It’s not easy to create an office environment where knowledge sharing is a common practice.
One of the most common barriers to sharing knowledge is fear of rejection. If employees think that their ideas will be rejected, they are far less likely to share them. Another problem that inhibits knowledge sharing at the workplace is the hierarchical structure prevalent in many office environments.
Now that you know what the two biggest obstacles to knowledge sharing are, here are 7 tips to help you encourage employees to share their knowledge with others and build an open environment for knowledge exchange that will drive innovation.
1. Learn what’s their passion
It is common for employees to have their most and least favorite parts of a job. There may be areas about which they feel especially passionate and excited. Identify these areas and find a way for employees to spend more of their energy there. You will be rewarded with a higher quality of work and potential pathways for knowledge sharing. For example, a successful social media manager may be able to share their methodology that will benefit other areas of your marketing department.
Expertise sharing and managing knowledge were two different things managed separately. Now research and the popularity of many contemporary social network systems show that they have actually merged together.
Managing knowledge has been an age old concept of effectively utilizing the knowledge resources and revolves around the activities of capturing, storing and reusing it. But then, it is the ‘expertise sharing’ that caught the attention. There are many contemporary social network systems that manage ‘expertise sharing’ but what makes them tick? Is the question.
The thing that both commonly share is the social setup and the prevailing culture of both the organization and the social network environment where they operate. These are the foundations.
It is no longer about using the metaphor of “Knowledge management”. Now the flavor is towards the usage of the word “Expertise sharing”. It does make sense, actually. There is an element of social capital influence in expertise sharing. Social capital develops and flourishes when people see that their actions are reciprocated and that other individuals meet their expectations.
Before we delve into the details, I would like to thank Mark S Ackerman from the School and Electrical engineering and computer science, University of Michigan and Christine Halverson from the IBM T.J Whatson research Centre for their insightful paper ‘Sharing expertise, the next step for knowledge management”. I have referred some content from their paper.
As stated above, the social capital influence consists of three dimensions. Structural, Cognitive and relational. Structural dimension deals with the ability of people to reach out from their comfort zones and seek out information and help from each other. The cognitive dimension deals with shared stories and shared understandings within a group. The relational dimension includes the social norms, trust and obligations within the social network.
Are the structural, cognitive and relational dimensions included in the many expertise sharing systems?
The catch is, when these are embedded, they promote expertise sharing. Expertise sharing works well when the social capital influence is embedded within the current expertise sharing systems.
We will explore the current state of expertise sharing systems. We will look at their challenges and collaboration issues facing them. The most prominent among them is the socio-technical gap. A long existed gap in many collaborative work systems and CSCW.
Useful note: What is CSCW (Computer supported cooperative work)? CSCW is a coin termed by Irene Greif and Paul Cashman in 1984. Its main focus is on the areas where collaboration and coordinated activities are supported and managed by IT systems. It is synonymous with the word ‘Group ware’ systems.
CSCW warrants for a separate blog post and will be published in the future.We will explore some aspects of mitigating this gap as well as bringing in the structural and relational dimensions of social capital to the forefront in addressing these challenges.
We will conclude with a couple of approaches we can take to make expertise sharing an everyday affair.
The current state of Expertise sharing systems
Adding a context to a shared information
Adding a context to a shared information in a knowledge repository is a tedious and a time consuming process.
Useful Note:- knowledge repository is an information system which captures, stores and retrieves information. It also has some rules, structure and taxonomy for recording information.
A Knowledge repository acts as an information base. The initiatives within such knowledge repositories ranged from Data warehousing to Business intelligence. There are many examples to such knowledge repositories. For Example:- Customer relationship management system is a repository of customer information.
The assumption was that people with prior experience in their field would go and share their knowledge in this repository. The challenges in such systems are easily notable and apparent.
The system assumed that all knowledge whether explicit or tacit would be recorded. Secondly, it assumed that people would share information spontaneously and thirdly, people would understand on their own, the context surrounding that information.
One thing we need to understand here is that managing knowledge is not free. There are lots of resources tied to it, as well as time. There is a tedious 2 step process.
1. The person sharing the information has to build an appropriate context around it to relate it to other people. 2. The person receiving the information has to again put the effort of understanding and adapting the information to his or her context.
There are a whole lot of social processes involved in the expertise sharing process.
Accuracy and timely updates
Accuracy and relevant updates in a timely manner is a challenge in expertise recommendation systems. Recommending an expert to a group or to answer a posed question has always been a challenge. It has nothing to do with the recommendation engine on the technology side. It is more to do with the social and relational issues for dynamic changes and situations.
Even though we might have skills inventory, the skills keep changing and the users move on too. The recommended data must be accurate and updated for the recommendation of expertise to be timely and to the point.
Time and resource constraints.
Finding the right resource is difficult and that too on time. People can find expertise themselves. A good example is Quora. People can go online and post their questions and they get answers from anyone from the general public. Such online meeting places requires people of some expertise to help others.
The challenges are, such online systems assume everybody to join the conversation and spend time and energy. The question is how many people have this time to contribute and we cannot expect everyone to be sociable.
Weak bonding between participants.
Weak ties and bonding are a common pattern when peer groups form. Information and communication flows between them. These groups form when there is a common problem to be solved. They actively work on the problem and they disburse when it is solved. But then, even though the group team members are geographically spread out, the same issues persist of finding the right expertise and the data needs to be correct and relevant.
Other issues within this area, are social in nature. The group members need to understand each others work styles and culture which silently influences the overall productivity of the peer group.
