## 5 Discussion  
In this study, six FM KPI groups were identified, and importance orders of FM KPIs were obtained as a result of AHP-PROMETHEE calculations. Findings as a result of AHP-PROMETHEE analysis are summarized below and compared with existing literature [39,140] to identify the importance order of healthcare FM KPIs. \"Prediction of Resource/Energy load profile (E4)\" was found to be the most important KPI under the \"Environmental Aspect in Healthcare Facilities\" group. [PERSON] et al. [180] stated that the availability of the historical records and smart meters can provide optimal resource/energy use in buildings. However, the authors expressed that lack of data analytics induces the inability to perform reduction strategies in energy consumption. Within this context, authors stated that prediction of building energy consumption is a facilitator role to enable energy control and operation strategies. In parallel to literature, results of the study showed that responders need E4 KPI to evaluate the performance of the facility and to give a sound and reliable decision based on data and predictions. However, in the literature, this indicator was not considered in studies of [PERSON] et al. [139] and [PERSON] et al. [39]. The second most important FM KPI was found to be \"Energy/Resource Efficiency\". This KPI was used by [PERSON] et al. [140] to measure healthcare FM performance in China and it was found to be the third most important primary indicator for the evaluation of healthcare FM performance. Similar to the China case, this indicator was found to be important for measuring healthcare facilities' FM performance in Turkey as well. \"Resource/Energy consumption with respect to working days and non-working days (E1)\" was found to be the third most important FM KPI. Data mining methods are helpful to discover useful knowledge from big data sources such as BAS system, EMS, etc. For example, [PERSON] et al. [83] used the SAX representation to discover building power consumption according to climate and day type (weekdays and weekends). This information can be used to compare facilities' resource/energy consumption or discover anomalies. \"Resource/Energy Use Intensity (E10)\" or \"Energy utilization index\" was found to be the sixth most important healthcare FM KPI by [PERSON] [39]. Against the findings of [PERSON] et al., healthcare facilities that are located in Turkey have a lower focus on the E10 indicator to compare facility performance. However, the difference can be related to the consideration of limited FM KPIs for environmental aspects in their study. Moreover, the preferences for \"Greenhouse gas emissions per building area/number of patient/patient bed (E12)\" show parallelism with the findings of [PERSON] et al. [39], since this indicator has lower rank for the Turkey and Hong Kong case. \"Prediction of indoor air parameters and indoor quality (U2)\" and \"Indoor air quality (U1)\" were found to be the two most important FM KPIs under the user aspect group as a result of AHP-PROMETHEE analysis. Indoor air quality is especially important for healthcare facilities. According to ASHRAE Standard 170 Design Parameters [181], operating rooms' relative humidity needs to be within 20 to 60% and temperature needs to be within 68 to 75 F. Healthcare facilities give a service to patients who are very sensitive to outside factors. For example, hyperhyroidism induces people to be more sensitive to hot, humid conditions and heat waves. Furthermore, dry air causes particles to remain airborne for longer periods [181]. Similar to the ASHRAE standard, the Turkish Ministry of Health published design criteria which include the following: indoor air quality such as 17 \({}^{\circ}\)C temperature needs to be present in operating rooms in which, especially, heart operations are conducted [127]. \"Identification of space occupancy (U14)\" is important to figure out energy and resource consumption and development of control strategies in facilities.