A Systematic Approach to Determine the Amount of Data Required for Asset Management Decisions

Abstract

Facility, infrastructure, and asset related data is being generated at an unprecedented rate, usually without specific purposes or goals. Data is collected in large amounts for exploratory science, achieving significant statistical power, due to the relatively cheap cost of storing data in the cloud. In many cases however, organizations do not consider the negative issues with indiscriminate data collection to include diminishing returns to reduce uncertainty in asset management decisions and the cumulative costs of the data. This paper proposes a novel 4-step frame- work for determining the correct amount of data required for asset management decisions. The framework is built upon the following steps: 1) identify the problem, 2) establish context, 3) verify/collect data, and 4) analyze/decide (IEVA). The IEVA framework can be used as a baseline that orients asset managers to collect decision-focused data and make data-informed decisions.