Understanding the Impact of Business Analytics on Innovation

Advances in Business Analytics in the era of Big Data have provided unprecedented opportunities for organizations to innovate. With insights gained from Business Analytics, companies are able to develop new or improved products/services. However, few studies have investigated the mechanism through which Business Analytics contributes to a firm's innovation success. This research aims to address this gap by theoretically and empirically investigating the relationship between Business Analytics and innovation. To achieve this aim, absorptive capacity theory is used as a theoretical lens to inform the development of a research model. Absorptive capacity theory refers to a firm's ability to recognize the value of new, external information, assimilate it and apply it to commercial ends. The research model covers the use of Business Analytics, environmental scanning, data-driven culture, innovation (new product newness and meaningfulness), and competitive advantage. The research model is tested through a questionnaire survey of 218 UK businesses. The results suggest that Business Analytics directly improves environmental scanning which in turn helps to enhance a company's innovation. Business Analytics also directly enhances data-driven culture that in turn impacts on environmental scanning. Data-driven culture plays another important role by moderating the effect of environmental scanning on new product meaningfulness. The findings demonstrate the positive impact of business analytics on innovation and the pivotal roles of environmental scanning and data-driven culture. Organizations wishing to realize the potential of Business Analytics thus need changes in both their external and internal focus.

[1]  R. Kelly Rainer,et al.  Environmental Scanning for Information Technology: An Empirical Investigation , 1997, J. Manag. Inf. Syst..

[2]  Joe B. Hurst,et al.  A Decision-Making Perspective on the Learning of History. , 1984 .

[3]  Robert G. Cooper,et al.  The Dimensions of Industrial New Product Success and Failure , 1979 .

[4]  D. Gann,et al.  How open is innovation , 2010 .

[5]  S. Zahra,et al.  Absorptive Capacity: A Review, Reconceptualization, and Extension , 2002 .

[6]  Clyde W. Holsapple,et al.  A unified foundation for business analytics , 2014, Decis. Support Syst..

[7]  J. Workman,et al.  Market Orientation, Creativity, and New Product Performance in High-Technology Firms , 2004 .

[8]  Berrin Erdogan,et al.  Justice and Leader-Member Exchange: The Moderating Role of Organizational Culture , 2006 .

[9]  Marko Sarstedt,et al.  Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research , 2014 .

[10]  J. Hair.  Multivariate data analysis , 1972 .

[11]  Robert G. Dyson,et al.  Supporting strategy : frameworks, methods and models , 2007 .

[12]  M. Porter,et al.  How Information Gives You Competitive Advantage , 1985 .

[13]  R. Stock,et al.  Two Sides of the Same Coin: How Do Different Dimensions of Product Program Innovativeness Affect Customer Loyalty? , 2013 .

[14]  Jon Denham,et al.  Culture Is King: How Culture Contributes to Innovation , 2012 .

[15]  David L. Olson,et al.  The impact of advanced analytics and data accuracy on operational performance: A contingent resource based theory (RBT) perspective , 2014, Decis. Support Syst..

[16]  J. Lemmink,et al.  High‐Technology Service Innovation Success: A Decision‐Making Perspective , 2004 .

[17]  Detmar W. Straub,et al.  Specifying Formative Constructs in Information Systems Research , 2007, MIS Q..

[18]  Veda C. Storey,et al.  Business Intelligence and Analytics: From Big Data to Big Impact , 2012, MIS Q..

[19]  P. Ritala,et al.  Incremental and Radical Innovation in Coopetition—The Role of Absorptive Capacity and Appropriability , 2013 .

[20]  P. H. Friesen,et al.  Innovation in Conservative and Entrepreneurial Firms: Two Models of Strategic Momentum , 1982 .

[21]  Rashi Glazer.  Marketing in an Information-Intensive Environment: Strategic Implications of Knowledge as an Asset , 1991 .

[22]  T. M. Amabile.  The social psychology of creativity: A componential conceptualization. , 1983 .

[23]  Bart Baesens,et al.  Profit optimizing customer churn prediction with Bayesian network classifiers , 2014, Intell. Data Anal..

[24]  C. Perrow.  A FRAMEWORK FOR THE COMPARATIVE ANALYSIS OF ORGANIZATIONS , 1967 .

[25]  Chung-Ming Lau,et al.  The HR system, organizational culture, and product innovation , 2004 .

