Leveraging previously reported research to create a decision support tool for institutional facility maintenance

2019 ◽  
Vol 17 (3) ◽  
pp. 249-266
Author(s):  
Michael A. Beauregard ◽  
Steven K. Ayer
Keyword(s):  
Decision Support ◽  
Literature Review ◽  
Decision Support Tool ◽  
Facility Management ◽  
Decision Makers ◽  
Content Type ◽  
Support Tool ◽  
Facility Maintenance ◽  
K 12 ◽  
Work Orders

Purpose The discretionary expense budget required to maintain public infrastructure has declined in recent years, even as public expectations and accountability for performance have increased. The purpose of this paper is to leverage previously reported research to create a decision support tool (DST) for prioritizing institutional facility maintenance. Design/methodology/approach A structured literature review was developed to identify critical aspects of facility maintenance shown to have a positive relationship with academic performance in K-12 schools within the USA. Analytical hierarchy process (AHP) serves as a framework for a multi-criteria DST based on the findings of the literature review. Finally, a targeted focus group of industry professionals was used to validate the usability of the resulting DST. Findings The framework for the DST developed for this study effectively represents the scale and scope of an institutional facility. Results of the study suggest that when evaluating multi-criteria work orders, the proposed visual AHP methodology can be used to generate usable DSTs to assist with the prioritization of work. Practical implications This study provides a methodology for building a multi-criterion DST leveraging precedent research, using a visual AHP to assist facility management (FM) decision-makers in the prioritization of routine work orders. Originality/value The developed process indicates a practical approach to incorporating disparate research findings into a concise and useable manner to guide FM decision-makers, who have traditionally not been able to explicitly leverage this information to make evidence-based spending decisions.

Reliability analysis of productivity enhancement initiatives

2018 ◽  
Vol 29 (6) ◽  
pp. 1003-1024 ◽  
Author(s):  
Boyd Alexander Nicholds ◽  
John P.T. Mo
Keyword(s):  
Risk Assessment ◽  
Decision Support ◽  
Human Factors ◽  
Decision Support Tool ◽  
Reliability Function ◽  
Decision Makers ◽  
Performance Gain ◽  
Content Type ◽  
Support Tool ◽  
Performance Targets

Purpose Process improvement (PI) projects in manufacturing suffer from high failure rates, often due to management capability overstretch. An organisation’s management may be unaware that they lack the necessary capability to achieve desired performance gains from a particular PI project. As a consequence, PI projects containing a level of complexity are undertaken but the organisation is not capable of providing the required resources. The purpose of this paper is to develop a new method for assessing whether a productivity enhancement initiative which develops into PI projects have a good probability of success (POS). The risk assessment method predicts the POS in achieving desired performance targets from a PI project. Design/methodology/approach The POS of a system can be measured in terms of reliability. An operation with a high POS indicates high reliability of the system’s ability to perform. Reliability is a form of risk assessment. When applied to PI projects, several key factors should be addressed. First, risk should be modelled with a framework that includes human factors. Second, time is an important dimension due to the need for persistence in effort. This research proposes the concept of performance effectiveness function, kP, that links the capability of an organisation with its performance level. A PI reliability function indicating the probably of success of the PI projects can then be derived at the design stage by combining the capability score and actual performance. Findings The PI reliability function has been developed and tested with an industry case in which a PI project is planned. The analysis indicates that the company is far from ideal to do the project. Research limitations/implications The reliability function may be used as a decision support tool to assist decision makers to set realistic performance gain targets from PI projects. The data set for deriving the function came from automotive and metal industries. Further research is required to generalise this methodology to other industries. Practical implications The reliability-based approach fills the gap in PI literature with a more holistic approach to determine the POS. Using the system’s reliability as an indicator, decision makers can analyse the system’s design so that resources can be used to increase key capabilities and hence the overall system’s POS can be increased more effectively. Social implications Many manufacturing organisations are looking to improve their operations by projects that aim to reduce waste in their operations. However, researches show that while achieving desired performance gain from PI is possible, it is by no means certain due to human factors. This research provides a decision support tool that evaluates human factors as well. Originality/value The originality lies in integration of the reliability theory to PI risk assessment and the novel method of characterising organisational capabilities to work towards meeting desired performance targets from manufacturing PI projects. This work has good potential to generalise for estimating the POS of other types of development projects.

scholarly journals A web-based decision support tool for groundwater remediation technologies selection

2006 ◽  
Vol 8 (2) ◽  
pp. 91-100 ◽  
Author(s):  
Olfa Khelifi ◽  
Andrea Lodolo ◽  
Sanja Vranes ◽  
Gabriele Centi ◽  
Stanislav Miertus
Keyword(s):  
Decision Support ◽  
Groundwater Remediation ◽  
Local Community ◽  
Decision Support Tool ◽  
Decision Makers ◽  
Relative Importance ◽  
Problem Complexity ◽  
Web Based ◽  
Support Tool ◽  
Promethee Ii

