This begins the third series on knowledge management in special libraries and information centers, structured around Five Cs: Capture, Curate, Connect, Collaborate, and Create. This four-part series is about the third C: Connect.
According to Tom Stewart, “Connection is the essence of knowledge management.” Connection supports the demand side of knowledge. It enables demand-driven or just-in-time knowledge management. It is a necessary complement to capture, which provides the supply side of knowledge.
There are three types of connection that are important for knowledge management: people to people, people to content, and content to content. In this first of a four-part series, I discuss connecting people to people. People can connect to people through communities, Enterprise Social Networks (ESNs), and expertise locators.
People connect to other people for sharing their tacit knowledge. Tacit knowledge is personal knowledge that resides in an individual. It is content that has not been recorded or exchanged. It relies on experiences, ideas, insights, values, and judgments and usually requires joint, shared activities in order to transmit it. Individuals possess tacit knowledge and must learn to verbalize that knowledge. The art of talking about a problem or opportunity causes it to take shape and to be defined. Once defined, it can be solved or developed.
Dave Snowden wrote: “We will always tell more than we can write down” and “If you ask someone, or a body, for specific knowledge in the context of a real need it will never be refused.” And Tom Stewart wrote: “80 percent of (community) traffic starts with questions: Does anybody know? Does anybody have? Has anybody ever done something like?”
This argues for offering communities and ESNs as part of any knowledge management program. Communities are the people who connect, and threaded discussions or ESNs are the mechanism for the connection.
One very important kind of connection is boundary spanning. Bridging across organizational boundaries enables knowledge to flow between previously isolated groups.
Valdis Krebs and June Holley defined boundary spanners as “nodes that connect two or more clusters – they act as bridges between groups.” They wrote:
“When left unmanaged, networks follow two simple, yet powerful driving forces:
- Birds of a feather flock together.
- Those close by, form a tie.
This results in many small and dense clusters with little or no diversity. Everyone in the cluster knows what everyone else knows and no one knows what is going on in other clusters. The lack of outside information, and dense cohesion within the network, removes all possibility for new ideas and innovations.”
To overcome this tendency, it is important to make explicit efforts to establish links between different groups. Examples include different regions of the world (e.g., North America, Latin America, Europe/Middle East/Africa, and Asia Pacific), departments (e.g., circulation, reference, digital, and archives), and roles (e.g., librarians, other information specialists, IT staff, archivists, and administrators).
One of the following conditions typically exists in an organization. These are listed in increasing level of connectedness:
- There are no communities. Small teams work together, but there is limited connection beyond the teams.
- There are some communities within departments. For example, a community of librarians who share ideas.
- There are some communities that span some departments. For example, a community for reference and digital specialists for a specific collection.
- There are some communities that span all departments. For example, a community with everyone involved in a specific subject area.
- There are communities for all important topics spanning all departments and including all roles. This is true boundary spanning.
The higher the level of connectedness you can achieve, the more knowledge will flow between groups. You can use social network analysis (SNA) to help determine the current state of social networks and to identify boundary spanning opportunities.
Social network analysis is mapping and measuring relationships and flows between people, groups, organizations, computers, or other information and knowledge processing entities. The nodes in the network are the people and groups, while the links show relationships or flows between the nodes. SNA provides both a visual and a mathematical analysis of human relationships. SNA can be used to improve communities, identify missing links, and improve connections between groups.
SNA can be used to identify people who are linked, but who may not be part of a formal community. These people can be invited join a community relevant to them.
You can use SNA to bridge silos, create awareness of distributed expertise distributed in the network, and identify and draw in peripheral network members. Valdis Krebs and June Holley asserted that “improved connectivity is created through an iterative process of knowing the network and knitting the network.” SNA enables you to know the network so that you can then proceed to weave new members into it.
Valdis advised to “connect on your similarities and profit from your diversities.” By using SNA to identify those with both similarities and differences, and using this information to better connect those people, you can enable greatly improved knowledge flow within and across organizations. SNA is especially useful in understanding and improving the social networks of individuals, in enabling more effective collaboration by ensuring that the right people are included, and in starting, building, and extending communities.
Enterprise Social Networks (ESNs)
An Enterprise Social Network is an internal, private social networking platform used for communications and collaboration within an organization. ESNs connect people across organizational boundaries, make it easy to share status updates, provide employee profiles for learning about and finding colleagues, and enable private, secure threaded discussions.
An ESN can be viewed as an internal version of social media tools typically used in the external world such as LinkedIn, Twitter, Facebook, Instagram, and YouTube. ESNs offer personal profiles with each person’s bio, interests, photo, and the history of all their posts and comments all in one place. Viewing personal profiles in an ESN makes it easy to find out about other people and what they have shared.
ESNs can be used in three different ways. They can be accessed via versions optimized for web browser, web app, or mobile app. ESNs work particularly well on mobile devices such as phones and tablets, unlike older browser-based software.
Enterprise Social Networks can turn routine communications that used to take place in email or text chat into more interactive dialogues, including photo and video sharing. Essentially an ESN is a modern version of what used to be called a bulletin board or a listserv. It is more visual, has indented threads, and has the ability to add photos and videos. The key use cases for ESNs are sharing information, asking questions, finding resources, answering questions, recognizing colleagues, informing about activities, and suggesting ideas.
