Abstract

Current methods for controlling of construction projects are characterized by manual processes, which are failure-prone, tedious and for that time-consuming and cost-intensive. Furthermore, an additional challenge is caused by the absent dynamic in conventional controlling processes, which is of high importance to avoid damages and ensure a proactive management of a construction project. As construction projects are highly complex due to various influences which imply an enormous amount of information and are designated by dynamic processes, conventional controlling methods are insufficient and not able to meet these requirements. Therefore, current data-driven developments which can deal with an enormous amount of information are indispensable for a sufficient controlling of complex and dynamic projects. Accordingly, within this paper an approach for a data-driven controlling solution is presented, in which common data environments, databases and business intelligence applications are combined to ensure an efficient and proactive controlling. To investigate the advantages of business intelligence solutions for data-driven controlling the exemplary scenario of claim management controlling is used. It is shown that the user is able to speed up the processes and secure a proactive controlling by using a consistent database throughout the project. To achieve these targets an automatic data orchestration and visualization of the claim offers is exploited. Consequently, the claim manager is able to predict developments, identify risk potential, investigate KPIs or take actions to minimize negative effects e.g., time effort and costs. The requirements for these purposes are considered in a recommendation for action differentiated regarding the individual elements of a socio-technical system (human, organization, technology). The outlook includes an overview of potential technologies to ensure real-time analytics to shorten reaction and damage times related to the claims by immediately initiating countermeasures.

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