Business Intelligence: How Sport Scientists Can Support Organization Decision Making in Professional Sport

2019 ◽  
Vol 14 (4) ◽  
pp. 544-546 ◽  
Author(s):  
Patrick Ward ◽  
Johann Windt ◽  
Thomas Kempton
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Data Collection ◽  
Business Intelligence ◽  
Professional Sport ◽  
Data Systems ◽  
Decision Support Model ◽  
Systematic Analysis ◽  
Domain Specific ◽  
Specific Expertise

The application of scientific principles to inform practice has become increasingly common in professional sports, with increasing numbers of sport scientists operating in this area. The authors believe that in addition to domain-specific expertise, effective sport scientists working in professional sport should be able to develop systematic analysis frameworks to enhance performance in their organization. Although statistical analysis is critical to this process, it depends on proper data collection, integration, and storage. The purpose of this commentary is to discuss the opportunity for sport-science professionals to contribute beyond their domain-specific expertise and apply these principles in a business-intelligence function to support decision makers across the organization. The decision-support model aims to improve both the efficiency and the effectiveness of decisions and comprises 3 areas: data collection and organization, analytic models to drive insight, and interface and communication of information. In addition to developing frameworks for managing data systems, the authors suggest that sport scientists’ grounding in scientific thinking and statistics positions them to assist in the development of robust decision-making processes across the organization. Furthermore, sport scientists can audit the outcomes of decisions made by the organization. By tracking outcomes, a feedback loop can be established to identify the types of decisions that are being made well and the situations where poor decisions persist. The authors have proposed that sport scientists can contribute to the broader success of professional sporting organizations by promoting decision-support services that incorporate data collection, analysis, and communication.

scholarly journals Implementasi Metode SMARTER Untuk Rekomendasi Penerima Bantuan Raskin Masa Covid 19

2021 ◽  
Vol 5 (2) ◽  
pp. 549
Author(s):  
Julfikar Rahmad ◽  
Volvo Sihombing ◽  
Masrizal Masrizal
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Rural Areas ◽  
Lower Class ◽  
Developed Countries ◽  
Decision Support Model ◽  
Head Of Household ◽  
Classic Problem ◽  
The Government ◽  
The Right

The problem of poverty is a classic problem that occurs in every country, both developed countries and developing countries like Indonesia. In every country, there are many programs carried out by the government to overcome the problem of poverty, one of which is the RASKIN program carried out by the Indonesian government. The method used to complete this research is SMARTER (Simple Multi Attribute Rating Technique Exploiting Ranks). During the Covid 19 pandemin, which is currently happening, various kinds of assistance are needed for middle and lower class people in rural areas, thus to distribute assistance, assistance distribution techniques are needed so that it reaches the right people. The SMARTER method was chosen because it is a form of decision support model used in decision making with multi attributes that will be used to solve decision-making problems. The research was conducted in Sei Beluru Village, Meranti District, Asahan Regency. In Sei Beluru Village, several criteria were obtained from direct observation of the field, namely the area of the house floor, the type of floor of the house, the type of house wall, the toilet facilities, the source of drinking water, lighting, materials. fuel used, frequency of eating, ability to buy meat, ability to buy clothes, ability to seek treatment, monthly income, education of the head of household, ownership of assets. Decision support systems using the Smarter method are able to analyze data on people who are entitled to receive Raskin assistance. The results obtained from this study are that from several prospective recipients of Raskin assistance with the specified criteria, it is found that the most prioritized alternative has the highest value of 0.603 using the Smarter method.

scholarly journals Auxiliary Decision Support Model of Sports Training Based on Association Rules

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Changnian Zhang ◽  
MeiJie Li ◽  
Hui Wang ◽  
Ning Wang
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Association Rules ◽  
Human Body ◽  
Movement Trajectory ◽  
Classification Rules ◽  
Sports Training ◽  
Decision Support Model ◽  
Discriminative Ability ◽  
Support Model

In sports or fitness training, nonstandard movements will affect the training effect and even lead to sports injuries. However, the standard movements of various sports activities need professional guidance, so it is difficult to find out whether the movements are standard or not. In recent years, body pose estimation has become a hot topic in computer vision research. A deep learning model can effectively identify the human nodes and movement trajectory in pictures or videos and evaluate the movements of the target human body. However, the movement process is generally covered by others or the situation of nearby personnel, which leads to the deviation of the movement recognition of the human body and affects the evaluation of the movement. Thus, it is unable to effectively correct the wrong movement, but will mislead the training personnel. Therefore, this paper proposes a novel decision support model for sports training based on association rules. We use posterior probability settings to reveal the weights of the discriminative ability of attribute items and set the classification performance to reflect the weights of three measures to evaluate credit contribution. Thus, the learning threshold setting reflects the weight of the decision-making ability of sports training. Furthermore, compared with traditional association rules, attribute items, frequent item sets, and classification rules that can improve the decision-making performance of sports training are discovered, which complement the deficiencies of different measures. Finally, using the weighted voting strategy to fuse the decision-making information of the classification rules, we can effectively assist in sports training so that the coach can work out corresponding countermeasures and realize scientific management.

