Enterprise knowledge

In this section, we will discuss knowledge, its definition and types in a generic context, as well as in a collaboration context. Before going into detail, we have to clarify the difference between data, information, and knowledge due to the confusion of these three related terms.

[Kabilan, 2007] described the differences between data, information, and knowledge. Data is raw. It exists and has no significance beyond its existence (in and of itself). It can exist in any form, usable or not. Information is data that has been given meaning by way of a relational connection. It exists when the relationships between data are recognized within a specific context. It can be useful, but is not necessarily so. Knowledge is the appropriate collection of information. It describes what actions to take when certain information exists. It has to be useful.

It follows that knowledge is the most valuable asset of any enterprise. It is a very important resource for learning new things, solving problems, creating core competencies, and initiating new situations for both individuals and enterprises now and in the future [Liao, 2003].

Knowledge describes how and why things are done within an enterprise. It also concerns the production of new facts or new knowledge.

Coming back to the relation between data, information, and knowledge, according to [Aamodt et al., 1995], we can summarize that the role of knowledge is to play the active part in the process of:

transforming data into information (data interpretation)

deriving new information from an existing one (elaboration)

acquiring new knowledge (learning)

Knowledge technologies, according to [Milton, 2008], have emerged during the last two decades in order to deal with knowledge in an enterprise. They are computer-based techniques and tools that provide a richer and more intelligent use of information technology. They are associated with a number of subject areas:

Knowledge Engineering: emerged from the work in Artificial Intelligence. It concerns the building of computer systems that solve problems in the way humans do.

Knowledge Based Engineering: emerged from the world of Computer Aided Design (CAD). It concerns the building of computer systems that help engineers to work more efficiently.

Knowledge Management: emerged from a number of business initiatives. It concerns the use of techniques and tools to make better use of assets in an enterprise. This subject area involves the identification and analysis of required knowledge assets and knowledge asset-related processes, subsequent planning, etc. [D1.1 Synergy, 2008].

1.3.1. Types of enterprise knowledge

Enterprise knowledge can be classified as follows [Spender 1993] [Nonaka & Takeuchi, 1995] [D1.1 Synergy, 2008]:

Explicit knowledge is both formalized and abstract. It is easily expressed, transferred, and shared in the form of data, facts, figures, rules, or formulas. This kind of knowledge can be transmitted between individuals in formal and systematic ways. The more explicit the knowledge is, the more stable it is. For example, textbooks, software code, etc. Generally explicit knowledge is associated with data through business processes. It can be implemented in an enterprise through creating, reading, updating, and deleting operations.

Tacit knowledge is often referred to as knowledge-in-practice. It is highly personal knowledge developed from direct experience. It is subjective, and not easily expressible. It can be shared through interactive conversation. Examples of this kind of knowledge are experience, idea, emotions, intuitions, and insights; which are the foundation of innovation and creativity. Tacit knowledge has two dimensions:

technical and cognitive. The technical dimension is described as know-how which is dependent on experience. The cognitive dimension is composed of schema, values, and beliefs.

Social knowledge is shared and may be either explicit or tacit. For example, scientific knowledge which is shared and explicit, communal knowledge which is shared and tacit, etc. Individual knowledge is always tacit.

1.3.2. Knowledge for collaboration

This section focuses on knowledge that can drive and support collaboration. This knowledge encompasses:

Enterprise information

Shared and public information of the enterprise network

Information about how to find, access, and retrieve the above information

Expertise and procedures to effectively apply the above.

The above knowledge is available within enterprises, as well as in networks to enhance and promote productivity in collaboration. Knowledge users are potentially contributing to the content of knowledge on collaboration. Some knowledge may be freely shared within enterprises or some networks. Some may be commercially valuable knowledge like product information.

[Li et al., 2006] classified enterprise knowledge relevant to the formation and operation of collaborative ventures into four categories: enterprise core competence, VO³ (Virtual Organization) formation knowledge, partner selection knowledge, and VO operations management knowledge. Fig.II.4 summarizes the different categories of knowledge for collaboration together with their possible sources:

Fig.II. 4 Enterprise benefits of knowledge oriented collaboration [InterOP Roadmap, 2006]

Enterprise core competence: this is knowledge of the enterprise’s own capabilities and capacities, strengths and weaknesses, and technical IPR. This kind of knowledge

3 A VO is a short-term association with a specific goal of being active in fulfilling a Business Opportunity (BO).

VO is similar to virtual enterprise (VE) and is a special type of collaborative network. [Camarinha-Matos et al., 2005]

concerns the enterprise’s internal experience which can come from formal and informal sources. We might see a fractal view of the enterprise as a collaboration of its internal functions.

Process knowledge for VO formation: this is knowledge of best practice in formation of a VO, critical factors in VO development, legal issues, risk analysis, and application of tools such as maturity gate planning. It also includes moderation knowledge about collaboration and interoperability issues likely to be critical to partners. The sources of this kind of knowledge are enterprise experience of current and previous collaboration, as well as knowledge of collaboration practices in the industrial sector from previous collaborations and from ISUs⁴ (Interoperable Service Utility).

Process knowledge for partner selection: this is knowledge of potential partners’ core competencies, collaboration and interoperability capability, and reliability in collaboration. The knowledge in this category can be retrieved from knowledge of potential and actual partners from previous collaborations and from ISUs, as well as from the current and previous enterprise experience.

VO operations management knowledge: this includes the VO enterprise model to support decision making, knowledge of interoperability issues within the VO applied to ensure communication, and moderation knowledge about operational factors likely to be critical to partners. This kind of knowledge can be retrieved from various sources for example, enterprise experience, and best practices from ISUs.

1.4. Conclusion

The aim of Section 1 is to discuss inter-enterprise collaboration and enterprise knowledge in both the generic and the collaboration context.

A number of definitions concerning collaboration have been highlighted which allow us to summarize that collaboration has both human and organizational aspects. The human aspect concerns the actors who accomplish the collaboration tasks. The organizational aspect concerns the strategies, goals and relationships as well as the processes. Collaboration has four levels: communication for exchanging data, coordination for sharing and synchronization of tasks, cooperation if a common goal and process have been established, and integration if the enterprises have become a single entity.

Collaboration leads to setting up a collaborative network which can be configured by several elements (partners, common goals, relationships, and topology including duration and decision-making power). These elements are related to the definition of collaboration. They are the main criteria for characterising collaborations.

Enterprise knowledge can be acquired from experience, practice, conversation, innovation, document, software code, etc. The knowledge that drives and supports collaboration is for

4 The ISU provides interoperability as a technical, commoditized functionality, delivered as services. The ISU is a basic infrastructure that supports information exchange between diverse knowledge sources, software applications, and Web Services [Li et al., 2006].

example, core competences of the enterprise, experiences from previous collaborations, knowledge of interoperability issues, decision-making support, etc. Normally, the knowledge required for collaboration is retrieved from experiences, and best practices.

The precision of collaboration characterization depends on the knowledge we can retrieve from partners. The capture of more knowledge and better quality knowledge leads to a more accurate characterization of the collaboration and the result will be closer to reality.