[26]  Dominic Barton,et al.  Making advanced analytics work for you. , 2012, Harvard business review.

[27]  Brian Fitzgerald,et al.  A Longitudinal Study of Software Process Improvement , 1999, IEEE Softw..

[28]  Varun Grover,et al.  Exploring Mediation Between Environmental and Structural Attributes: The Penetration of Communication Technologies in Manufacturing Organizations , 1999, J. Manag. Inf. Syst..

[29]  Xiaojun Pan,et al.  Production , Manufacturing and Logistics Dynamic optimal control of process – product innovation with learning by doing , 2015 .

[30]  Breda Kenny,et al.  The Impact of Organisational Culture Factors on Innovation Levels in SMEs: An Empirical Investigation , 2006 .

[31]  Richard Vidgen,et al.  Management challenges in creating value from business analytics , 2017, Eur. J. Oper. Res..

[32]  R. Calantone,et al.  New Product Success: Is It Really Controllable by Managers in Highly Turbulent Environments? , 2008 .

[33]  D. Hambrick.  Environmental scanning and organizational strategy , 1982 .

[34]  V. A. Thompson.  Bureaucracy and innovation , 1969 .

[35]  Michael L. Tushman,et al.  Information Processing as an Integrating Concept in Organizational Design. , 1978 .

[36]  Ping-Chuan Chen,et al.  Collaborative green innovation in emerging countries: a social capital perspective , 2014 .

[37]  M. Wedel,et al.  Marketing Analytics for Data-Rich Environments , 2016 .

[38]  Straub,et al.  Editor's Comments: An Update and Extension to SEM Guidelines for Administrative and Social Science Research , 2011 .

[39]  J. Roldán,et al.  Absorptive capacity, innovation and cultural barriers: A conditional mediation model , 2014 .

[40]  Wes Nichols,et al.  Advertising Analytics 2.0. (cover story) , 2013 .

[41]  David C. Mohr,et al.  Employee turnover and operational performance: the moderating effect of group‐oriented organisational culture , 2012 .

[42]  Paulo B. Góes,et al.  Editor's comments: big data and IS research , 2014 .

[43]  Jay R. Galbraith.  Organization Design: An Information Processing View , 1974 .

[44]  Daniel A. Levinthal,et al.  ABSORPTIVE CAPACITY: A NEW PERSPECTIVE ON LEARNING AND INNOVATION , 1990 .

[45]  Asil Oztekin,et al.  A data analytic approach to forecasting daily stock returns in an emerging market , 2016, Eur. J. Oper. Res..

[46]  C. Rebolledo,et al.  The role of relative absorptive capacity in improving suppliers' operational performance , 2012 .

[47]  S. Zahra,et al.  Entrepreneurship and Dynamic Capabilities: A Review, Model and Research Agenda , 2006 .

[48]  David C. Wyld,et al.  Keys to Innovation: The Right Measures and the Right Culture? , 2009 .

[49]  Indranil Bose,et al.  Managing a Big Data project: The case of Ramco Cements Limited , 2015 .

[50]  Johan Frishammar,et al.  Managing External Information in Manufacturing Firms : The Impact on Innovation Performance , 2005 .

[51]  Rajiv Sabherwal,et al.  Strategic Alignment Between Business and Information Technology: A Knowledge-Based View of Behaviors, Outcome, and Consequences , 2006, J. Manag. Inf. Syst..

[52]  Joe Peppard,et al.  Why IT Fumbles Analytics , 2013 .

[53]  J. Barney,et al.  Organizational Culture: Can It Be a Source of Sustained Competitive Advantage? , 1986 .

[54]  C. McDermott,et al.  Service innovation and performance in SMEs , 2012 .

[55]  Michael J. Gallivan,et al.  A framework for ex ante project risk assessment based on absorptive capacity , 2006, Eur. J. Oper. Res..

[56]  Richard J. Ormerod,et al.  A new perspective on the dynamics of information technology‐enabled strategic change , 1998, Inf. Syst. J..

[57]  Kristopher J Preacher,et al.  Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models , 2008, Behavior research methods.

[58]  Rajesh Sethi,et al.  Can Quality‐Oriented Firms Develop Innovative New Products? , 2009 .

[59]  R. Little.  A Test of Missing Completely at Random for Multivariate Data with Missing Values , 1988 .

[60]  Joan C. Woodward.  Management and technology , 1958 .

[61]  S. Sambrook,et al.  Towards a multidisciplinary definition of innovation , 2009 .

