Business Analytics Success: A Conceptual Framework and an Application to Virtual Organizing

Business Analytics Success: A Conceptual Framework and an Application to Virtual Organizing

Hindupur Ramakrishna (University of Redlands, USA)
DOI: 10.4018/978-1-60566-070-7.ch013
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The chapter presents a conceptual framework that identifies technological and organizational factors that impact the success of business analytics (BA) use in organizations in general and virtual organizations in particular. The framework explores BA success through three business disciplines: Decision sciences (DS), information systems (IS), and management. We believe that BA success comes from proper interaction between the three disciplines. Though the concept of BA has been around for a long time in business literature, its full potential use has not been realized in organizations for a variety of reasons. The information and communication technologies (ICT) that have made virtual organizations, and flattening of the world possible have also created a better infrastructure/environment for use of BA by providing the capability to collect massive amounts of data and by providing easier-to-use analytic tools. Currently, BA is being touted as the next information technology (IT) capability that will generate considerable value including competitive advantage to businesses. In this chapter we present and discuss our framework, discuss its viability through existing examples of BA success, and finally apply the framework to a special emerging context in organizations, virtual organizing. Implications of this framework for identifying and filling research gaps in this area and implications for managers interested in exploring BA use in their organizations are presented
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Though the history of organizational/managerial decision-making is long, its movement from “decision-making as an art” to “decision-making as a science” is more recent. Parallel, and sometimes independent, developments in three fields have aided this evolution. Management theory focused on the typologies and processes of decision-making and the behavioral aspects (Henderson & Nutt, 1980; Kepner & Tregoe, 1965; Mintzberg et al, 1976; Simon, 1977; Tydeman et al, 1980)—the softer side. Decision Sciences (DS) as a field was formally defined in the early 1970s, and the field included the work done in management theory and extended it through the use of quantitative techniques—the harder side. Though quantitative techniques, mathematical and statistical, were available for use by organizations and managers, their use was not widespread due to the lack of availability and ease-of-use of the tools and data necessary for quantitative analysis. A parallel development in information systems (IS) that made the necessary tools and data available, and easier to use by most managers, made it possible for organizations to capture/collect/access massive amounts of data regarding the organizational processes and analyze them for decision-making through the use of quantitative analysis.

Business analytics (BA)—the use of analytic techniques (driven by data and quantitative analysis) for organizational/managerial decision-making, a new term that has been coined recently—is a result of the parallel developments in the three disciplines, Management, DS, and IS. History of analytic techniques and data to improve organizational decision-making can be traced to the 1960s to the development of the first decision support systems (DSS) (Power, 2001, 2002, and 20042004). Analytics has also been defined to be a subset of business intelligence (BI). BI includes both data access and reporting, and analytics. More formal definitions of BI and its essential components can be found in Negash and Gray (2003). The terms “data mining” and “business analytics” have also been used interchangeably in the literature (Kohavi, Rothleder, and Simoudis, 2002) to indicate the general process of investigation and subsequent analysis of data to identify the existence of new and meaningful trends.

Relatively few formal definitions of BA exist in the literature. Davenport and Harris (2007) define analytics as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.” Davenport & Harris further state that the “analytics may be input for human decisions or may drive fully automated decisions.” While data access and reporting help businesses understand “what happened,” and “what actions are needed,” analytics helps them to understand “why is this happening,” “what if these trends continue,” and perhaps forecast “what will happen next” (Davenport & Harris, 2007).

Prior work related to the Management, IS, and DS aspects of BA is extensive in each area. Success in decision-making and problem-solving (including success of different phases) and its relation to different problem-solving methods and individual and group behavior has been studied extensively in the Management literature. Data collection, storage, and access issues have been addressed extensively in IS literature. Extensive work on building a variety of quantitative models exists in DS (sometimes also referred to as Management Science or Operations Research) literature. Some literature also exists that integrates two disciplines – for example, group decision support systems (GDSS) work that integrates Management and IS aspects of BA. Davenport’s (2006) work is the first attempt to link explicitly the three disciplines critical to BA success. Davenport identified three key attributes for organizations to be analytically competitive – (1) widespread use of modeling and optimization, (2) an enterprise approach, and (3) senior executive advocates. In the same work, the author argues that organizational success in BA can result if analytics-minded leaders actively recruit analytically competent people who are proficient in the use of technology and can decide “when to run the numbers.”