The contention and the challenge stated above in all the four areas is not the technology problem that hampers the expertise sharing. It is the social and collaboration issues that needs to be sorted out and all of them suffer from the same social technical gap. Sharing expertise requires us to bridge this gap and surmount the collaboration challenges.
Let’s look at what the social-technical gap is all about.
The social-technical gap for Expertise sharing.
The social technical gap concerns with the underlying social issues when developing or designing technology for expertise sharing. It is the gap between the technology and social phenomenon.
We seriously need to include both the structural and relational dimensions in designing systems to bridge this gap. We looked at this in our previous blog.
On examining things deeply, three big areas emerge which need to be addressed. These are the social findings that are highly relevant in our current society.
Even though human beings are social animals, we have our own nuances in the way we approach others and share information. We wear social masks and have our own social identity online.
We manage and project ourselves differently with different people.
For example, what we tell about success in life with our kids, would be different in how we speak about success in public. Isn’t it.
How we talk to our parents about our happiness would be different on how we talk about it with our spouses. Isn’t it.
Useful note:Social identity is a person’s self –concept in a perceived social group. It was coined by Henri Tajfel and John Turner in the 1970’s. Social identity motivates people to be and show positive distinctiveness among a social network or a social group. This behavior ranges from within the individual’s immediate family to the wider group.
Everyone does this unconsciously without much thinking. Our social activity is both fluid and nuanced. Technology and applications with embedded social network are on the contrary quite simple models. They wouldn’t know this complexity by being fluid and nuanced spontaneously.
Any technology interfering with such social interactions and impression management, cannot foster or nurture the subtleness in the fluidity or nuanced behavior. It is difficult and as such there is a gap.
Compromised Social norms.
By social norms we are talking about rules existing in a social network or social setting. These norms exist even in a collaborative expertise sharing system. The same norms of social behavior exist in even in online social media and other social networks.
Useful note: Social norms are more like “values and rules of behavior” which are considered acceptable in the society. They are all mostly unwritten. It is useful to have a quick reference on the social impact theory, which dwells on the personal importance, urgency and the size of the social network the person is involved with.
Unless there is a strict governing hierarchy in a social network, these rules are broken. We have seen these rules being broken all the time in popular social networks. So the people who are using the social networks are actually constantly reshaping the rules based on their current behavior and needs.
For example, Facebook never started as a photo sharing system. It was initially launched for communicating user status. But then, over the years, the users had evolved and changed the behavior of the system.
This mandates that the social media system or the social network requires a back channel brokering system to mediate and move around the rules and re-write the rules sometimes. Can this be a norm in Enterprise systems? A big question mark.
A special mention on how social identity and social norms affects the real world business scenarios. Assistant Professor Liu Yanju, from the Singapore Management University (SMU) ,School of Accountancy, quantifies how private and social interests interact, and the conditions under which one interest can take precedence over the other.
Liu studied “Sin” industries particularly tobacco and alcohol found that when there are high ‘financial rewards’ involved, the financial analysts backed them ignoring the social norms.
Rewards for everybody
According to the Grudin Paradox, there should be incentives and rewards for everybody participating in the collaborative expertise sharing system. Jonathan Grudin in 1989 framed this concept and is called the Grudin paradox.
Useful note:Jonathan Grudin was a principal researcher at Microsoft research in the areas of Human computer interaction and CSCW (Computer supported cooperative work). The Grudin’s number or the Grudin’s problem is used extensively in designing collaborative software for organizations and social networks.
For example:- What is in the best interests of the landlord may not be in the best interests of the tenants. Tenants may not want to share the number of electric appliances they are using inside the house. Even though this may be part of the house contract for limiting the number. The same case is the case with the Employer and Employee in different scenarios in organizational setting.
So, what we are saying is, everybody needs rewards. In an expertise sharing system both the experts and users need to be rewarded. Practically speaking, “What is in it for me” must be effectively addressed for all the users.
There exists a gap.
Now that we have understood the aspects of the social –technical gap to a good extent, we need to consider how we can move around this gap.
There are some solutions that can be looked into to acknowledge the social processes that needs to be addressed for a expertise sharing system.
Approaches to circumvent the expertise sharing gap
1.A combo of social network, knowledge sharing and expertise sharing.
Knowledge repositories have existed from a very long time in many companies and other social networks. We augment the usage of this repository by combining the prevailing social network in an organization or social setup.
If the user is not able to find an answer for a question in a repository, we can escalate it. The system automatically triggers an escalation and routes it to another expert, a chat session or a bulletin board or even to a help desk.
When the system escalates the question, other users in the immediate environment come to know about it. They are familiar with the situation. As they work in the same environment, they know the context and direct it to the appropriate expert.
Even if there is a discrepancy, the system still provides the answer by linking the knowledge repository with the organizational social networks.
3.Creating virtual social environments explicitly.
By creating a virtual social environment explicitly, new ways of collaboration emerge. People and expertise all come together. Those who have the question and those who have the answers for them.
The questions are visible to the open public and hence they have a broader reach and are able to solicit the best and relevant answers from the experts.
Example: – Quora is a good example of the online expertise sharing social environment.
Useful Note:Quora is a question and answer social network embedded in a social media system. A community of users can ask questions, answer and edit their responses. It is founded by two ex-employees of Facebook in 2009.
Another useful way is to use both the Synchronous and Asynchronous mode of communication. Babble and Loops both projects at IBM are some good examples. Twitter is also another good example of such communication.
All these systems provide new forms of collaboration that is currently happening through these online social networks. These systems are bridging the gap for they serve not only to build social relations but also for expertise sharing.
For further resources on this subject, please find the below links.