Introduction
Knowledge sharing is critical to knowledge management (KM), especially in organizations prioritizing technical knowledge and expertise (Ahmad & Karim, 2019). This process enables skilled employees to share their expertise for improved organizational performance. Exchanging information across the workforce supports innovation and growth across organizational teams, increases efficiency and reduces costs, enhances customer focus and increases team collaboration for better customer services (Akram et al., 2020).
Article summary
The article analyzes Conoco Philips’ knowledge-sharing processes and the entity’s challenges in this process (Evans & Lindsay, 2013). The organization introduced the concept of knowledge sharing in early 2004, aiming to promote functional excellence, leverage knowledge better and ensure continuity of knowledge sharing among technicians and engineers. Also, the organization aimed to derive skills and knowledge from its retiring workforce and pass on this knowledge to the younger generation of technicians. The organization adopted the Fast model (Find, Ask, Share, Trust) to achieve this goal. This model is anchored on broader knowledge-sharing protocols of virtual communities in line with their business functions.
Conoco Philips supports its knowledge sharing by adopting a three-tier support model of a knowledge team, IT partners and external consultants. The knowledge-sharing team oversees the organization’s knowledge management process, tools, and templates (Evans & Lindsay, 2013). The IT partners offer infrastructure support and engage in site maintenance, while the external consultants maintain share point sites and offer customization and knowledge management (KM) expertise. The organization funds the KM through business streams. Some networks are given seed money by the organization to start. However, funding is uniformly distributed across the business units. Knowledge sharing team is allocated a budget for technology platforms. However, the network staffing costs are allocated to the business units. The senior executives support KM initiatives by participating in team meetings, knowledge-sharing leadership and communicating with relevant personnel (Evans & Lindsay, 2013).
The knowledge-sharing approach shown in Figure 12.13 below aligns with Conoco Philips’s strategic motivation for knowledge management.
Source: (Evans & Lindsay, 2013)
The fundamental objectives of introducing knowledge sharing in the organization were to enhance functional excellence, leverage interdepartmental knowledge sharing and transfer critical skills to the younger generation of engineers and technicians. The knowledge architecture allows for collaborative engagement among the staff, which is crucial in knowledge sharing (Denaux et al., 2017). The ability to give and receive feedback is also a critical component of knowledge sharing (Singh et al., 2021). Thus, the adopted model is essential for the organization to obtain maximum feedback through asking and discussing to improve the KM process. The benefits of knowledge sharing are also anchored on its reusability and future referencing (Abbasi et al., 2021). The knowledge architecture model facilitates an enhanced knowledge library, which facilitates reusability and future referencing for improved performance. Lastly, the knowledge architectural model aligns with the organization’s KM approaches. For instance, adopting the OneWiki learning platform ensures collective knowledge and global learning among the staff, consequently leading to enhanced knowledge sharing.
Measuring the success of KM initiatives is essential to determine its return on investment (ROI) to an organization (Goonesekera, 2023). Conoco Phillips adopted a unique approach to the financial impact of KM. For instance, the entity encourages employees to give success stories that show measurable gains emanating from the process (Payal et al., 2019). For instance, the employees highlight cost savings, environmental and safety and reduced turnaround times. Lee et al. (2020) note that having quantifiable metrics in KM is critical to track the efficiency of the process and inform the need for adjustments or revisions. Every success story includes a benefits summary that must be certified by leadership as accurate before being published.
Conclusion
Knowledge sharing enhanced inter-professional learning and improves employees’ skills and competence in speciality areas. By adopting a knowledge-sharing approach in Conoco Philips, the organization increases efficacy, reduces costs and improves environmental impacts, among other benefits. Adopting the FAST model and 140 networks of excellence facilitates efficiency in knowledge sharing. Besides, the entity’s unique approach to assessing the financial impact of KM through obtaining success stories from employees offers insight into the efficiency and effectiveness of the initiative. By adopting the KM initiative, Conoco Philips can obtain improved organizational performance and foster a culture of knowledge sharing, which is critical for its sustainability.
References
- Abbasi, S. G., Shabbir, M. S., Abbas, M., & Tahir, M. S. (2021). HPWS and knowledge sharing behavior: The role of psychological empowerment and organizational identification in public sector banks. Journal of Public Affairs, 21(3), e2512.
- Ahmad, F., & Karim, M. (2019). Impacts of knowledge sharing: a review and directions for future research. Journal of workplace learning, 31(3), 207-230.
- Akram, T., Lei, S., Haider, M. J., & Hussain, S. T. (2020). The impact of organizational justice on employee innovative work behavior: Mediating role of knowledge sharing. Journal of Innovation & Knowledge, 5(2), 117-129.
- Denaux, R., Ren, Y., Villazon-Terrazas, B., Alexopoulos, P., Faraotti, A., & Wu, H. (2017). Knowledge architecture for organisations. In Exploiting Linked Data and Knowledge Graphs in Large Organisations (pp. 57-84). Cham: Springer International Publishing.
- Evans, J. R., & Lindsay, W. M. (2013). Managing for quality and performance excellence. Cengage Learning.
- Goonesekera, T. (2023). Measuring knowledge management maturity levels in the manufacturing sector using fuzzy logic theory (Doctoral dissertation, La Trobe).
- Lee, O. K. D., Choi, B., & Lee, H. (2020). How do knowledge management resources and capabilities pay off in short term and long term?. Information & Management, 57(2), 103166.
- Payal, R., Ahmed, S., & Debnath, R. M. (2019). Impact of knowledge management on organizational performance: An application of structural equation modeling. VINE Journal of Information and Knowledge Management Systems, 49(4), 510-530.
- Singh, S. K., Gupta, S., Busso, D., & Kamboj, S. (2021). Top management knowledge value, knowledge sharing practices, open innovation and organizational performance. Journal of Business Research, 128, 788-798.