What’s in for Me: Why Should I Bother?

I’m part of a Collaboration 2.0 group which started on linkedin, and was moved over to yammer. One of the rules of the group is that you need to work at a big company and do this stuff for a living. This is a great premise! The owner/moderator is thoughtful and engaged, but the group doesn’t see a lot of traffic.

Why is this?
I believe there are a few reasons. (I’ll of course relate this back to OneStop.)

  1. The feedback loop is not well defined.
  2. The value proposition is not crystal clear.
  3. There isn’t enough in it for me.
  4. Metrics

Feedback Loop:
I’ve posted twice to the group. I thought the posts were insightful and would get a discussion going. No responses. I need feedback! Apparently the “what’s in it for me, let’s use the acronynm WIIFM” quotient wasn’t high enough for people to respond.

Value Prop (WIIFM)
I’m part of a half dozen linkedin groups. The vast majority of the posts are from consultants. The value prop for them (WIIFM) is that they are trying to raise their visibility level, (their web based stock price so to speak) and indirectly line up some work.

I started to get active on linkedin when I thought there was a chance my job would disappear. Would I have reached out otherwise? Probably, but not as aggressively. Would I have joined Collaboration 2.0? Not sure. I would probably have monitored (or lurked) to pull out good ideas.

I initiated my blog when I was up for a promotion to Principal Engineer. I didn’t do it out of the goodness of my heart or that I was inately keen on community contribution.

Organizational Credit
One of the reasons people bother to author OneStop pages is that it’s cool. (WIIFM++) They get their pictures at the top right of the pages they author, and become much more visibile in their area(s) of expertise. Most of their managers are supportive as it’s obvious that this sort of information sharing is of high value add to the company. However, this value add need to be demonstrated through…

Metrics
When you see a couple of hundred hits on your page every month it becomes much easier to make the time. It also become much easier for your manager to support your efforts.

At the upper right of the header for this blog it mentions that “carefully crafted processes to make this work in the enterprise.”. Part of the process is rules of engagement. For most communities there really isn’t enough WIIFM, at least from the start. In many cases participants need to get “organizational credit”, or maybe just a direct push from their managers, to participate.

Better Search with Predictive Typing: Can We Do it Better Than Google ?

Many of my favorite sites including google, linkedin, and netflix now have excellent predictive typing support. It strikes me that we should be able to do the same thing on SunSpace, and maybe do it better.In the case of Google, the suggestions returned will be what others are searching for. This list is  influenced  by your own search history.

The Netflix engine searches the universe of Movies and Actors. The list displayed is influenced by the popularity.

Your Linkedin type ahead universe is populated mostly by your connections.

We should be able to take the best attributes of the above!

On SunSpace we have more information to work with. Like Netflix we are searching a bounded universe. There are tens of thousands of movies and actors to select from, verses hundreds of millions of documents in the google index. In SunSpace we have less that 150,000 objects to work with, and lots of information on each object.

On SunSpace we know. (This is all tracked via opaque handles)

  1. Search terms used, for you and for all users on the system.
  2. The documents and wiki pages that were found via search and the search terms used, for you and for all users on the system.

Thanks to Community Equity we also know a lot about each user and each wiki page and document in the system.

  1. Information Value of each document or wiki page.
  2. Meta data for each document and wiki page. (author, tags, last modified, etc.)
  3. Equity value for each user. (based mostly on Information Value of the documents they own.)

As an example, let’s say we are searching for Cloud Computing. Google gives the the following list of recommendations:

Cloud Computing
Cloud Computing Companies
Cloud Computing Wikis
Cloud Computing Leaders
Cloud Computing Stocks
Cloud Computing Architecture
etc.

In SunSpace we can provide you not only with the recommendation of the search term, but also

  1. the most popular cloud computing documents people have found with search
  2. cloud computing documents with the highest information value
  3. interesting meta data for each document.

I believe that people generally utilize type ahead as a time saver, verses as a recommendation engine, so we need to make sure the “expected” results appear at the top of the list. If a user as typing in “cloud computing” in a prior search, that term, and the document the user selected from the results list should appear first.

As a bonus, we can match against the corporate directory in real time, and provide phone numbers and locations for individuals. This is normally a 10-20 second endeavor using the IT supported tool.

Posted at 06:09AM Dec 29, 2009 by Michael Briggs in Sun  |  Comments[0]