Decision support system for a SME in the restaurant sector: Development of a prototype

doi:10.23919/CISTI.2017.7975831

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Decision support system for a SME in the restaurant sector: Development of a prototype

Proceedings Article•DOI•

Decision support system for a SME in the restaurant sector: Development of a prototype

Juan Edel Gutierrez Neyoy¹, Luis-Felipe Rodríguez¹, Luis A. Castro¹•Institutions (1)

Sonora Institute of Technology¹

21 Jun 2017-pp 1-6

TL;DR: The results of this work show that the company (being a SME) can improve in terms of competitive advantage through this tool of business intelligence and cross the barriers where most SMEs are stagnant in Mexico.

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Abstract: Business intelligence serves a great purpose in any business, but is usually omitted or ignored by SMEs due to lack of knowledge or simply because the owners do not consider it necessary for a medium to long-term plan term. In the long run, businesses usually fail to make a profit or cannot continue, and end up without even knowing what happened. The information generated by a company could serve as a starting point for good and solid decision-making, but the culture that dominates the SMEs of any industry leaves important information without registration or connection, leaving them to work based only on evidence and errors and Mostly "luck". This paper proposes a prototype of decision support system for a SME in the restaurant sector. The results of this work show that the company (being a SME) can improve in terms of competitive advantage through this tool of business intelligence and cross the barriers where most SMEs are stagnant in Mexico.

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Journal Article•DOI•

A Review of Business Intelligence and Analytics in Small and Medium-Sized Enterprises

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Marilex Rea Llave¹•Institutions (1)

University of Agder¹

01 Jan 2019-International Journal of Business Intelligence Research

TL;DR: This study collects, categorizes, synthesizes, and analyzes 78 articles related to BI&A in SMEs, and presents the research gaps and suggestions for future research to facilitate the progression of BI&a in SME research.

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Abstract: Business intelligence and analytics (BI&A) has become a cornerstone of many organizations in making informed decisions. Despite the importance of small and medium-sized enterprises (SMEs) to all wo...

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11 citations

Journal Article•DOI•

Identifying the main factors involved in business intelligence implementation in SMEs

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Juan Alexis Becerra-Godínez¹, José Leonardo Serralde-Coloapa¹, Martin Salvador Ulloa-Márquez¹, Abraham Gordillo-Mejía¹, Elizabeth Acosta-Gonzaga¹ - Show less +1 more•Institutions (1)

Instituto Politécnico Nacional¹

01 Feb 2020-Bulletin of Electrical Engineering and Informatics

TL;DR: The results showed main factors that influence the adoption of BI technologies in SMEs as well as recommendations given by several authors to ensure success in the process.

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Abstract: In recent years, the use of information and communication technology (ICT) tools has been recognized as a critical element for the development of enterprises; being mainly exploited by large companies. However, small and medium enterprises (SMEs) have yet opportunities to take advantage of them; this is the case of the implementation and usage of business intelligence (BI), which is a term that encompasses applications, tools, and methodologies that support decision-making process at a managerial level. Nevertheless, so far there is not a clear approach for its adoption in SMEs, for this reason, this work aims to identify the main factors involved in Business Intelligence implementation in SMEs through a literature review. Information for the analysis was gathered from scientific databases. The results showed main factors that influence the adoption of BI technologies in SMEs as well as recommendations given by several authors to ensure success in the process.

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10 citations

Cites background from "Decision support system for a SME i..."

...Benefits Reference Access to knowledge in real time [35, 47] Foment of customer satisfaction [35, 46, 48] Improvement of knowledge management [35, 40, 49] Dissemination of best practices [35] Reduction of costs [35, 38] Facilitation of work [35, 38, 48, 49] Improve the diagnosis of data [35, 37, 42, 50] Detection of risky situations [16, 23, 33, 40] Provide a better internal understanding of the company [40] Optimization of economic and time resources to generate higher profit margins [19, 20, 33, 38, 42, 51] Facilitation the decision making of the company [20, 33, 42, 45, 48] Provide quality information, that is, errors-free and useful for interpreting the results [20, 39, 42, 48-50, 52] Improvement of productivity in the company [20] Promotion of a better performance of human resources [20] Provide dynamic and interactive reports for operators and managers [38] Provide detailed information [38, 48, 49] Provide an analysis view [38, 49, 50] Allowance of viewing changes in the environment [25] Flexibility for information access [42, 46, 49] Generation of different views of the information needed by the management [47] Creation of stages based on evolution trends [33] Support of profitability of knowledge [16]...
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...There are other BI studies in SMEs, which were developed for different sectors, such as the study by Gutiérrez, Rodríguez, & Castro [37], focused on proposing a model in the sales area of the SMEs’ restaurant sector....
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...There are other BI studies in SMEs, which were developed for different sectors, such as the study by Gutiérrez, Rodríguez, & Castro [37], focused on proposing a model in the sales area of the SMEs’ restaurant sector....
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References

