Translating Management Maturity Levels to Flood Defences Asset Cost and Performance
Using Dynamic Bayesian Networks
R. Radityo Andjaringrat Adhi (TU Delft - Civil Engineering & Geosciences)
W.J. Klerk – Mentor (TU Delft - Hydraulic Structures and Flood Risk)
M. Kok – Mentor (TU Delft - Hydraulic Structures and Flood Risk)
M. van den Boomen – Mentor (TU Delft - Integral Design & Management)
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Abstract
Maturity model is widely known as an assessment tool to understand an organization management capabilities and identifying potential improvement. The model demonstrates informative results towards the organization management maturity but hard to acknowledge the influence of potential improvement towards the organization’s asset performance. There have not yet been a study on measuring the asset performance conditional of the organization management maturity. This research objective is to develop an approach to translates maturity model to an asset lifecycle cost and performance by using Dynamic Bayesian Network (DBN). This research uses semi-hypothetical case to see how the model might unfold and to learn the possibility of maturity model development. The chosen hypothetical case is the organizational decision-making process of grass revetment maintenance during winter season based on information management maturity. The output of the DBN is the expected annual cost of the asset for a grass revetment maintenance conditional to organization information management maturity. The result is analyzed by using Value of Information (VOI) which enables us to understand the influence of information management maturity towards the asset lifecycle cost. This research has led us to the conclusion that it is feasible to associate asset lifecycle cost and performance with the organization information management maturity by translating the case into a DBN. In general, this research can potentially lead to a better application on the maturity model and might be used for the organization decision process. This study is the first step towards enhancing our understanding of maturity model application and its implication towards the asset performance.