[62]  Hossam Ismail,et al.  A study of contingency relationships between supplier involvement, absorptive capacity and agile product innovation , 2013 .

[63]  Tom Pape,et al.  Prioritising data items for business analytics: Framework and application to human resources , 2016, Eur. J. Oper. Res..

[64]  Geoff Royston,et al.  Operational Research for the Real World: big questions from a small island , 2013, J. Oper. Res. Soc..

[65]  M. Jelinek.  Technology, Organizations, and Contingency , 1977 .

[66]  Terry S. Overton,et al.  Estimating Nonresponse Bias in Mail Surveys , 1977 .

[67]  S. Slater,et al.  Impact of Knowledge Type and Strategic Orientation on New Product Creativity and Advantage in High-Technology Firms† , 2013 .

[68]  Scott B. MacKenzie,et al.  Working memory: theories, models, and controversies. , 2012, Annual review of psychology.

[69]  Prasanna Tambe.  Big Data Investment, Skills, and Firm Value , 2014, Manag. Sci..

[70]  L. Thayer,et al.  Communication and communication systems: In organization, management, and interpersonal relations , 1986 .

[71]  Sven-Volker Rehm,et al.  The emergence of boundary clusters in inter-organizational innovation , 2015, Inf. Organ..

[72]  A. Rangaswamy,et al.  Performance implications of deploying marketing analytics , 2013 .

[73]  Neil F. Doherty,et al.  Operational research from Taylorism to Terabytes: A research agenda for the analytics age , 2015, Eur. J. Oper. Res..

[74]  Filipe Coelho,et al.  Market orientation and new-to-the-world products: Exploring the moderating effects of innovativeness, competitive strength, and environmental forces , 2009 .

[75]  Roger J. Calantone,et al.  Decomposing Product Innovativeness and Its Effects on New Product Success , 2006 .

[76]  Shijin Yoo,et al.  Paths to Success: How Do Market Orientation and Entrepreneurship Orientation Produce New Product Success? , 2013 .

[77]  L. J. Bourgeois,et al.  Strategy and Environment: A Conceptual Integration , 1980 .

[78]  Hugh J. Watson,et al.  Tutorial: Big Data Analytics: Concepts, Technologies, and Applications , 2014, Commun. Assoc. Inf. Syst..

[79]  Toby E. Stuart.  Interorganizational alliances and the performance of firms: A study of growth and innovation rates i , 2000 .

[80]  T. Davenport,et al.  Data to Knowledge to Results: Building an Analytic Capability , 2001 .

[81]  Yu‐Shan Chen,et al.  The positive effects of relationship learning and absorptive capacity on innovation performance and competitive advantage in industrial markets , 2009 .

[82]  C. Bode,et al.  Fostering incremental and radical innovation through performance-based contracting in buyer-supplier relationships , 2016 .

[83]  Elliot Bendoly,et al.  The efficient use of enterprise information for strategic advantage: A data envelopment analysis , 2009 .

[84]  Wenhong Luo,et al.  The Analytics Movement: Implications for Operations Research , 2010, Interfaces.

[85]  V. Sambamurthy,et al.  Information Technology Assimilation in Firms: The Influence of Senior Leadership and IT Infrastructures , 1999, Inf. Syst. Res..

[86]  Shu Han,et al.  Changing the Competitive Landscape: Continuous Innovation Through IT-Enabled Knowledge Capabilities , 2010, Inf. Syst. Res..

[87]  Dursun Delen,et al.  Data, information and analytics as services , 2013, Decis. Support Syst..

[88]  Rajiv Sabherwal,et al.  Alignment Between Business and IS Strategies: A Study of Prospectors, Analyzers, and Defenders , 2001, Inf. Syst. Res..

[89]  Aino Kianto,et al.  The impact of intellectual capital management on company competitiveness and financial performance , 2013 .

[90]  Ephraim R. McLean,et al.  The DeLone and McLean Model of Information Systems Success: A Ten-Year Update , 2003, J. Manag. Inf. Syst..

[91]  I. Yeoman.  Competing on analytics: The new science of winning , 2009 .

[92]  Roger H. L. Chiang,et al.  Big Data Research in Information Systems: Toward an Inclusive Research Agenda , 2016, J. Assoc. Inf. Syst..

[93]  James M. Higgins,et al.  Want Innovation? Then Use Cultural Artifacts that Support It , 2002 .

