Detailed Investigation of an Organization Using Regression Analysis to Improve Facilities Maintenance Operations Across its Multiple Locations
Open Access DepositedPM-Door representing preventative maintenance (PM) tasks and SR-Locksmith representing service requests tasks. The data was obtained from an organization with three facility locations and evaluated using descriptive statistics, Pearson’s correlation, two-sample t-tests, simpler linear regression (SLR), multiple linear regression (MLR), and MLR with interaction terms. The results produced statistically significant improvements in completion time across all work order (WO) categories. The regression results were used to develop an interactive Decision-Making Tool that enables FMM personnel to make data-informed decisions supported by statistical evidence. A Net Present Value (NPV) comparing pre- and post-FMMOM staffing structure showed significant reduction in total NPV over a six-year period. This research demonstrated both the financial and operational impact the implementation of the FMMOM has on FMM across an organization’s locations.
Organizations continue to struggle with ongoing challenges in technology integration, operational inconsistencies, disconnected systems, aging infrastructure, siloed operations, and skills gap across their facility locations. To achieve effective Facilities Maintenance Management (FMM) operations across multiple locations, this Praxis proposes the implementation of the FMM Operations Model (FMMOM). The FMMOM consists of ten components which were evaluated using regression analysis to quantify their combined and individual impact on operational efficiency. Two datasets were assessed
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ClarkeMorgan_gwu_0075A_17904.pdf | 2026-06-24 | Open Access |
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