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Use of big data in project evaluations

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.

Category

Academic article

Language

English

Author(s)

  • Nils Olsson
  • Heidi Bull-Berg

Affiliation

  • Norwegian University of Science and Technology
  • SINTEF Community / Mobility and Economics

Year

2015

Published in

International Journal of Managing Projects in Business

ISSN

1753-8378

Publisher

Emerald Group Publishing Limited

Volume

8

Issue

3

Page(s)

491 - 512

View this publication at Cristin