[94]  Soo Wook Kim,et al.  Opening the technological innovation black box: The case of the electronics industry in Korea , 2016, Eur. J. Oper. Res..

[95]  K. Atuahene–Gima,et al.  Market Orientation and Innovation , 1996 .

[96]  W. Moore,et al.  The Role of Market Information in New Product Success/Failure , 1997 .

[97]  Richard P. Bagozzi,et al.  Assessing Construct Validity in Organizational Research , 1991 .

[98]  R. Kelly Rainer,et al.  The Impact of Information Technology Infrastructure Flexibility on Strategic Alignment and Application Implementations , 2003, Commun. Assoc. Inf. Syst..

[99]  Claudia van Oppen,et al.  USING PLS PATH MODELING FOR ASSESSING HIERARCHICAL CONSTRUCT MODELS : GUIDELINES AND EMPIRICAL , 2022 .

[100]  Luis G. Vargas,et al.  Predictive analytics model for healthcare planning and scheduling , 2016, Eur. J. Oper. Res..

[101]  Mohan Subramaniam,et al.  The Influence of Intellectual Capital on the Types of Innovative Capabilities , 2005 .

[102]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[103]  P. Shrout,et al.  Mediation in experimental and nonexperimental studies: new procedures and recommendations. , 2002, Psychological methods.

[104]  Min Zhang,et al.  Absorptive capacity and mass customization capability , 2015 .

[105]  David B. Balkin,et al.  Organizational Culture and Innovation: A Meta‐Analytic Review , 2013 .

[106]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[107]  Maria Elena Baltazar Herrera.  Creating competitive advantage by institutionalizing corporate social innovation , 2015 .

[108]  T. Davenport.  Competing on analytics. , 2006, Harvard business review.

[109]  M. Tushman.  Special Boundary Roles in the Innovation Process. , 1977 .

[110]  Jason Bennett Thatcher,et al.  Antecedents and outcomes of strategic IS alignment: an empirical investigation , 2006, IEEE Transactions on Engineering Management.

[111]  Chun Wei Choo.  The Art of Scanning the Environment , 2005 .

[112]  G. Hult,et al.  Innovation, Market Orientation, and Organizational Learning: An Integration and Empirical Examination , 1998 .

[113]  Kweku-Muata Osei-Bryson,et al.  A snail shell process model for knowledge discovery via data analytics , 2016, Decis. Support Syst..

[114]  G. Ahuja.  Collaboration Networks, Structural Holes, and Innovation: A Longitudinal Study , 1998 .

[115]  Andrew Schwarz,et al.  Examining the Impact of Multicollinearity in Discovering Higher-Order Factor Models , 2014, Commun. Assoc. Inf. Syst..

[116]  Sunil Mithas,et al.  Business Analytics: Radical Shift or Incremental Change? , 2012, Commun. Assoc. Inf. Syst..

[117]  Heiner Evanschitzky,et al.  Success Factors of Product Innovation: An Updated Meta‐Analysis , 2012 .

[118]  I. Nonaka,et al.  How Japanese Companies Create the Dynamics of Innovation , 1995 .

[119]  Kam-Fai Wong,et al.  Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions , 2012, MIS Q..

[120]  Evan Stubbs.  Big Data Big Innovation: Enabling Competitive Differentiation Through Business Analytics , 2014 .

[121]  Cynthia A. Lengnick-Hall,et al.  Innovation and Competitive Advantage: What We Know and What We Need to Learn , 1992 .

[122]  Scott B. MacKenzie,et al.  Construct Measurement and Validation Procedures in MIS and Behavioral Research: Integrating New and Existing Techniques , 2011, MIS Q..

[123]  Albert H. Rubenstein,et al.  The effects of perceived needs and means on the generation of ideas for industrial research and development projects , 1967 .

[124]  R. Cooper,et al.  What distinguishes the top performing new products in financial services , 1994 .

[125]  Marko Sarstedt,et al.  Editorial - Partial Least Squares Structural Equation Modeling: Rigorous Applications, Better Results and Higher Acceptance , 2013 .

[126]  W. E. Holland,et al.  Boundary-Spanning Roles in a Research and Development Organization: An Empirical Investigation , 1975 .

[127]  Robert Fildes,et al.  Reassessing the scope of OR practice: The Influences of Problem Structuring Methods and the Analytics Movement , 2015, Eur. J. Oper. Res..