概要

Collaboration and Expertise Networks (CEN)

Expertise is not easily identified and is even more difficult to manage on an ongoing basis, which leaves vast resources of tacit knowledge and experience untapped. There is growing recognition that access to these types of implicit information is critical to the efficient running of enterprise operations. For example, the employees of geographically dispersed organizations typically have difficulty in determining what others are doing and which resources can best address their problems. Failure to foster exchange within the knowledge community leads to duplication of effort and an overall reduction in productivity levels. Autonomy CEN builds communities of expertise to promote collaboration and fuel innovation. A key part of Web 2.0 technology, these social knowledge networks overcome situational myopia and bring experts together to establish congruent goals and increase productivity.

By forming a conceptual understanding of user interaction with information as it is consumed and created, Autonomy's technology identifies tacit knowledge automatically and in context. It builds a conceptual understanding of the relationships between experts and the content with which they interact, automatically clustering similar people and resources into related groups. Rapidly deployed, Autonomy CEN incorporates content from the array of existing collaboration tools inside the enterprise, from IM, wikis and workflow applications to team calendaring, each of which has its own incompatible proprietary expertise repository, non-uniform schema and distinctive interfaces. Whereas labor-intensive technologies and "point solutions" force the user to adapt to the technology by changing his or her behavior, Autonomy's implicit analysis ensures users remain on task with minimal cultural or behavioural change and virtually no training.

Expertise management is facilitated through:

Implicit Profiling: IDOL automatically recommends an expert based on a conceptual understanding of the content they consume and create across all data formats including email, IM, documents, online and even voice

Explicit Profiling: users have the ability to describe their own expertise using natural language free text as well as keywords. IDOL also leverages any metadata that has been assigned to experts either by themselves or by the administrator

Clustering: IDOL clusters disparate pieces of information automatically by concept, matching them to the conceptual profiles of experts in real-time in order to highlight crucial information and expertise resources

Alerting: staff can be alerted to new information and changing situations automatically, and be connected to a network of experts the instant new information arrives

Location-based Expertise Assignment: users can combine a conceptual search for experts with information such as geographic location, department and availability

Virtual Libraries: not all the data within the organization's information assets will play a significant role in key business decisions. IDOL leverages "collaborative feedback" to create libraries of the most useful information

Document Rating: users can rate content either positively or negatively, as well as add comments to content that exists within the organization, allowing the most widely used information to appear higher in the library rankings

Document Scaling: users can rate the usefulness of information with a sliding scale to influence IDOL's relevancy calculation

Visualization: Autonomy's spectrograph updates automatically and in real-time to reflect the changing relationships between experts and the available information assets over time, allowing management to plan and respond accordingly