets, and risks to produce long-term capital investment plans that typically extend from 5 to 50 years.

The goal of AIP is to simulate the entire life-cycle cost of each asset, each asset class, and ultimately the entire asset inventory. This enables organizations to quantify risks and identify the most economical opportunities available for achieving the desired levels of services.

Most AIP solutions make use of financial modeling techniques, source data about asset characteristics and conditions, predictive analytics for modeling the behavior of assets over time, and prescriptive analytics for experimenting with different ways to influence the condition of assets. These features allow organizations to:

  • make more accurate, data-driven asset investment decisions,
  • assess trends related to asset performance over time and make asset investment decisions accordingly,
  • explore alternative opportunities for revenue-generation,
  • reduce operational risks related to asset failure and maintain or improve service levels.
  • By working with an AIP solution that simulates various combinations of inspection, maintenance, and renewal policies, organizations can compare total cost versus levels of service in the long run and prioritize interventions based on actual and predicted asset condition as well as criticality.

Main Features of an AIP Solution

AIP solutions are designed to extract essential asset-related data from existing EAM systems and APM tools, including physical attributes, criticality, and historical interventions or events. Working with this data, organizations can make well-informed decisions related to asset maintenance and policy and develop accurate strategic investment plans.

Asset attribute modeling is another essential feature of AIP solutions. It allows organizations to create and calculate specific attributes or relevant industry or asset-specific indicators that they would like to follow or use in decision policies. This modeling capability can also be used to generate predictive models for specific attributes, including asset condition and probabilities of failure.

Additional technical characteristics can include predictive models and combinatorial analysis. Organizations can use predictive models to consider and quantify inherent uncertainties surrounding various parameters, including future degradation or asset-aging, cost related to specific interventions, and macro-economic factors. Combinatorial analysis can be used to create multiple decision policies for each asset type as well as to synchronize interventions and manage several constraints on groups of assets.

Lastly, AIP solutions rapidly generate asset management reports, including investment master planning, short and long-term capital planning, levels of service, and accounting reports, that take into account the entirety of an organization’s asset knowledge. This leads to dramatic improvements both in mean-time-to-decision and in the overall quality of the asset analysis and also makes it easier to include a wide variety of stakeholders in the planning and budget-approval process.

Be Pro-active with AIP

AIP combines infrastructure modeling tools with C-level financial and performance reporting to help asset-intensive organizations improve organizational efficiency, reduce costs, and explore different revenue opportunities. Using this proactive, data-centric approach to executive-level capital investment decision-making, organizations can model both the behavior of their assets over time as well as the decision-making policies that go into maintaining a given level of service and risk over the entire lifecycle of those assets.

DIREXYON’s Unique Approach to AIP

DIREXYON is a unique financial modeling and predictive analytics solution for complex, long-term strategic asset investment planning that allows our clients to effectively digitize their institutional expertise and make clearer, data-driven asset investment decisions.

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