The characterisation of engineering activity through email communication and content dynamics, for support of engineering project management

Chris Snider, Stanko Skec, James Gopsill, Ben Hicks

Research output: Contribution to journalArticle (Academic Journal)

11 Citations (Scopus)
212 Downloads (Pure)


Significant challenge exists in the effective monitoring and management of engineering design and development projects. Due to traits such as contextual variation and scale, detailed understanding of engineering projects and activity are difficult to form, with monitoring hence reliant on interpretation of managerial personnel and adherence to defined performance indicators.
This paper presents a novel approach to the quantitative monitoring and analysis of engineering activity through computational topic identification and analysis of low-level communication data. Through three metrics of communication activity, this approach enables detailed detection and tracking of activity associated with specific project work areas. By application to 11,832 emails within two industry email corpora, this work identifies four distinct patterns in activity, and derives seven characteristics of communication activity within engineering design and development. Patterns identified are associated with background discussion, focussed working, and the appearance of issues, supporting detailed managerial understanding. Characteristics identified relate to through-process norms against which a manager may compare and assess.
Such project-specific information extends the ability of managers to understand the activity within their specific project scenario. Through detailed description of activity and its characteristics, in tandem with existing toolsets, a manager may be supported in their interpretation and decision-making processes.
Original languageEnglish
Number of pages31
JournalDesign Science
Issue numbere22
Publication statusPublished - 9 Nov 2017

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  • Projects

    LOCM: The Language of Collaborative Manufacturing

    Gopsill, J. A., Mcalpine, H. C., Mcmahon, C. A., Snider, C. M., Shi, L., Watts, L., Jones, S., Johnson, P., Newnes, L., Payne, S., Culley, S. & Hicks, B. J.


    Project: Research

  • Datasets

    DS - Topic Persistence

    Skec, S. (Creator), Gopsill, J. A. (Creator), Snider, C. M. (Creator) & Hicks, B. J. (Data Manager), University of Bristol, 26 Jul 2017



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