https://doi.org/10.24928/2018/0535

Ad Hoc Data Analytics and Business Intelligence Service Framework for Construction Projects

Frank L. Wang1, Leonardo Rischmoller2, Dean Reed3 & Atul Khanzode44

1Business Intelligence Lead, DPR Construction, 1450 Veterans Boulevard, Redwood City, CA 94063, USA, [email protected]
2Business Analyst, DPR Construction, 1450 Veterans Boulevard, Redwood City, CA 94063, USA, [email protected]
3Lean/Integration Advocate, DPR Construction, 1450 Veterans Boulevard, Redwood City, CA 94063, USA, [email protected]
4Technology and Innovation Leader, DPR Construction, 1450 Veterans Boulevard, Redwood City, CA 94063, USA, [email protected]

Abstract

This paper presents a framework of an ad-hoc data analytic and Business Intelligence service tailored to a construction project. Mandates of delivering integrated information solutions and effective reporting are commonly required nowadays in large capital projects. Due to the nature of construction projects with schedule and budget constraints, poorly defined business problems prohibited the team to deploy full scale data analytic and Business Intelligence (BI) services on site. On the other hand, the increasingly complex data coming from multiple applications and organizations on projects requires more powerful data integration tools and techniques. The proposed framework outlines an agile and ad hoc best practice for job site data analytics and effective reporting based on a real use case from a large pharmaceutical project. Processes in the framework include data alignment, Level of Detail (LoD) data articulation and analytical model establishment. It also illustrates how to resolve complex data analytic challenges for unforeseen cost disputes and how to deliver solutions within a short period of time.

Keywords

Integration, waste, customization, complex, Integrated Information, Data Analytics

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Reference

Wang, F. L. , Rischmoller, L. , Reed, D. & Khanzode4, A. 2018. Ad Hoc Data Analytics and Business Intelligence Service Framework for Construction Projects, 26th Annual Conference of the International Group for Lean Construction , 1058-1068. doi.org/10.24928/2018/0535

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