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Open Access

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Book•

Building the data warehouse

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William H. Inmon

01 Jan 1992

TL;DR: This Second Edition of Building the Data Warehouse is revised and expanded to include new techniques and applications of data warehouse technology and update existing topics to reflect the latest thinking.

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Abstract: From the Publisher: The data warehouse solves the problem of getting information out of legacy systems quickly and efficiently. If designed and built right, data warehouses can provide significant freedom of access to data, thereby delivering enormous benefits to any organization. In this unique handbook, W. H. Inmon, "the father of the data warehouse," provides detailed discussion and analysis of all major issues related to the design and construction of the data warehouse, including granularity of data, partitioning data, metadata, lack of creditability of decision support systems (DSS) data, the system of record, migration and more. This Second Edition of Building the Data Warehouse is revised and expanded to include new techniques and applications of data warehouse technology and update existing topics to reflect the latest thinking. It includes a useful review checklist to help evaluate the effectiveness of the design.

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2,820 citations

"Decision support system for a SME i..." refers background in this paper

...They are subsets of data for the purpose of helping a specific area within the business to make better decisions [13]....
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Journal Article•DOI•

Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud

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Haluk Demirkan¹, Dursun Delen²•Institutions (2)

University of Washington¹, Oklahoma State University–Stillwater²

01 Apr 2013

TL;DR: A conceptual framework for DSS in cloud is proposed, a unique contribution of this paper is its perspective on how to servitize the product oriented DSS environment, and the opportunities and challenges of engineering service oriented D SS in cloud are demonstrated.

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Abstract: Using service-oriented decision support systems (DSS in cloud) is one of the major trends for many organizations in hopes of becoming more agile. In this paper, after defining a list of requirements for service-oriented DSS, we propose a conceptual framework for DSS in cloud, and discus about research directions. A unique contribution of this paper is its perspective on how to servitize the product oriented DSS environment, and demonstrate the opportunities and challenges of engineering service oriented DSS in cloud. When we define data, information and analytics as services, we see that traditional measurement mechanisms, which are mainly time and cost driven, do not work well. Organizations need to consider value of service level and quality in addition to the cost and duration of delivered services. DSS in CLOUD enables scale, scope and speed economies. This article contributes new knowledge in service science by tying the information technology strategy perspectives to the database and design science perspectives for a broader audience.

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521 citations

"Decision support system for a SME i..." refers background in this paper

...First, each sector or department of the company needs reliable and timely information to perform its work [4]....
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Book•

Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications

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Larissa Terpeluk Moss, Shaku Atre

01 Feb 2003

TL;DR: The authors walk readers through every step of the process--from strategic planning to the selection of new technologies and the evaluation of application releases and conclude by crystallizing their many years of experience in a list of dos, don'ts, tips, and rules of thumb.

