Competing on Performance on the Global Marketplace: Applying Business Analytics as a Robust Decision Tool

Competing on Performance on the Global Marketplace: Applying Business Analytics as a Robust Decision Tool

Rajagopal (EGADE Business School, Tecnologico de Monterrey, Mexico City, Mexico & Boston University, USA)
Copyright: © 2017 |Pages: 13
DOI: 10.4018/978-1-5225-0902-8.ch001
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Globalization has triggered many new ways for companies to improve their business performance and stay competitive in the marketplace. Initially most companies strengthen their capability and competence towards developing competitive differentiation through continuous innovation to stay competitive and build sustainable brand image for their products and services. Over the mid-twentieth century, the information technology has made manifold advance proving scope for the companies to access the market information, carry out data analytics to meet their corporate requirements, and to derive right business decision for developing right competitive strategies. Accordingly, the new approaches of decision support systems have emerged and companies are interestingly adapting to the new environment of information analysis. The Big Data, business analytics, and business intelligence approaches have enveloped the business-to-business and business-to-customer industries as a strong decision making tool of the twenty-first century. This chapter discusses the state-of-art approaches and their impact on market competitiveness of the companies.
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Globalization has driven tremendous entrepreneurial dynamism in the marketplace down-to the bottom-of-the-pyramid of the market strata causing bi-directional movements of business forces. Most multinational companies are aiming at expanding their business activities in the local markets, while the enterprises operating at the niche are trying to go beyond territorial boundaries. Consequently, the marketplace today has been congested with the overflowing brands, corporate interventions, instability in demand, and chaos in making business decisions. Every company, irrespective of its operational size and investment, is competing today for improving its performance and stay competitive in the marketplace. Decision making has turned complicated for the companies as the uncertainties in the market increased discretely across the destination in the world. The term decision making has become more stakeholder oriented among the firms since the mid-twentieth century. Indeed decision terminology was imported from public administration into the business world as it was needed to treat decision making more bureaucratically to manage the result oriented strategies of the companies to gain the competitive lead. Further decision making incorporated the terms like resource allocation and policy making, shifting the managerial thought process, and the role toward a series of interlinked actions that envelopes any decision in a company. Yet, decision making in business emerges out of a conventional process to a broad competitive market pursuit, putting the managers of a company on pretest to implement the decision in a controlled situation, measure the results, and take the business decisions at the macro level across the markets and consumer segments. All business decision needs to be calculated meticulously for the potential risks along with an indulging human behavior. The advances in technology that support the cognitive processes have improved the decision making in complex business situations. The business decisions today are largely supported by scientific data analytics than subjective judgments. The data based decision support systems are reliable provided the quality of data is acceptable and has passed through the reliability tests. Such information analysis could lead executives to make well-enough decisions and test the decision-response matrices before implementing the decisions at macro level (Buchanan and O’Connell, 2006)

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