Deliver Facebook for the Enterprise | Knowledge Management

I attended a webinar from NewsGator called Deliver ‘Facebook for the Enterprise’ with SharePoint

NewsGator, Deliver Facebook for the Enterprise | Knowledge Management

Here are my rough notes, so please forgive typos:

September 11, 2008


  • Deb Bannon Senior Product Manager at Microsoft
  • Laura Farrelly – Marketing at NewsGator

What is social computing (SC)?

  • examples – Facebook, LinkedIn, Wikipedia
  • a collaboration mechanism using the Internet

Many employees are demanding the same type of web functionality in their companies

Social Computing is in the “collaboration spectrum”

  • SC – really about the connection with people rather than about content.

Enterprise 2.0

  • the enterprise use of web 2.0 technologies
  • power is moving from institutions to communities
  • moving from a top down to a bottom up model

Business Drivers for SC:

  • drive collaboration & social interaction
  • capture and share tacit knowledge
  • discover content in new ways
  • capture “wisdom of the masses” via social feedback
  • build sense of connection to the company
  • easy search and find relevant subject matter and subject matter experts
  • encourages participation
  • increases efficiency, productivity and speed

Growth in the Market

  • expected to by over $5B in 2013

Employees want the technology, but IT departments want to make sure the platforms are secure, manageable, and compliant

SharePoint (SP) can be used to bring web 2.0 into the enterprise

  • includes blog and wikis
  • enterprise search
  • consistent user interface and one-stop place for all such collaboration tools
  • easy to customize
  • NewsGator can integrate with SP

NewsGator Demo

  • “Facebook for the enterprise” – short review of what Facebook looks like.
  • Facebook Groups reviewed also
  • There is a risk of using consumer-based social networking products in the enterprise (for obvious reasons)
  • NewsGator’s answer is a dedicated platform for the enterprise (NewsGator’s platform, of course)

Live NewsGator Demo (very much like Facebook):

  • based on fake pharmaceutical company
  • recent activities section
  • anytime a name is displayed, it is hypertexted to the the person’s profile
  • there is a social network graph (this is nice) the closer (physically) the contact, the stronger the connection (not sure how the relationships — or thier strength — are established) Update – Laura Farrelly has clarified this blow in the comments – Thanks Laura!
  • can add tags to communities
  • communities are auto populated with info from SP and news feeds, emails, etc.
  • discussion threads are accessible via email – so that people can contribute via email.
  • RSS feeds (which is NewsGator’s forte)

Example from Universal McCann, which is using SP with NewsGator

  • global media communications agency
  • BTW – Universal McCann’s website is pretty slick (although maybe too slick – it’s a bit hard to navigate)
  • built communities based on area of interest rather than geographic location or projects
  • they use the platform also to connect with their customers
  • Universal McCann has a white paper on their site called The Social Butterfly Effect
  • Link to Universal McCann video case study.

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One thought on “Deliver Facebook for the Enterprise | Knowledge Management

  • September 11, 2008 at 9:05 pm

    Hi There – thanks for attending the webinar and for the great summary. I wanted to help provide more detail regarding your following note in the post:

    “there is a social network graph (this is nice) the closer (physically) the contact, the stronger the connection (not sure how the relationships — or thier strength — are established”

    We think the social network graph is nice too:) The relationships or their strength are based on the actions people are taking in the portal. We automatically track actions such as the articles people read, the feeds they subscribe to, the communities they join, and the tags or keywords they use in the system. We do this automatically without the user having to tell us what they do/like/need. Then we compare each person’s actions and can determine how similar each user is to one another. The more similar users are, the closer they will appear to one another in the network graph.

    Hope this helps. Thanks!

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