“Mr A meet Mr B, he has what you need.”
An online system which can make the above statement happen has the capability for expertise location.
There are multiple online systems in place which help people to find other people with specific expertise. All of these systems start with individuals’ details and aggregate information in a way that is searchable and findable.
A People Directory (a Who’s Who) is considered one of the most important resources within an enterprise. Consumer social tools like LinkedIn, Facebook and Twitter also serve as an important way of finding people that you know or people you want to know. In fact, these online systems have become global directories of contacts and relationships.
The way each of these social tools manages contacts is different depending on their area of focus. For example, LinkedIn focuses on professional contacts whereas Facebook focuses on social contacts.
Social software has matured in the past few years. However, companies are still not fully capitalising on the skills available within the organisation. As this Wall Street Journal article rightly points out:
Talk about a waste! Because of an inability to tap expertise, problems go unsolved, new ideas never get imagined, employees feel underutilized and underappreciated.
Humans are by nature social animals; we depend on others to fulfil our needs. Additionally, the economics of demand and supply can only be fulfilled if needs are clearly known. Online social applications comprising of wikis, blogs, activity stream, tagging, effective search and the like have made it possible to find exactly what we are looking for with ease.
Rich user profiles:
It all begins with information exchange: what others know about you and what you can find out about other individuals. There are two key parts to it:
- What you have
- What you want
What you have:
In his recent article, Alan Hamilton discusses the difference between knowledge and expertise and how social software acts as a glue to bring people together. Alan argues that one’s social contributions are a sure indication of skills compared to an advertised capability.
A person’s expertise is acquired through previous experience, shared knowledge, and/or accreditation. The sum of these criteria determines the worth of an expert in a particular field. People exhibit their own level of expertise through two approaches:
- Their own perception of their expertise
- Demonstrable expertise based on practical experience
When it comes to displaying this expertise in an online system, the more information a user profile can handle and contain within a clean contextual display the more valuable it is. It is also about making it simple for the users to provide as much information about themselves as possible.
Once the information is in the system, the system should be able to slice and dice it in a format which is discoverable. For example, if a user has listed himself as a “motor mechanic”, any search for “automobile engineer” should also list that person.
An important consideration while enabling rich user profiles is that it should be an individual user’s choice if they want their expertise to be displayed to everyone or just to a selected list. Individuals may also have a choice of their preferred contact time, so they do not find the system disruptive by other users contacting them at unsuitable hours.
Although a user should be able to provide their expertise in the system, there needs to be a clear distinction of expertise for which they have been accredited. Accreditations should also be displayed with the expertise, so that an individual trying to find an expert can make an informed decision who to choose from a range of experts. An expert’s prior contributions also help to determine their level of expertise.
What you want:
The needs of people can be met in two ways:
- Searching for and finding an expert to meet the need
- Be introduced to someone who has the expertise
The difference between the above two possibilities is that in the first case you have to go and find the expert, and in the second case the expert is made known to you (the latter being the simpler way).
Discovering expertise through an online system is best supported by expertise matching using a faceted search system. The matching criteria depends on multiple factors, and virtual assets like domain specific knowledge and information can easily be exchanged online without any dependence on location or time. However, some searches will require experts within a certain physical location for instances such as automobile repair.
For an online social software system, browsing for specific content can bring up an expert in that area, for example if you are reading an article on places to visit in London, suggestions can be provided for travel guides in the London area, with their number of years in business and customer reviews helping to choose the right expert.
A search for “director” in the above example not only shows the people who are directors, but also highlights the different content type related to the search term. This helps the user not only find people with the specific skill but also helps to find interesting content related to that area of expertise.
Your network defines your interests:
Online networks are created by connecting people with like-minded people, and this helps to build a recommendation system where experts are introduced to other people with the same need.
Whether it is based on the expertise you have or the skills that you are looking for, your network reflects your interests. People interested in your expertise will be interested in being part of your network and will follow your contributions. Similarly you will be more likely to keep up with people that you are interested in or have the skills you want.
Browsing through a contact’s own connections can be a good way of discovering other like-minded people and connecting with them, helping to expand your network and getting the most value out of it.
Finding what you need:
Once you have started to build your network, the content generated by your contacts should flow into your view and this helps you to discover more information that you are interested in. You can use filtering options to excluding the noise from your feed which helps you to focus on relevant information that you are more inclined to read and contribute to. This also shows how experts, knowledge and information are interlinked.
Taking into account the points mentioned above you can see that HighQ Collaborate fulfils a lot of these expertise location requirements. Expertise location is integrated into Collaborate’s activity stream, search and people profiles. An implicit recommendation system is something which we are still missing, but we do have this on our radar to help our users make even better use of our platform.
If I have missed out any points or features that you would like to see in HighQ Collaborate then we would really appreciate your comments on this blog post.