Managing complex engineering projects: What can we learn from the evolving digital footprint?

Ben Hicks, Stephen Culley, James Gopsill, Christopher Snider

Research output: Contribution to journalReview articlepeer-review

9 Citations (SciVal)
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The challenges of managing large complex engineering projects, such as those involving the design of infrastructure, aerospace and industrial systems; are widely acknowledged. While there exists a mature set of project management tools and methods, many of today's projects overrun in terms of both time and cost. Existing literature attributes these overruns to factors such as: unforeseen dependencies, a lack of understanding, late changes, poor communication, limited resource availability (inc. personnel), incomplete data and aspects of culture and planning. Fundamental to overcoming these factors belies the challenge of how management information relating to them can be provided, and done so in a cost eff; ective manner. Motivated by this challenge, recent research has demonstrated how management information can be automatically generated from the evolving digital footprint of an engineering project, which encompasses a broad range of data types and sources. In contrast to existing work that reports the generation, verification and application of methods for generating management information, this paper reviews all the reported methods to appraise the scope of management information that can be automatically generated from the digital footprint. In so doing, the paper presents a reference model for the generation of managerial information from the digital footprint, an appraisal of 27 methods, and a critical reflection of the scope and generalisability of data-driven project management methods. Key findings from the appraisal include the role of email in providing insights into potential issues, the role of computer models in automatically eliciting process and product dependencies, and the role of project documentation in assessing project norms. The critical reflection also raises issues such as privacy, highlights the enabling technologies, and presents opportunities for new Business Intelligence tools that are based on real-time monitoring and analysis of digital footprints.

Original languageEnglish
Article number102016
JournalInternational Journal of Information Management
Early online date26 Dec 2019
Publication statusPublished - 30 Apr 2020


  • Big Data
  • Business Intelligence
  • Knowledge Workers
  • Project Management

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Library and Information Sciences


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