How organisations leverage Big Data: a maturity model

Author:

Comuzzi Marco,Patel Anit

Abstract

Purpose While it is commonly recognised that Big Data have an immense potential to generate value for business organisations, appropriating value from Big Data and, in particular, Big Data-enabled analytics is still an open issue for many organisations. The purpose of this paper is to develop a maturity model to support organisations in the realisation of the value created by Big Data. Design/methodology/approach The maturity model is developed following a qualitative approach based on literature analysis and semi-structured interviews with domain experts. The completeness and usefulness of the model is evaluated qualitatively by practitioners, whereas the applicability of the model is evaluated by Big Data maturity assessments in three real-world organisations. Findings The proposed maturity model is considered exhaustive by domain experts and has helped the three assessed organisations to develop a more critical understanding of the next steps to take. Originality/value The maturity model integrates existing industry-developed maturity models into one single coherent Big Data maturity model. The proposed model answers the call for research on Big Data to abstract from technical issues to focus on the business implications of Big Data initiatives.

Publisher

Emerald

Subject

Industrial and Manufacturing Engineering,Strategy and Management,Computer Science Applications,Industrial relations,Management Information Systems

Reference44 articles.

1. Asay, M. (2014), “8 reasons why Big Data projects fail”, InformationWeek, available at: www.informationweek.com/big-data/big-data-analytics/8-reasons-big-data-projects-fail/a/d-id/1297842 (accessed 1 November 2015).

2. Developing maturity models for IT management;Business & Information Systems Engineering,2009

3. Betteridge, N. and Nott, C. (2014), “Big Data and analytics maturity model”, available at: www.ibmbigdatahub.com/blog/big-data-analytics-maturity-model (accessed 1 November 2015).

4. Digital business strategy: toward a next generation of insights;Mis Quarterly,2013

5. Big data;Business & Information Systems Engineering,2013

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