A Framework for Boosting Revenue Incorporating Big Data

Laura Lynn Segarra,John Elabd,Hamed Almalki,Moaad Alrasheed,Luis Rabelo,Jonathan Gonzalez,Michal Marczewski

doi:10.24840/2183-0606_004.001_0005

Laura Lynn Segarra, John Elabd + Show 5 more

Open Access

https://doi.org/10.24840/2183-0606_004.001_0005

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Abstract

Complex industry partnerships, innovative strategies, and cross-cutting industry competition, challenge business leaders in making strategic and operational decisions that support growth and competitiveness. Companies seeking to inform their business decisions by leveraging “big data” face challenges in processing and analyzing such large and rapid datasets. However leveraging big data can create value for businesses. Although various frameworks exist for implementing analytics, few accommodate the implementation of big data analytics. Our goal is to develop a framework by studying big data on a micro and macro level and examining how companies can use big data to boost revenue through creating value. This research is augmented by an in-depth examination of industry giant Amazon.com. Our results provide a framework that enhances traditional analytical frameworks through the integration of big data analytics. Our findings indicate that an integrated framework provides enhanced insights to decision makers seeking to create value for their businesses.

Highlights

Business leaders face many challenges in establishing and maintaining a competitive advantage in today’s fierce and cross-cutting industry
The collection and interpretation of big data is accomplished through strong computing ability that actively engages many digital data streams and uses algorithms to analyze the data in search of meaningful and useful correlations (Davenport, 2014)
We propose a business enterprise framework for boosting revenue that incorporates the use of big data analytics

Summary

Introduction

Business leaders face many challenges in establishing and maintaining a competitive advantage in today’s fierce and cross-cutting industry. Advancements in technology and management approaches, such as Business Intelligence Systems and Six Sigma programs, have allowed business leaders to make more informed decisions through the use of data analytics and tools that integrate performance metrics, scorecards, and management reporting (Davenport, 2006). As technology continues to advance, the of sheer volume of information generated, variety of sources data is generated from, and velocity in which data is generated, pose challenges for businesses that seek to capture, store, manage, and analyze data that is both large in scope and scale. Giving rise to the term “Big Data”, technological advancements have paved the way for data to grow exponentially on a ISSN 2183-0606 http://creativecommons.org/licenses/by/3.0. According to Gobble (2013), the term “Big Data” refers to the case of having extremely large data sets that require innovative methods in the collection, storage, organization, analysis and sharing of such data. Key sources of big data include public data, private data, data exhaust, community data, and selfquantification data (George et al, 2014)

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