Integrating knowledge management and business interoperability: a scenario framework

In today's dynamic and competitive environment, businesses become increasingly complex and knowledgeintensive. Knowledge is believed to be a potential asset that could secure sustainable competitive advantage to an organization. While, to gain value from the knowledge, an organization should be able to manage it effectively. How organizations manage their knowledge is known as Knowledge Management (KM), which represents a combination of both technical and human aspects. KM authors claim that the major challenge of managing knowledge is less its creation and more its capture and integration. Managing knowledge in an organization expects the collaboration between a broad spectrum of contributors that ranges from people and processes to supportive technologies. Business Interoperability (BI) is defined as the organizational and operational ability of an enterprise to cooperate with its business partners and to efficiently set-up, conduct and develop digital business with the objective to create value. Knowledge Interoperability (KI), as part of BI, is the ability of two or more different entities to share their intellectual assets, gaining primary advantage of the mutual knowledge and use it, and to more significantly extend them through cooperation. Interoperability at knowledge level should be the compatibility of the skills, competencies and knowledge assets of an enterprise with those of another enterprise. KI concerns three distinct levels: organization level (organization roles, skills and competencies, knowledge assets, human resources management, laws and regulations, legal obligations and relationships with government institutions); technical level (knowledge data); and semantics (knowledge ontologies). This paper will focus narrowly on the organizational level. While most of the present research focuses on technical aspects of interoperability, a systematic analysis of strategic and organizational issues of interoperability lacks currently. This paper is conceptual in nature and aims to open a debate about the integration of KM into BI.