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Editorial Advisory Board
Table of Contents
Knowledge Management and Virtual Organizations
Chapter 1
Fernando Garrigos
This chapter presents the interrelationships between professional virtual communities and social networks, and analyzes how, and in what ways, these... Sample PDF
Interrelationships Between Professional Virtual Communities and Social Networks, and the Importance of Virtual Communities in Creating and Sharing Knowledge
Chapter 2
Luis V. Casaló
The rapid growth of virtual communities has created a new interest in researchers. Indeed, understanding these communities is especially relevant... Sample PDF
The Role of Trust, Satisfaction, and Communication in the Development of Participation in Virtual Communities
Chapter 3
Cesar Camison
Organisations are finding it more difficult to keep abreast with the pace of change. The continuous rise of business opportunities and the increase... Sample PDF
Can Virtual Networks Encourage Knowledge Absorptive Capacity?
Chapter 4
Montserrat Boronat Navarro
In this study we adopt an inter-organizational view to examine virtual organizations. Thus, we understand this phenomenon as a strategic agreement... Sample PDF
Knowledge Integration Through Inter-Organizational Virtual Organizations
Chapter 5
Mark E. Nissen
In today’s increasingly networked world of organizational practice, information and computer technologies are enabling people and organizations to... Sample PDF
Visualizing Knowledge Networks and Flows to Enhance Organizational Metacognition in Virtual Organizations
Chapter 6
Eduardo Bueno Campos
The aim of this chapter is to deepen the concept of ‘Communities of Practice’ (CoPs) from the understanding of a reference framework for knowledge... Sample PDF
Model on Knowledge-Governance: Collaboration Focus and Communities of Practice
Chapter 7
Josep Capó-Vicedo
This chapter highlights the necessity of establishing relationships with other companies and external agents in order to empower the creation and... Sample PDF
Knowledge Management in SMEs Clusters
Chapter 8
Raquel Sanchis
This chapter presents a general overview of the relationships between information and communications technologies (ITCs) and the process of... Sample PDF
Tools for Supporting Knowledge Management: Knowledge Internalization Through E-Learning
Chapter 9
Cesar Camison, Carlos Devece, Daniel Palacios, Carles Camisón-Haba
In this chapter we describe a practical tool useful to managing knowledge in the firm. It has already been introduced and tested in several firms... Sample PDF
The Value of Virtual Networks for Knowledge Management: A Tool for Practical Development
Chapter 10
M. Eugenia Fabra, Cesar Camison
Companies are increasingly conscious of the fact that the achieving of their objectives, together with the improvement of their competitive... Sample PDF
Human Capital and E-Learning: Developing Knowledge Through Virtual Networks
Chapter 11
Júlio Da Costa Mendes
This chapter looks to analyse new paradigms in the relationship between public and private organisations towards tourism destinations. It proposes... Sample PDF
The Development of Knowledge and Information Networks in Tourism Destinations
Chapter 12
E. Claver-Cortés
Government agencies are being pressed to become more efficient. For this reason, e-government strategies result from the expectations from society... Sample PDF
E-Government Challenges: Barriers and Facilitators in Spanish City Councils
Chapter 13
Hindupur Ramakrishna
The chapter presents a conceptual framework that identifies technological and organizational factors that impact the success of business analytics... Sample PDF
Business Analytics Success: A Conceptual Framework and an Application to Virtual Organizing
Chapter 14
Andrew Targowski
This chapter provides theoretical analysis and synthesis of how computer applications are applied in problem-solving and decision-making in practice... Sample PDF
The Evolution from Data to Wisdom in Decision-Making at the Level of Real and Virtual Networks
Chapter 15
Editor Conclusions  (pages 278-279)
Cesar Camison
The study of virtual organizations encompasses several research fields, and the variables involved in each of them are sometimes closely related.... Sample PDF
Editor Conclusions
Chapter 16
Andrew P. Sage, Cynthia T. Small
This chapter describes a complex adaptive systems (CAS)-based enterprise knowledge-sharing (KnS) model. The CAS-based enterprise KnS model consists... Sample PDF
A Complex Adaptive Systems-Based Enterprise Knowledge Sharing Model
Chapter 17
James G. Williams, Kai A. Olsen
The Telecommunications Act of 1996 opened competition in the telecommunications market in the U.S. and forced the incumbent telecommunications... Sample PDF
Developing a Telecommunication Operation Support Systems (OSS): The Impact of a Change in Network Technology
Chapter 18
Tor Guimaraes
Emerging agent-based systems offer new means of effectively addressing complex decision processes and enabling solutions to business requirements... Sample PDF
Enabling the Virtual Organization with Agent Technology
Chapter 19
Jens Gammelgaard
In geographically dispersed organizations, like multinational corporations (MNCs), contextual gaps exist between senders and receivers of knowledge.... Sample PDF
Virtual Communities of Practice: A Mechanism for Efficient Knowledge Retrieval in MNCs
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