Social Search in the context of Social Learning

(Written as an explanation of introNetworks' Smart Search for @marciamarcia)

Do we know what are people looking for?

Thinking of how someone would potentially search the enterprise network before the network is built is a critical piece of the puzzle for those contemplating putting in a social network (or more appropriately, a knowledge network).

This thinking comes in the form of a series of Users Stories that articulate how a variety of people will take advantage of the knowledge network in explicit detail. What types of problems will they expect to solve, what type of knowledge can they easily extract, how effectively can they sort through thousands of individual profiles to find a finite set of skills in seconds? Every organization is different and one size will not fit all situations, making these User Stories as targeted as possible.

Is there a better way to capture profile information?

Extracting information that will be the basis of the knowledge network and searchable as described in the User Stories becomes the next challenge for the network designer. It is important to be able to customize the user profiles so that experiences, skills, challenges, values, expertise, personal and professional interests are user-submitted in an environment that is trusted and doesn't leave users feeling vulnerable. In this type of environment they are open, honest and forthcoming. It is vital that the profile be rich in content and completed in the context as described by the various user stories that have been compiled. When users give weight to each attribute in their profile by attaching importance, the overall quality of the network is increased tremendously.

Searching smarter.

With thousands of these nearly encyclopedic profiles that have been designed to capture the essence of what’s important to the specific needs of the organization, the potential to drill down with finite search criteria becomes a matter of a few clicks of the mouse. Imagine being able to isolate the population of 12,000 employees down to the 145 people with expertise in task management, and further tighten the criteria to those that also have a background in the energy industry and have taken a course in Delegation – which nets a much smaller list of 12 people. This is a much more actionable list and also allows the searcher to learn even more about these 12 people before reaching out to them, as the profile contains much more information than was searched for – this allows the user to use reasoning and experience to find the one or two perfect people for a project, or to pose a question to, in minutes, not hours or days.

Planning for actionable business intelligence

We believe that thinking ahead, knowing what your users will be searching for, and how you will use that information to further the goals of the organization are critical to the success of the design, implementation and sustainability of an enterprise knowledge network.