Communities are groups of people who share a concern, a set of problems, or passion about a topic. They have something in common, and they come together to deepen their understanding of that topic through online discussions, meetings, and calls.
Community members build trusting relationships as they get to know one another by interacting online or on calls. As they develop trust in one another, they can provide useful help. Members can share information, ask and answer questions, and find expertise and resources.
Communities are fundamental to connecting people with related interests so that they can share with one another, innovate, reuse each other’s ideas, collaborate, and learn together. Starting a community is an excellent first step in launching a KM initiative and can be used as a building block for more elaborate functionality.
Communities enable knowledge to flow between people. Community members:
- Share new ideas, lessons learned, proven practices, insights, and practical suggestions.
- Innovate through brainstorming, building on each other’s ideas, and keeping informed on emerging developments.
- Reuse solutions through asking and answering questions, applying shared insights, and retrieving posted material.
- Collaborate through threaded discussions, conversations, and interactions.
- Learn from other members of the community; from invited guest speakers about successes, failures, case studies, and new trends; and through mentoring.
Connecting people so they can take advantage of the expertise of others is one of the desired modes of knowledge flow in a typical KM program. Expertise locators are systems for finding experts on particular subjects. They help find people who know about a particular tool, industry, or specialty. Identifying someone who has performed a particular kind of work, speaks a specific language, or has a unique skill can be challenging, and expertise locators help meet that challenge.
Individuals enter details about what they know, what they can do, what they have done, where they are, where they have worked, and other pieces of information that might be useful to someone else into the system. Once this has been done, expertise locators enable searching for other people who have the desired attributes, skills, and experience. The search results can be used to connect to the right individuals.
Expertise locators are also referred to as:
- Employee Directory
- Expert Finder
- Expertise Locators
- Expertise Location System
- People Directory
- People Finder
- People Network
- Skills Database
- Skills Inventory
- Skills Profile
- Skills Tracking
- Social Profile
- Staff Directory
- Who’s Who
- Yellow Pages
There are multiple approaches to populating and updating expertise locators, including skills databases, social software profiles, and automated processes.
A self-populated database relies on everyone entering and maintaining their own data, which is difficult to achieve. To avoid this challenge, the database can be fed from internal Human Resources (HR) systems, but this approach is limited by what is available in HR systems and by local privacy laws. Another approach is to feed the data from LinkedIn, which benefits from the fact that most people maintain their own LinkedIn profiles.
An effective way to get people to enter their skills is to display a percent complete indicator next to their name when they connect to the intranet or any internal system. Supplement this with automated reminder messages sent every month until they achieve 100% completion or perform an annual update.
Social Software Profile
Self-tagging and self-rating leaves capture up to the individual. It can be hard to keep the data maintained, and people may exaggerate their own expertise. Peer tagging and peer rating is more objective but may miss some areas of expertise. Official designation by an authority is potentially the most objective but may miss some experts and may become bureaucratic or biased.
An effective way to get people to populate their profiles is to have the senior executive of the organization lead by example. Ask them to complete their profile and to send out a message with a link to their profile, requesting everyone in the organization to complete theirs.
Automated Monitoring and Crawling
To avoid relying on manual expertise identification, automated approaches have been tried, with mixed results. Some systems monitor all email messages and mine the content to determine individual interests and expertise. This can be effective, but it raises concerns about privacy, and can cause resentment and resistance as a result.
Crawling threaded discussions to observe who is answering questions may be preferable to monitoring email, as these are usually openly accessible behind the firewall. But the effort involved in doing so may not be worth it compared to just using the threaded discussions directly to let expertise emerge at the time of need.
Another option is to crawl through libraries and repositories to see who submitted content and to update the skills inventory with the associated topics for each contributor. This approach may suffer from a limited number of contributors and contributions. Crawling personal files would include much more content but would raise the same privacy concerns as monitoring email messages.
Ask the Expert
It can be useful to formalize expertise location by implementing an “ask the expert” process. This can be implemented in several ways. It can be done by tapping into a skills inventory or expertise management tool. Or by developing or purchasing a standalone tool that allows users to enter questions, routes these to designated experts, and returns answers that are also captured in a database.
Another technique is to use existing threaded discussions to reach experts within communities who can reply to questions. This is a typical use of threaded discussions anyway, so adding this capability is simple. To do so, ask the moderator to designate at least two subscribers who are assigned as experts who monitor the threaded discussion. The moderator is usually one of these experts. At least one expert should be on duty every workday. Users can be told to expect an email response within 48 hours with one of the following: the answer to their question, the status of the expert’s search for the answer and when to expect it, or a statement that the answer is unlikely to be provided but may come from other subscribers. If you use this method, you may not need to implement a separate expertise locator tool.
Ask the expert is also referred to as Q&A (questions and answers). The best-known public version is Quora.
In Part 2 of this series, I will discuss connecting people to content.
To learn more, please join us for “The Five Cs of Knowledge Management Part 3: Connect”, the third in a new series presented by Stan Garfield on Wednesday, April 19, 2023 at 11 a.m. Pacific, 2 p.m. Eastern. (Can’t make it? Register anyway and we’ll send you a link to the recording and slides afterwards). Register now or call 604-278-6717
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