A Holistic View of Factors Impacting the Adoption of Lessons Learned Management Systems

The benefits of a lessons learned (LL) program are widely recognized. A lesson learned management system (LLMS) is the software designed to support the LL program and is essential to the program’s value delivery. The need for knowledge management (KM) in the energy sector appears to increase as energy companies focus on the energy transition while continuing digital transformation, performance improvement, and decarbonization of conventional energy production. Digital transformation has increased the accessibility to intelligent, well-designed lessons learned management systems (LLMS). However, there remain challenges to adoption. This study aims to explore factors impacting the adoption of LLMSs within the context of the upstream oil and gas sector. First, a comprehensive literature review is conducted to understand existing barriers and enablers. Semi-structured interviews are then conducted with employees from a large global oil and gas company to uncover existing barriers and factors leading to the adoption of an LLMS. The thematic analysis method was used to analyze the interview data, in which five themes are presented: understand existing barriers, incorporate enabling processes and governance, facilitate the people element supporting the LL programs, satisfy users with important LLMS characteristics, and improve the LL process with an LLMS. Finally, practical recommendations for organizations to increase the adoption of an LLMS are summarized.

Name thesis:degree_name

Master

Department dc:contributor.department

System Design and Management Program.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• Kittipeerapat, Thitisak

Advisor dc:contributor.advisor

• Rhodes, Donna H.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/147404

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/147404