Asset Performance Modelling

Our approach to Performance Modelling takes the generic underlying functionality required to model the performance of assets (e.g. asset failure and degradation, and its associated consequences) and ties it to the specific Key Performance Indicators of a client's business, such as a specific Performance-Penalty regime*, and predicts how the performance of assets impacts on client's revenue.

Risk-based

apm’s approach considers two major factor

• Data Uncertainty: Asset owners may have a number of different asset data repository systems, as well as tacit data
• Data Variability: The performance of assets, such as asset failure frequency, varies with time – changing from one month to the next

Our approach allows data to be taken in many forms and levels, and accounts for both its uncertainty and variability. In fact, apm push the idea that data only needs to be collected at a high-level unless it is critical.

In terms of taking a risk-based approach to performance modelling, this is crucial when attempting to make informed asset investment decisions, as it allows a client to understand how its assets will perform: (a) on average (at the mean or 50th percentile), and; (b) at the worst case (e.g. at the 95th percentile). This information can be used to determine how the uncertainty of asset performance impacts a clients KPIs and/or revenue.

The difference between the mean and the 95th is risk generated through data uncertainty and variability, and would normally be held in a Risk Register as part of a businesses Risk Management system, or would form part of a Risk Contingency Fund as part of a Tendering process.

Benefits Analysis

We typically take a scenarios approach to assessing asset plans:

• A base-line asset plan is set
• Different scenarios are created, based on incremental changes to the base-line
• Quantification and/or qualification of the benefits of each incremental change can be made by comparing the base-line and other scenarios

Early Implementation

The full benefits of apm's Performance Modelling are achieved via early modelling implementation; if necessary, in advance of an asset management system.

The fact that the approach can use data in a relatively raw form means that it can generate results very quickly. After which, data gathering and integrated systems not only provide the basis for collecting the right data, and more efficiently, but greatly speed up our ability to provide more refined performance, KPI and revenue predictions.