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Abstract: From the Publisher: "If you are looking for a complete treatment of business intelligence, then go no further than this book. Larissa T. Moss and Shaku Atre have covered all the bases in a cohesive and logical order, making it easy for the reader to follow their line of thought. From early design to ETL to physical database design, the book ties together all the components of business intelligence." --Bill Inmon, Inmon Enterprises Business Intelligence Roadmap is a visual guide to developing an effective business intelligence (BI) decision-support application. This book outlines a methodology that takes into account the complexity of developing applications in an integrated BI environment. The authors walk readers through every step of the process--from strategic planning to the selection of new technologies and the evaluation of application releases. The book also serves as a single-source guide to the best practices of BI projects. Part I steers readers through the six stages of a BI project: justification, planning, business analysis, design, construction, and deployment. Each chapter describes one of sixteen development steps and the major activities, deliverables, roles, and responsibilities. All technical material is clearly expressed in tables, graphs, and diagrams. Part II provides five matrices that serve as references for the development process charted in Part I. Management tools, such as graphs illustrating the timing and coordination of activities, are included throughout the book. The authors conclude by crystallizing their many years of experience in a list of dos, don'ts, tips, and rules of thumb. The accompanying CD-ROMincludes a complete, customizable work breakdown structure. Both the book and the methodology it describes are designed to adapt to the specific needs of individual stakeholders and organizations. The book directs business representatives, business sponsors, project managers, and technicians to the chapters that address their distinct responsibilities. The framework of the book allows organizations to begin at any step and enables projects to be scheduled and managed in a variety of ways. Business Intelligence Roadmap is a clear and comprehensive guide to negotiating the complexities inherent in the development of valuable business intelligence decision-support applications. 0201784203B02112003

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464 citations

Additional excerpts

...The Extraction, Transformation, and Load (ETL) subsystem is the basis on which the Data Warehouse is implemented [12]....
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Posted Content•

The Impact of Business Analytics on Supply Chain Performance

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Peter Trkman¹, Kevin McCormack, Marcos Paulo Valadares de Oliveira², Marcelo Ladeira³•Institutions (3)

University of Ljubljana, Faculty of Economics¹, Universidade Federal do Espírito Santo², Universidade Federal de Minas Gerais³

01 Jan 2010-Social Science Research Network

TL;DR: The findings suggest the existence of a statistically significant relationship between analytical capabilities and performance and the moderation effect of information systems support is considerably stronger than the effect of business process orientation.

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Abstract: The paper investigates the relationship between analytical capabilities in the plan, source, make and deliver area of the supply chain and its performance using information system support and business process orientation as moderators. Structural equation modeling employs a sample of 310 companies from different industries from the USA, Europe, Canada, Brazil and China. The findings suggest the existence of a statistically significant relationship between analytical capabilities and performance. The moderation effect of information systems support is considerably stronger than the effect of business process orientation. The results provide a better understanding of the areas where the impact of business analytics may be the strongest.

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391 citations

Additional excerpts

...For example, Trkman demonstrates how the supply chain is optimized by including the use of Business Analytics in the redesign of the supply chain process, obtaining several benefits such as improvement in performance, better use of resources and avoiding downtime [14]....
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Book•

The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling

[...]

Ralph Kimball, Margy Ross

01 Jan 2013

TL;DR: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition is a complete library of updated dimensional modeling techniques, the most comprehensive collection ever.

...read moreread less

Abstract: Updated new edition of Ralph Kimball's groundbreaking book on dimensional modeling for data warehousing and business intelligence!The first edition of Ralph Kimball'sThe Data Warehouse Toolkitintroduced the industry to dimensional modeling, and now his books are considered the most authoritative guides in this space. This new third edition is a complete library of updated dimensional modeling techniques, the most comprehensive collection ever. It covers new and enhanced star schema dimensional modeling patterns, adds two new chapters on ETL techniques, includes new and expanded business matrices for 12 case studies, and more.Authored by Ralph Kimball and Margy Ross, known worldwide as educators, consultants, and influential thought leaders in data warehousing and business intelligenceBegins with fundamental design recommendations and progresses through increasingly complex scenariosPresents unique modeling techniques for business applications such as inventory management, procurement, invoicing, accounting, customer relationship management, big data analytics, and moreDraws real-world case studies from a variety of industries, including retail sales, financial services, telecommunications, education, health care, insurance, e-commerce, and moreDesign dimensional databases that are easy to understand and provide fast query response withThe Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition.

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372 citations

"Decision support system for a SME i..." refers methods in this paper

...A data warehouse helps the decision making process in the company in which it is used [11]....
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...DESIGN AND DEVELOPMENT To carry out the development of the prototype we take as reference the tasks proposed by Ralph Kimball as part of his methodology (these tasks can be seen in Figure 1)....
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...In particular, we followed the methodology proposed by Ralph Kimball [11]....
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