Organizing Around Big Data: Organizational Analytic Capabilities for Improved Performance

Dijo T. Alexander, Case Western Reserve University
Kalle Lyytinen, Case Western Reserve University

Description

In the digital age of accelerating applications founded on big data and analytics, organizations need to utilize knowledge as a key asset. In the absence of established guidelines, organizations currently overplay the power of data and software tools to produce magical insights, largely ignoring organizational competencies to marry big data ‘evidence’ with business decision-making to generate impactful managerial action. Our goal is to address this gap. Using the dynamic capability lens, this study examines how organizations can address this challenge and transform their organizations by building competencies which enable success with big data. We conducted a survey of 224 big data analytics practitioners, from both business and technology, to estimate the impact of critical organizational factors on the success of big data initiatives. Our results suggest broad support for the positive effect of firm level organizational capabilities such as mobilization of analytic competencies, continuous learning and experimentation on successful analytics outcomes. Surprisingly, collaboration and market orientation are not found to have a significant effect. The results illuminates the emphasis firms should place on developing the analytic skills to design and conduct experiments rooted on contextual data to extract business insights that may lead to business process and product innovations. The study underscores the need to bridge data science and decision science to experiment with data towards improved business decisions.

 

Organizing Around Big Data: Organizational Analytic Capabilities for Improved Performance

In the digital age of accelerating applications founded on big data and analytics, organizations need to utilize knowledge as a key asset. In the absence of established guidelines, organizations currently overplay the power of data and software tools to produce magical insights, largely ignoring organizational competencies to marry big data ‘evidence’ with business decision-making to generate impactful managerial action. Our goal is to address this gap. Using the dynamic capability lens, this study examines how organizations can address this challenge and transform their organizations by building competencies which enable success with big data. We conducted a survey of 224 big data analytics practitioners, from both business and technology, to estimate the impact of critical organizational factors on the success of big data initiatives. Our results suggest broad support for the positive effect of firm level organizational capabilities such as mobilization of analytic competencies, continuous learning and experimentation on successful analytics outcomes. Surprisingly, collaboration and market orientation are not found to have a significant effect. The results illuminates the emphasis firms should place on developing the analytic skills to design and conduct experiments rooted on contextual data to extract business insights that may lead to business process and product innovations. The study underscores the need to bridge data science and decision science to experiment with data towards improved business decisions.