Revolutionize Your Approach to Knowledge Management
There is currently a movement underway in the search community to deliver more personalized, intent-based search. But what about going one step beyond and anticipating people's needs? Here is an example: You arrive in the morning to find an email from your manager asking for a presentation about a corporate alliance formed before you joined the company. You see that your search engine has already begun working by locating and presenting conceptually relevant pieces of information on your desktop. The first piece is a video file. When you click to view the video, you are taken to the exact point in the video that discusses the alliance; there's no sifting or time-wasting through irrelevant frames. You are also presented with pertinent press releases, a PowerPoint covering key points, and the partnership contract. At your fingertips is information you had no idea existed, which may not have included the exact metadata to produce the same result using a keyword search. Without an intelligent search technology, you may have asked colleagues, searched for files, and then viewed the entire video to get the kernel of information you needed.
Own Your Social Network and Build your Knowledge Graph
Knowledge is not counted by what is produced, but what is shared. Content represents only a subset of that knowledge. To truly maximize an organization's intellectual assets, you must build a knowledge graph by identifying and continually updating people's respective skills and social networks. When this happens, people can quickly leverage and share expertise, and connect and collaborate on similar projects. They can leverage existing work that might not live in an enterprise system, but perhaps in the expert's personal storage. This type of socializing and accessibility encourages mentorship and leverages knowledge across the organization.
A knowledge graph is not something that a single content management system can own. People interact across different systems, and relationships are constantly evolving. But it is something that an intelligent search technology can infer. In the era of big data, we have abundant information regarding people's content browsing, consumption and contribution habits. We know who emails with which group and which individuals. We know who is working cross-functionally on a certain project. We know who works on the same account team. Using this type of contextual data to deliver precise search results can change the course of business—if it can be understood quickly enough to make a difference.
People often exaggerate or misrepresent their level of expertise, or they just fail to keep their profile updated. But sophisticated technology can properly combine the self-professed profile with an automated analysis of content. Data will tell you not what someone says they know, but what they actually know; not who they claim to know, but who they actually know well. These types of connections can be used to add another layer of context to provide a better, more personalized search experience.
But understanding a knowledge network requires the ability to interact with influencers—those individuals who shape opinion within communities—the people you can turn to for support and insight. While this may sound simple, the challenge lies in analyzing significant volumes of data in near-real time to determine these relationships and influences in a manner that optimizes an employee's search experience.
Search Should be Data-Driven
Data-driven predictions and decisions are gaining a lot of momentum and visibility. From Nate Silver's accurate prediction of all 50 states' results in the last presidential race, to the increasing use of statistics by law enforcement to combat crime, people are finding new ways to apply a data-focused methodology to conventional thinking. This same data-driven rigor should be applied to search. Search should not be a static experience, but constantly deliver customized conversations based on the data related to the user, the environment and the context.
When organizations choose search technology that understands the concepts and context of all information—regardless of where it resides, how it is accessed, or its format—it is possible to remove the irrelevant noise contained in much of big data. Employees that are able to leverage the wide array of information that exists inside and outside their enterprise can gain an immediate competitive advantage that you can only get from one source—your information, in all its forms.