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A Text Mining Approach for Extracting Lessons Learned from Project Documentation: An Illustrative Case Study

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  • Benjamin Matthies

    (South Westphalia University of Applied Sciences, Germany)

Abstract

Lessons learned are important building blocks for continuous learning in project-based organisations. Nonetheless, the practical reality is that lessons learned are often not consistently reused for organisational learning. Two problems are commonly described in this context: the information overload and the lack of procedures and methods for the assessment and implementation of lessons learned. This paper addresses these problems, and appropriate solutions are combined in a systematic lesson learned process. Latent Dirichlet Allocation is presented to solve the first problem. Regarding the second problem, established risk management methods are adapted. The entire lessons learned process will be demonstrated in a practical case study.

Suggested Citation

  • Benjamin Matthies, 2017. "A Text Mining Approach for Extracting Lessons Learned from Project Documentation: An Illustrative Case Study," International Journal of Management, Knowledge and Learning, International School for Social and Business Studies, Celje, Slovenia, vol. 6(2), pages 153-174.
    • Handle: RePEc:isv:jouijm:v:6:y:2017:i:2:p:153-174
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    References listed on IDEAS

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    1. Prencipe, Andrea & Tell, Fredrik, 2001. "Inter-project learning: processes and outcomes of knowledge codification in project-based firms," Research Policy, Elsevier, vol. 30(9), pages 1373-1394, December.
    2. Kam Jugdev, 2012. "Learning from Lessons Learned: Project Management Research Program," American Journal of Economics and Business Administration, Science Publications, vol. 4(1), pages 13-22, January.
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    Cited by:

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