Abstract

This paper aims to benchmark the Lessons Learned (LL) and Knowledge Management (KM) systems at X Oil Company. In order to do so, interviews were conducted with project managers from the company in order to assess their understanding of LL and KM use and applications and their current existing system. This information served as the input and guidance for the required research to be done. The paper covers a comprehensive literature review which discusses in detail the steps to be taken, the requirements, key success factors and arising challenges for successful implementation of the LL system. Finally, the paper provides suggestions and recommendations such as application of web 2.0 technologies and methods for improvement and maintenance of high-quality lessons learned in addition to ease of retrieval. Following the steps and recommendations would help X Oil Company and other organizations achieve KM excellence.

Highlights

  • Most project managers know the consequence and the importance of capturing lessons learned; it is good for the team, organization and existing and future projects

  • X Oil Company project managers had been interviewed in order to collect the research data

  • It has been observed that X Oil Company Project Managers have a high level of understanding the importance of project’s lessons learned

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Summary

Introduction

Most project managers know the consequence and the importance of capturing lessons learned; it is good for the team, organization and existing and future projects. Lessons learned are the documented information that illustrates both the negative and positive experience of a project and discovers both strengths and weaknesses. They demonstrate the organization’s commitment to project management excellence and the project managers’ opportunity to learn from. Capturing lessons learned should be an ongoing process throughout the life of the project and not by learning from previous projects we are doomed to repeat similar failure situations. Essential reasons for repeating mistakes are difficulty in retrieving data as well as not appreciating lessons learned practices (Dolfing, 2019)

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