Tailorable Technologies for Improving Business Intelligence Systems

2021 ◽  
pp. 560-575
Author(s):  
Shah J. Miah
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Conceptual Framework ◽  
Business Intelligence ◽  
Cost Effective ◽  
Business Owners ◽  
Business Intelligence Systems ◽  
Effective Operation

The Australian farm-based businesses can be benefited from specially designed applications for cost-effective operation while maximizing profits to survive in economic and environmental crises. For decision support, existing business intelligence systems (BIS) approaches scarcely deal with specific user's provisions to adjust changing situations in decision making, without extra technical exertions. In this chapter, the authors describe a conceptual framework of tailorable BIS solution that is based on case study findings in that the highlighted requirements are relevant to address changing situations through enhancing end user's engagement. The activities of end user's engagement supported through the use of tailorable features that reinforce a shift from the traditional BIS process to a new provision where business owners can actively involve in adjusting their features to their decision support.

scholarly journals Two-Envelope System for Consultant Selection using Weighted Sum Model

2018 ◽  
Vol 7 (4.27) ◽  
pp. 121
Author(s):  
Mohd Faizal Bin Omar ◽  
Bambang Trigunarsyah ◽  
Johnny Wong
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Model Building ◽  
Classical Problem ◽  
Quality Criteria ◽  
Weighted Sum ◽  
Decision Support Model ◽  
User Requirement ◽  
Study Approach ◽  
Technical Department

Consultant Selection is one of a classical problem in Multi Criteria Decision Making (MCDM). Most of the literature in Operation Research only concentrates on model building rather than developing an inclusive analytic tool that extends to a Decision Support System (DSS). In this paper, we deploy a case study approach to understand the user requirement for DSS development. We observe the process of consultant selection and the decision making at one of the technical department which involve in the infrastructure project in Malaysia. A two-envelope system and a simple Weighted Sum Model are currently in use. We demonstrate the abstraction and application based on two case projects. Sensitivity analysis is also performed and the result shows that the decision changed if it is solely based on fees or with minimal quality criteria.  Finally, we gather the findings from the organizational flows, user modelling and decision making process in order to benchmark with our future works. This will helps us to better understand and develop an improved decision support model or tools for consultant selection problem. 

A decision-making model for the rework of defective products

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
João Cláudio Soares ◽  
Anabela Pereira Tereso ◽  
Sérgio Dinis Sousa
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Decision Model ◽  
Cost Models ◽  
Total Quality ◽  
Decision Support Model ◽  
Quality Cost ◽  
Defective Items ◽  
Content Type ◽  
Quality Costs

PurposeThis paper proposes a decision support model that can be used to help decide the destination of defective products, for mass production industries. The objective of this model is to reduce the cost of the defect, and consequently reduce the total quality costs.Design/methodology/approachThe decision model was developed based on the theory of quality costs and decision-making models, considering the practical aspects of reality through data collection, observation and experience in Industrial Pole of Manaus (Brazil) industries. A decision model adjusted to reality assists in the construction of the decision process, indicating the facts, data collection and the planning of the actions to choose the best alternative.FindingsThe specific contributions of this research are: (1) define a sequential structure of actions, effects and costs associated with defective items; (2) allow a comprehensive approach to failure costs, including various elements of lost opportunity costs; (3) minimize failure costs, and consequently reduce total quality costs, without necessarily investing in prevention and assessment; (4) describe the use and application of the built theory; (5) identify the quality cost elements most representative in existence of defective items; and (6) identify improvement points in the management of possible future defective items.Originality/valueMuch of the work of implementation of quality cost models do not emphasize the analysis of the destination of defective items. Also, there are no studies that use decision models with identification, accounting and evaluation of effects and criteria of quality, productivity and cost to define the destination of manufacture defective items.

scholarly journals How to Discourage Adversaries From Affecting Decision Outcomes of a Repeated Patent Application Decision--Making Process

2021 ◽  
Author(s):  
Willem van der Sluis
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Maker ◽  
Patent Application ◽  
Decision Making Process ◽  
Sequential Decision ◽  
Decision Support Model ◽  
Application Process ◽  
Decision Outcomes ◽  
Application Decision

