Driving Tech Enhancement Through Capability Dialogue
Abstract The energy sector is a dynamic landscape in which organizations are committed to driving technological enhancement by means of a strong framework of capability dialogue. This paper discusses how knowledge sharing tools can be strategically leveraged to foster an open, supportive communication environment that supports a culture of continuous improvement and enhances employee's engagement levels. The article also outlines how this facilitates the development of a collaborative learning ecosystem through which employees in different areas of the organization can learn from one another. By ensuring more meaningful and effective learning and development programs, emphasis on capability dialogue guarantees that subject matter experts (SMEs) get involved in these programs leading to seamless transfer of expertise as well as best practices. Such involvement aids individual growth and improves collective organizational capabilities. Our aim is to bridge skill gaps and raise technical proficiency across the entire workforce through structured learning interventions, focused training programmes, and mentoring initiatives. The importance of integrating with state-of-the-art learning methodologies for sustainability is underscored by this research. It focuses on the role played continuous professional development (CPD) as well as personalized learning paths have within an organization towards nurturing a highly skilled and adaptable workforce. Commitment to fostering a culture centred on learning drives operational excellence and innovation so that organizations remain on top in their respective industries. Further, the paper discusses digital transformation's influence on learning experiences as well as the need for adaptive educational technology capable of keeping up with industry changes.
Authors
- F. O. Al Mehairbi
Institutions
- Abu Dhabi National Oil (United Arab Emirates) (AE)
Publication Details
- Published
- 2024-11-04
- DOI
- https://doi.org/10.2118/222385-ms
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00