IBM’s SmallBlue

Network visualization for expertise sharing

The Problem

The Solution

Organizational Network Analysis Tools - Why?

Need for new knowledge‐sharing model because:

• Amount of content created and consumed increasing exponentially, thus rendering formal codification of all knowledge impossible.
• Hard to identify a set group of subject matter experts because the definition of “expert” is contextual.
• The most valuable intellectual capital is often tacit.
• The global nature of business makes it difficult to cultivate personal networks.

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Instead of treating knowledge as a static, capturable resource, embrace its contextual nature and preserve that context - instead of extracting the knowledge from its owner, put people in touch with the expert.

The SmallBlue suite helps users manage their personal networks, and reach out to their extended network (the friends of their friends) to find and access expertise and information.

History

• Concept of “knowledge networks” and increasing recognition of importance of informal relationships in knowledge transfer
• 2006 - SmallBlue is developed as an internal tool for expertise search
• Becomes the commercial product IBM Atlas, which is later integrated into the collaboration software suite Lotus Connections

Suite Components

• SmallBlue Client: Information capture and upload that drives the rest of the platform.
• SmallBlue Ego: egocentric social network visualizations for evaluation of social capital.
• SmallBlue Find: search engine that ranks people according to desired knowledge or skills.
• SmallBlue Reach: network-analysis engine that shows user profiles and the shortest social networking path through which to contact a person.
• SmallBlue Net: large-scale social network visualization and analysis tool.

SmallBlue Client

System for information capture. Automatically generates a person’s profile and social network from the info gathered.

“Data were only collected from people who had opted into SmallBlue after reading our privacy policies. There was no requirement or coercion to join; users could opt out at any time and have all their data removed. New users could try SmallBlue at any time before opting in. When a user opted in, they only had to specify the location of their email archives and chat history – users could include one or the other or both -- and our tool would extract and index the data. The real email or chat data never left the users’ machine.”

SmallBlue Client’s Information Capture Model

People

Network

SmallBlue Ego

Circular spider view shows the inferred personal social network of Ching-Yung Lin in August 2007. Different colors = different corporate business divisions. List next to the spider list shows the social capital of Xu from Lin's viewpoint. The locations of people in Lin's ego network are shown on the map.

SmallBlue Find

Search engine which returns a relevance-ranked list of people. Interprets a search string, maps it onto related keywords. Search engine aggregates results for all keywords and ranks them according to relevance weighting and aggregated social-network structure. SmallBlue then generates a list of the top 1,000 people who best match the search terms.

List is displayed with each person’s picture, job title, role, and online status. By default, SmallBlue shows top matched experts in the entire company. Users can search experts within a business division, country, community, group, or specific social distance. There is also an interface that lets users set several predefined ranges in tabbed pages that facilitate seeing top experts among various search ranges through only one search submission

SmallBlue Reach

Clicking on a search result from SmallBlue Find brings up the associated user profile in SmallBlue Reach.

Reach is a network-analysis engine that shows users their shortest social paths to reach a person. It also shows the formal organization groups and informal groups to which a person belongs as well as a person’s public activities in blogs, forums, social bookmarks, profiles, and so on.

SmallBlue Net

SNA in two views: according to topic, or according to people in a community/group.

“Although we conventionally think of an expert as someone who has the most knowledge of a particular topic, sometimes we want to find the person who knows the expert rather than the expert themselves or we want to find the person who others think is the expert which is associated with the person at the center of the social network for a topic. For these reasons, it is sometimes useful to see the whole social network.”

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Network Visualization

Map View

Visualized social network in response to search term “healthcare”. Mousing over a thumbnail pictures brings up the same information about role and business unit as displayed in SmallBlue Find.

“In addition to the traditional network clustering view, the interface provides a map view which displays the geographic location of all the people in the network.”

SmallBlue Net - Color-coding, Bridges, Hubs

“There are several ways of viewing the data. For instance, instead of seeing the nodes displayed as pictures, users can see the nodes color coded by business unit. This is an especially useful way to see how information is getting shared and propagated in the organization and provides insight into the structure and cohesiveness of emergent communities. Users also have the option of seeing who is the hub of the network and who is providing a bridge between separate clusters.”

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