Outcomes of repeated decision--making processes may be affected by adversarial actors, without being noticed. Adversaries may try to gain knowledge about a particular decision--making process, identify its decision--makers, and guess which underlying decision support model is used. Then they can simulate the process, and craft different scenarios to affect its decision outcomes. Therefore, designers of decision support systems need to incorporate this in the decision modeling phase. The purpose of this study is to demonstrate this for the repeated decision--making in a patent application process. In this process, two sequential decision outcomes can be affected by adversarial actors: a company's decision to which type of patent office to send a patent request to, and the decision of a specialized patent officer to grant an application, or not. It is motivated that the company's decision--maker is \emph{bounded} rational. A theory for information--theoretic bounded rational decision--making under uncertainty proposed by Ortega et al.\ is adopted to model this type of decision--maker. A framework is provided to simulate a number of scenarios that adversaries may deploy to affect decision outcomes of a repeated patent application decision--making process. The framework is also utilized for statistically testing the presence of the scenarios, and to demonstrate how to discourage adversaries from deploying them.

scholarly journals Assistance Decision Model for SMEs

2020 ◽  
Vol 8 (5) ◽  
pp. 1248-1255
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Support System ◽  
Research Method ◽  
Decision Model ◽  
Financial Assistance ◽  
System Model ◽  
Decision Making Process ◽  
Decision Support Model ◽  
The Government

SMEs in Indonesia are one of the economic drivers of the nation. Its presence and development shows a sizeable contribution to Gross Domestic Income (GDP) each year. With this background, the Indonesian government provides stimulants in the form of financial assistance for the special SMEs for beginner SMEs. The government is encouraging the growth of SMEs by providing assistance to SMEs. During this time the process of determining the provision of assistance is done manually so that it is less effective and efficient. Therefore, the purpose of this study is to make a decision support model for the Ministry of SMEs to provide financial assistance to SMEs. The research method uses AHP and Promethee. Based on the results and discussion produced a Decision Support System model to help the Ministry of SMEs provide financial assistance to SMEs. The conclusion of this study is the suitability of SME ministry staff with the resulting model in the form of ease in the decision making process of providing assistance to SMEs.

Closing the Gap between Data Mining and Business Users of Business Intelligence Systems

2012 ◽  
Vol 3 (4) ◽  
pp. 14-53 ◽  
Author(s):  
Ana Azevedo ◽  
Manuel Filipe Santos
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Business Intelligence ◽  
Easy Access ◽  
Complete Knowledge ◽  
Business Intelligence Systems ◽  
Closing The Gap

Since Lunh first used the term Business Intelligence (BI) in 1958, major transformations happened in the field of information systems and technologies, especially in the area of decision support systems. BI systems are widely used in organizations and their importance is recognized. These systems present themselves as essential parts of a complete knowledge of business and an irreplaceable tool in the support to decision making. The dissemination of data mining (DM) tools is increasing in the BI field, as well as the acknowledgment of the relevance of its usage in enterprise BI systems. BI tools are friendly, iterative, and interactive, allowing business users an easy access. The user can manipulate directly data, having the ability to extract all the value contained into that business data. Problems noted in the use of DM in the field of BI is related to the fact that DM models are complex in order to be directly manipulated by business users, not including BI tools. The nonexistence of BI tools allowing business users the direct manipulation of DM models was identified as the problem. More of these issues, possible solutions and conclusions are presented in this article.

SISTEM PENDUKUNG KEPUTUSAN PENENTUAN PRIORITAS PEMBANGUNAN DAERAH MENERAPKAN METODE PREFERENCE SELECTION INDEX (PSI)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Martina Klarasia Siahaan ◽  
Mesran Mesran ◽  
Sumiaty Adelina Hutabarat ◽  
Joli Afriany
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Data Collection ◽  
Decision Support System ◽  
Support System ◽  
System Development ◽  
Selection Index ◽  
Fund Allocation ◽  
Collection Data ◽  
Psi Method

This study aims to determine development priorities in 2018 Kota Medan District covering planning, use and evaluation of village development. This study uses qualitative research, with a case study strategy. The technique of collecting data is done by interviews, observation and documentation. Test the validity of data by triangulating data sources and data collection techniques. Data analysis uses determination techniques through data collection, data reduction, data presentation and conclusion. Evaluations for the Village Fund for 2017 include constraints faced during the implementation of development and allocation of village funds such as a lack of sense of responsibility between village officials in managing village funds, people who care about development are still few, and there is a lack of meetings to deliver information on village fund allocation to the community. The decision support system for determining village development priorities has stages, starting from selecting criteria, aspects to assessments that have been set, decision making difficulties in determining priorities and calculating weights. Related to this, the Preference Selection Index (PSI) method can be used to solve the problem. The results of the process are in the form of village rankings as a recommendation for decision making to choose as suitable occupies the designated fields. The results of the system supplementation, it was concluded that the use of this method can help the process of making prioritization of development, can be studied, quite easy to use, and produce information used.Keywords: Decision Support System, Development Priority, PSI

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