Groundwater remediation operation involves several considerations in terms of environmental, technological and socio-economic aspects. A decision support tool (DST) becomes therefore necessary in order to manage problem complexity and to define effective groundwater remediation interventions. CCR (Credence Clearwater Revival), a decision support tool for groundwater remediation technologies assessment and selection, has been developed to help decision-makers (site owners, investors, local community representatives, environmentalists, regulators, etc.) to assess the available technologies and select the preferred remedial options. The analysis is based on technical, economical, environmental and social criteria. These criteria are ranked by all involved parties to determine their relative importance for a particular groundwater remediation project. The Multi-Criteria Decision Making (MCDM) is the core of the CCR using the PROMETHEE II algorithm.

Predictive data analytics for contract renewals: a decision support tool for managerial decision-making

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Serhat Simsek ◽  
Abdullah Albizri ◽  
Marina Johnson ◽  
Tyler Custis ◽  
Stephan Weikert
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Organizational Performance ◽  
Predictive Analytics ◽  
Design Science ◽  
Decision Support Tool ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
Content Type ◽  
Support Tool

PurposePredictive analytics and artificial intelligence are perceived as significant drivers to improve organizational performance and managerial decision-making. Hiring employees and contract renewals are instances of managerial decision-making problems that can incur high financial costs and long-term impacts on organizational performance. The primary goal of this study is to identify the Major League Baseball (MLB) free agents who are likely to receive a contract.Design/methodology/approachThis study used the design science research paradigm and the cognitive analytics management (CAM) theory to develop the research framework. A dataset on MLB's free agents between 2013 and 2017 was collected. A decision support tool was built using artificial neural networks.FindingsThere are clear links between a player's statistical performance and the decision of the player to sign a new offered contract. “Age,” “Wins above Replacement” and “the team on which a player last played” are the most significant factors in determining if a player signs a new contract.Originality/valueThis paper applied analytical modeling to personnel decision-making using the design science paradigm and guided by CAM as the kernel theory. The study employed machine learning techniques, producing a model that predicts the probability of free agents signing a new contract. Also, a web-based tool was developed to help decision-makers in baseball front offices so they can determine which available free agents to offer contracts.

scholarly journals DEVELOPMENT AND TEST OF A DECISION SUPPORT TOOL FOR HOSPITAL HEALTH TECHNOLOGY ASSESSMENT

2012 ◽  
Vol 28 (4) ◽  
pp. 460-465 ◽  
Author(s):  
Laura Sampietro-Colom ◽  
Irene Morilla-Bachs ◽  
Santiago Gutierrez-Moreno ◽  
Pedro Gallo
Keyword(s):  
Decision Support ◽  
Platelet Rich Plasma ◽  
Decision Support Tool ◽  
Two Dimensions ◽  
Decision Makers ◽  
Process Of Care ◽  
Support Tool ◽  
Health Technologies ◽  
A Value ◽  
Benefit Patient

Objective: To develop and test a decision-support tool for prioritizing new competing Health Technologies (HTs) after their assessment using the mini-HTA approach.Methods:A two layer value/risk tool was developed based on the mini-HTA. The first layer included 12 mini-HTA variables classified in two dimensions, namely value (safety, clinical benefit, patient impact, cost-effectiveness, quality of the evidence, innovativeness) and risk (staff, space and process of care impacts, incremental costs, net cost, investment effort). Weights given to these variables were obtained from a survey among decision-makers (at National/Regional level and hospital settings). A second layer included results from mini-HTA (scored as higher, equal or lower), which compares the performance of the new HT (in terms of the abovementioned 12 variables) with the available comparator. An algorithm combining the first (weights) and second (scores) layers was developed to obtain an overall score for each HT, which was then plotted in a value/risk matrix. The tool was tested using results from the mini-HTAs for three new HTs (Surgical Robot, Platelet Rich Plasma, Deep Brain Stimulation).Results: No significant differences among decision-makers were observed as regards the weights given to the 12 variables, therefore, the median aggregate weights from decision-makers were introduced in the first layer. The dot plot resulting from the mini-HTA presented good power to visually discriminate between the assessed HTs.Conclusion: The decision-support tool developed here makes possible a robust and straightforward comparison of different competing HTs. This facilitates hospital decision-makers deliberations on the prioritization of competing investments under fixed budgets.

scholarly journals A Pareto Based Multi-Objective Evolutionary Algorithm Approach to Military Installation Rail Infrastructure Investment

