Big Data Evaluation Scorecard

This study seeks to examine the evolution of issues that have been espoused by both junior and senior scholars to aggregate out of literature, a criterion that can guide firms in evaluating their Big data analytic (BDA) projects. The systematic review approach took stock of varied socio-technical understanding, requirements, and capabilities used in addressing Big data issues and synthesized these issues for value accruals. The study strongly argues that Big data benefits accrue to firms whose economic activities require distributed collaborative effort, operational visibilities, cost, and time-sensitive decisions who adopt and implement the concept in their strategic, tactical, and operational levels. Though the trend shows steady growth in scholars’ interests and expectations in BDA, a significant percentage of the reviewed studies were not informed by any theory. The study contributes to BDA literature by affording scholars issue gaps and for practitioners, an analytical competency and evaluation scorecard that links strategic business goals to operational outcomes

A Typology of Big Data Capabilities from Resources to Dynamic Capabilities. Evidence from a Ghanaian Health Insurance Firm.

Big data is generating a lot of interest across different industries, with firms seeking to leverage big data to obtain enormous benefits. In the health insurance industry, especially in developing countries, there are efforts to use big data to increase healthcare access and at the same time reduce cost. Despite these efforts, there is a lack of literature on how to develop big data capabilities. Conceptually, the typology of capabilities has been suggested to follow a hierarchical order from resources and finally lead to dynamic capabilities in firms. This research examines the typology of big data capabilities in a health insurance developing country firm, to achieve dynamic capabilities from resources