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Article
Publication date: 1 June 2015

Nils O.E. Olsson and Heidi Bull-Berg

– The purpose of this paper is to investigate how Big Data can be used in project evaluations.

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Abstract

Purpose

The purpose of this paper is to investigate how Big Data can be used in project evaluations.

Design/methodology/approach

The study is based on literature research and interviews with 15 professionals in IT, project and asset management and government agencies. The authors discuss and illustrate what data that can be used for project evaluations and discuss potential obstacles.

Findings

New data is creating new opportunities to analyse a phenomenon based on different types of data. Interesting data categories include: internet traffic, movement-related data, physical environment data and data in organisational internal systems. The authors show how these data categories can be applied in project evaluations.

Research limitations/implications

Big Data gives an opportunity to add quantitative data in ex post evaluations. Use of Big Data can serve as a step towards a stronger technology focus in evaluations of projects.

Practical implications

There are major advantages in using Big Data, increasing the opportunities to find indicators that are relevant when a project is evaluated.

Social implications

Possible problematic issues related to use of Big Data that are addressed in the study include: availability, applicability, relevance, privacy policy, ownership, cost and competence. The study indicates that none of the challenges need to hinder use of Big Data when evaluating projects, provided that the issues are properly managed.

Originality/value

The study illustrates how Big Data can be applied in project management research.

Details

International Journal of Managing Projects in Business, vol. 8 no. 3
Type: Research Article
ISSN: 1753-8378

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Article
Publication date: 1 June 2015

Derek Walker

217

Abstract

Details

International Journal of Managing Projects in Business, vol. 8 no. 3
Type: Research Article
ISSN: 1753-8378

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