2019 ◽  
Vol 7 (2) ◽  
pp. 64-75
Author(s):  
Eugene Lesinski ◽  
Steven Corns
Keyword(s):  
Decision Support ◽  
Evolutionary Algorithm ◽  
Lower Cost ◽  
Decision Support Tool ◽  
Decision Makers ◽  
Support Tool ◽  
Track Maintenance ◽  
Multi Objective ◽  
Military Installation ◽  
Prioritization Scheme

Decision making for military railyard infrastructure is an inherently multi-objective problem, balancing cost versus capability. In this research, a Pareto-based Multi-Objective Evolutionary Algorithm is compared to a military rail inventory and decision support tool (RAILER). The problem is formulated as a multi-objective evolutionary algorithm in which the overall railyard condition is increased while decreasing cost to repair and maintain. A prioritization scheme for track maintenance is introduced that takes into account the volume of materials transported over the track and each rail segment’s primary purpose. Available repair options include repairing current 90 gauge rail, upgrade of rail segments to 115 gauge rail, and the swapping of rail removed during the upgrade. The proposed Multi-Objective Evolutionary Algorithm approach provides several advantages to the RAILER approach. The MOEA methodology allows decision makers to incorporate additional repair options beyond the current repair or do nothing options. It was found that many of the solutions identified by the evolutionary algorithm were both lower cost and provide a higher overall condition that those generated by DoD’s rail inventory and decision support system, RAILER. Additionally, the MOEA methodology generates lower cost, higher capability solutions when reduced sets of repair options are considered. The collection of non-dominated solutions provided by this technique gives decision makers increased flexibility and the ability to evaluate whether an additional cost repair solution is worth the increase in facility rail condition.

scholarly journals An integrated custom decision-support computer aided facility management informative system for healthcare facilities and analysis

2019 ◽  
Vol 10 (1) ◽  
pp. 135-145 ◽  
Author(s):  
Ernesto Iadanza ◽  
Alessio Luschi
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
Healthcare Facility ◽  
Facility Management ◽  
Third Party ◽  
Complete Analysis ◽  
Support Tool ◽  
Healthcare Facilities ◽  
Computer Aided ◽  
System Maps

Abstract This article presents a Computer Aided Facility Management informative system which can output Key Performance Indicators and quantitative parameters about the analysed healthcare facility. The designed system is a self-sufficient application able to manage and analyse digital plans of hospital buildings with no need of third-party plugins or licenses. The system maps hospital’s inner organisation, destinations of use and environmental comforts giving quantitative, qualitative and graphical reports. The core database is linked to other existing hospital databases, so that the system can act as a central control cockpit. Outputs can be used by top-management and decisional staff as a decision-support tool in order to improve hospital’s structure and organisation and to reduce the major workflow risks. Furthermore, many plug-ins and modules have been developed through the years which can be easily linked to the main application thanks to its REST architecture, and which contribute to a complete analysis and management of the healthcare facilities.

Benchmarking contractors’ financial performance: case study of Singapore

2020 ◽  
Vol 25 (2) ◽  
pp. 183-199 ◽  
Author(s):  
Zhe Zhang ◽  
Zhi Ye Koh ◽  
Florence Ling
Keyword(s):  
Decision Support ◽  
Decision Tree ◽  
Financial Performance ◽  
Decision Support Tool ◽  
International Standards ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Content Type ◽  
Support Tool ◽  
Public Agency

Purpose This study aims to develop benchmarks of the financial performance of contractors and a decision support tool for evaluation, selection and appointment of contractors. The financial benchmarks allow contractors to know where they are relative to the best-performing contractors, and they can then take steps to improve their own performance. The decision support tool helps clients to decide which contractor should be awarded the project. Design/methodology/approach Financial data between 2013 and 2015 of 44 Singapore-based contractors were acquired from a Singaporean public agency. Benchmarks for Z-score and financial ratios were developed. A decision tree for evaluating contractors was constructed. Findings This study found that between 57% and 64% of contractors stayed in the financially healthy zone from 2013 to 2015. Ratios related to financial liabilities are relatively bad compared with international standards. Research limitations/implications The limitation is that the data is obtained from a cross-sectional survey of contractors’ financial performance in Singapore over a three-year period. Regarding the finding that ratios relating to financial liabilities are weak, the implication is that contractors need to reduce their financial liabilities to achieve a good solvency profile. Contractors may use the benchmarks to check their financial performances relative to that of their competitors. To reduce financial risks, project clients may use these benchmarks to examine contractors’ financial performance. Originality/value This study provides benchmarks for contractors and clients to examine the financial performance of contractors in Singapore. A decision tree is provided to aid clients in making decisions on which contractors to appoint.

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