Implementation of the Data-Driven Analytics Protocol through Facility Management and Real Estate Industry Cases

Abstract

This research proposes a systematic data-driven analytics protocol and case studies that can help decision makers in the construction industry embrace the practice of using data to make critical choices. The protocol consists of six phases: (1) conceptualization, (2) design, (3) development, (4) refinement, (5) analysis, and (6) outcome. Two case studies, the Fire Engineering and Maintenance Department at a university in Indiana and housing market outlook and business expansion locations are conducted based on the proposed protocol. As a result of implementing the data-driven analytics protocol for the first case study, a budget strategy for preventive maintenance was established through activity prioritization and a clustering analysis. In the second case study, the future values for the land permits were predicted, and the counties with investment value in land availability were selected for strategic business expansion. Therefore, the proposed systematic protocol for analytics would help decision makers and employees comprehend projects and realize the importance of data-driven analytics, which would promote insights into long-term success in their organization.

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