Benchmarking facilities operation and maintenance management using CAFM database: Data analysis and new results

• Workflow of benchmarking for facilities management.
• Integration of CAFM system components in the benchmarking project.
• Statistical techniques to provide new results.

Operation and maintenance (O&M) activities of the constructed facilities are the longest part in the life cycle of the building. Similarly the energy consumption costs and the maintenance costs are the largest expense component for the property sustainment budget. The performance of these O&M activities needs to be measured annually and monitored to support long-term cost saving strategies. This study demonstrates the application of three dimensions (3D) object-oriented database supporting the facilities management benchmarking project. As case study the 3D object hierarchy of the Central Building of the Graphisoft Park in Budapest was presented. The objective of the current study may provide feasibility workflow diagram and prototype for organizations that start to collect benchmark data from their own buildings. The main objectives were to specify the access of data in Computer Aided Facility Management (CAFM) system, and to elaborate a methodology to gathering building O&M costs data with the core outcome that is usable for further quantitative analysis included hypothesis testing. To achieve this objective, based on a questionnaire survey new sample of data collected on facility management factors, sites (n=76) and buildings on the sites (n=207) from the range of Hungarian Corporate Real Estates were participated. Data mining techniques included Descriptive Statistics, Correlation Analysis, one-way ANOVA and Box Plot was used to identify significant relationships to determine differences in annual O&M costs by age, number of users and heritage. This study presents new results where negative correlation between maintenance costs and age of the facilities was found. ANOVA was obtained (p<0.05), the number of users of buildings has a significant positive effect and explain almost 60% of annual utility costs of facilities. Identical to the hypothesized nearly 100% higher mean annual maintenance cost per m2 was measured between heritage and non heritage facilities.