Leveraging Process Innovation with Business Analytics

Leveraging Process Innovation with Business Analytics

Marcos Paulo Valadares de Oliveira (Univeridade Federal do Espírito Santo, Vitória, Brazil), Claudia Xavier Cavalcanti (Universidade Federal do Espírito Santo, Vitória, Brazil), Marcelo Bronzo Ladeira (Universidade Federal de Minas Gerais, Belo Horizonte, Brazil) and Kevin P. McCormack (Northwood University, Midland, MI, USA)
Copyright: © 2016 |Pages: 13
DOI: 10.4018/IJDSST.2016070104
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Abstract

Although recognized as increasingly relevant, the relationships between analytical orientation and process innovation are still unclear, specifically the role of analytical resources and capabilities in this association. This paper presents the results of empirical research conducted to investigate these complex links. The empirical data was drawn from 81 companies of different sectors in Brazil. Data analysis was mainly based on path analysis with structural equation modeling. The findings of this study indicate that analytical orientation can leverage process innovation. Moreover, information quality is somehow a more valuable resource to analytical orientation than information technology, and that analytical capabilities, especially analytical leadership, were proven to be more important to sustain analytical orientation than companies' analytical resources. Another important result, also with considerable repercussion in future research on the theme, was the predictive relevance of analytical capabilities for analytical orientation. This was much higher than the predictive relevance shown by analytical resources.
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1. Introduction

The Information Technology (IT) literature has long emphasized the importance of IT-enabled quality information for firms operating amidst competitive environments (Davern & Kauffman, 2000; Melville, Kraemer, & Gurbaxani, 2004; Mithas, Ramasubbu, & Sambamurthy, 2011). The use of Analytics is often referred as the use of techniques, technologies, systems, practices, methodologies, and applications that analyze critical business information to help an enterprise better understand its business and market, and make timely business decisions. In addition, Analytics includes business-centric practices and methodologies that can be applied to various high-impact applications such as e-commerce, market intelligence, e-government, healthcare, and security (Chen, Chiang, & Storey, 2012).

Business analytics is being shown as an effective alternative for organizations, to make decisions and take actions that would be almost impossible otherwise (Davenport & Harris, 2007). Despite the recognition about the importance of Business Analytics and the significant amounts of investments made by companies in analytical resources (Kiron, Prentice, & Ferguson, 2014), the gap between current and potential use of analytics – specially considering process innovation – remains wide (Cokins, 2013).

The resource based theory (RBT) suggests that competitive advantage is a result of firms possessing heterogeneous resources and capabilities and encourages organizational acquisition and development of unique, valuable, and scarce resources, including skills, technologies, and know-how (Barney, 1991; Wernerfelt, 1984). Building causal links between resources and the generation of productive opportunities for growth and innovation, in a seminal work, Penrose (1959) supports the idea that firms can create economic value not due to mere possession of resources, but due to effective and innovative management of resources. This argument is grounded on the idea that managers, by functioning as catalysts in the conversion of firm’s resources into firm capabilities, can exploit new combinations of resources and capabilities that lead to innovation and economic value creation.

The empirical relationship between business analytics and overall performance was already proven as significant (Bronzo et al., 2013; Davenport, 2013b; Khan, 2013; Klatt, Schlaefke, & Moeller, 2011; Schläfke, Silvi, & Möller, 2013; Trkman, Ladeira, Oliveira, & McCormack, 2012; Trkman, McCormack, de Oliveira, Ladeira, & Oliveira, 2010) but its impact over process innovation specifically remains unclear. Aiming to clarify this issue, this research paper is based on Penrose’s and considers the premise that analytical resources (i.e. technology and information quality) and analytical capabilities (i.e. skills and leadership) are both taken as antecedents of analytical orientation which hypothetically lead to process innovation.

The aim of this paper is to delve deeper into the relationship between Analytical Orientation and Process Innovation. The idea behind the model specification (and the theory that support the relationships investigated) is that in order to be more innovative, companies may take the advantage of an adequate balancing between its investments in analytical resources and capabilities and build a more consistent analytic orientation.

The rest of the paper is organized as follows: it begins by contextualizing the concept of business analytics. Next the hypothetical model is presented describing the relationship between analytical orientation and process innovation. Further the methodology and data analysis are presented and the hypothetical model is tested. Finally, conclusion and discussion about the results are offered pointing out potential contributions to the IS and strategic management literature.

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