Aesthetic Workshop 2015 Business Intelligence Advancement Workshop

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Aesthetic Workshop 2015 Business Intelligence Advancement Workshop – BIM for Landscape Design Improving Climate Adaptation Planning: The Evaluation of Software Tools Based on the ISO 25010 Standard

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Aesthetic Workshop 2015 Business Intelligence Advancement Workshop

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Serious Games And Gamification

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By Gökhan Demirdöğen Gökhan Demirdöğen Scilit Google Scholar 1 , Zeynep Işık Zeynep Işık Scilit Google Scholar 1 and Yusuf Arayici Yusuf Arayici Scilit Google Scholar 2, *

User‐centered Approaches In Software Development Processes: Qualitative Research Into The Practice Of Hungarian Companies

Received: August 6, 2021 / Revised: November 22, 2021 / Accepted: December 2, 2021 / Published: January 10, 2022

(This article belongs to the special issue BIM implementation to meet the changing demands of the construction industry)

The use of digital technologies such as Internet of Things (IoT) and smart meters creates a huge data stack in facility management (FM). However, the use of data analysis techniques has been limited to converting available data into information within activities carried out in FM. In this context, Business Intelligence and Analytics (BI&A) techniques can offer a promising opportunity to elaborate on facility performance and discover measurable new FM Key Performance Indicators (KPIs), as existing KPIs are too crude to reflect actual facility performance to discover. In addition, there is no comprehensive study covering BI&A activities and their importance for FM in healthcare. Therefore, this study aims to identify healthcare FM KPIs and their levels of importance for the Turkish healthcare FM sector using the AHP-integrated PROMETHEE method. As a result of the research, 98 FM KPIs in healthcare were found, which are divided into six categories. The comparison of the findings with the literature search showed that there are some similarities and differences between countries’ FM healthcare ranks. Within this context, differences between countries can be related to the inclusion of limited FM KPIs in the existing studies. Therefore, the FM KPIs proposed in this study are very comprehensive and detailed to measure and discover FM performance in healthcare. This research can help professionals to perform more detailed building performance analysis in FM. In addition, the findings of this study will pave the way for new developments in FM software and effective use of available data to enable lean FM processes in healthcare facilities.

Business Intelligence and Analytics (BI&A) is an umbrella term that refers to information systems for transforming raw data into meaningful information and reducing uncertainty in decision making [1]. It allows one to extract critical business information from the data stack. This helps organizations gain a competitive advantage over counterparts [2]. That is why BI&A activities have become one of the most important activities in companies. Today, the need for data analytics activities is increasing with the advancement in technology, such as the use of cloud technologies, databases and IT-oriented technologies in the architecture, engineering and construction (AEC) industry [3]. Expectations of IT-oriented technologies in AEC are automation, workflow, business process improvement, knowledge acquisition across systems and devices, and analytics and forecasting solutions, requiring more BI&A implementation [4].

If Design Foundation

FM is the most costly phase in the building life cycle, the building life cycle phase that corresponds to 60% of the life cycle cost expenditure [5, 6]. In addition, 30% of global energy is consumed by buildings [7]. Statistics show that the energy consumption of buildings will increase by another 70% by 2050 [8]. In addition, about 16% more energy is consumed by buildings compared to design data [9]. Irregular or poor maintenance activities lead to increased energy consumption (30%) in commercial buildings [10]. In FM, fault detection and diagnosis (FDD), including the use of data mining, can enable energy savings of 5-30% [9]. To eliminate high expenditure, technical inspections can be carried out in facilities. However, the technical inspections are not complete in identifying the real condition of assets and minor errors, causing more serious problems in the running processes. Mawed and Al-Hajj [11] explicitly stated that the wrong decision of service providers in the FM industry led to declining margins. Therefore, using available data from Automated Maintenance Systems (CMMS), Electronic Document Management Systems (EDMS), Energy Management Systems (EMS), Energy Management Control Systems (EMCS), Building Information Modeling (BIM) and Building Automation Systems (BAS) is crucial to perform preventive actions in facilities [ 9, 12, 13, 14]. For example, BAS registers raw data from the building environment in a short time (30 s or 1 min) [15]. Researchers believe that using these systems would increase efficiency; reduce the problems you face such as power management, FDD and control optimization; and eliminate personal judgment in the built environment [15, 16]. Available data can be used to evaluate and improve facility performance [13, 17].

Mechanical, electrical and plumbing (MEP) systems also account for approximately 40% of total construction costs. In addition, the prices of maintenance work of built MEP systems consist of 60% of the maintenance costs [18]. FDD systems provide an excellent opportunity to diagnose FM problems. However, FDD lacks capabilities in terms of functional and behavioral interaction between systems, user comfort and components [9]. O’Neill et al. [9] stated that the interconnected complexity and sheer volume of the operation and maintenance phase create an overwhelming decision-making process. Therefore, the use of data analysis activities in the operation and maintenance phase is essential to eliminate serious cost implications and ensure the safety of building installations.

Hopland and Kvamsdal [19] stated that FM consists of complex operations and activities. Therefore, the authors emphasized that facility managers need the right tools to manage scarce resources. However, the proposed FM systems in the literature or available commercial systems are query based or have limited data analysis capabilities or limited data availability, depending on the lack of mean values ​​(rules based systems) or a specific area such as energy and maintenance or need for an external analytics solution such as Python, R or Weka in terms of certain data sources (such as BIM) [15, 17, 20, 21, 22, 23, 24, 25, 26, 27]. Therefore, no data-driven decisions can be made during FM. Achmed et al. [3] stated that larger datasets are created during the lifecycle of a construction project. However, the value of these data sources is hidden. Authors indicated that BI&A can be used to analyze or predict project KPIs. Parallel to the study by Ahmed et al., Lavy et al. [28] reported that data analytics can be used in analyzing relationships and effects of FM key performance indicators (KPIs). In addition, Dutta et al. [29] and Gunay et al. [17] stated that the available performance metrics only consider one aspect of performance and undermine new technology and advances in data analytics. Within this context, data analytics activities represent a promising feature to uncover more detailed facility performance and new KPIs for FM.

While there are some studies in the literature that use individual BI&A solutions for FM problems and their use in building performance assessment, there is no comprehensive study that combines all the necessary FM KPIs. A few studies focused only on determining and ranking FM KPIs for healthcare facilities. However, these studies do not take into account the power of data analysis. Therefore, although high-tech systems are used in healthcare FM, discovering new KPIs in these studies is limited. Moreover, lack of determination of data analysis activities in FM causes hidden value in or non-measurement of data and relies on unavailable data. Therefore, performance benchmarking is limited to raw metrics. Due to non-data-driven decisions, FM results in cost inefficiency, inadequacy, unsuitability of facilities for future needs, and failure to contribute to the mission of the organization [17, 30]. Therefore, this study aims to: (i) identify and define FM KPIs for the management of healthcare facilities throughout their lifespan; and (ii) prioritizing FM KPIs for the Turkish healthcare sector.

From Plastic Waste To Art

Thus, the contribution of the study is to reveal measurable FM KPIs to enable detailed performance analysis and strategic decision-making in healthcare facilities. With an empirical study, the research contributes to practice by signaling

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