A Definition of Noise

FriendFeed co-founder Bret Taylor has a nice interview with CNET’s Dan Farber today. In the interview, Bret mentions that FriendFeed will be introducing ranking algorithms soon. These will create your own personalized FeedMeme.  Which is going to be interesting. Dan Farber then asks whether user controls over content will be rolled soon. Bret answers ‘no’.

In the discussion around this link to the interview, Kingsley Joseph comments:

great interview. Bret’s got it right – ranking algorithms, not filtering is the key to noise processing

This was an interesting comment. I think of noise as a very personal thing. And the ability to define your own take for what constitutes noise makes sense to me. But Kingsley has a different point of view.

So I wondered…are we talking about the same thing. What exactly is noise?

A Definition of Noise

The diagram below is my definition of noise.

Signal is all about the stuff you actually want. For some, it’s a steady stream of social media entries. For others, it may be a steady stream of parenting items. Or baseball discussions.

Discovery is the middle ground. It’s things you weren’t looking for, but find interesting. Maybe Flickr Favorited pictures. An interesting tidbit from the world of science. An Inquisitr celebrity update.

Noise is the stuff you just don’t have the patience to put up with. It’s not anything you’re seeking, it’s annoying you that it’s even on your screen.

In this definition, there’s a fine line between discovery and noise. I’m argue that its the quantity of entries that determine whether something is noise or not. A few items creeping into your FriendFeed is probably all right for all but the hard core signalists. At some point though, when the volume of stuff you’re not seeking crosses a threshold, the entries become noise. You’re not getting enough of the stuff you’re seeking.

Everyone has their own threshold for discovery versus noise. This is the personalization required for noise control. Alexander van Elsas touches on this issue in a recent post:

It’s the noise problem (Try a search on “noise” here for example). How can we find the things that are really important from that huge pile of information floating around. That is partially why we have aggregation and filtering services. Each of them, using one algorithm or another, tries to compile a tiny subset of the universe and present that to its users. The question that remains is whether or not the right tiny space is presented.

Alexander strikes me as being closer to the signalist end of the information spectrum.

FriendFeed Rooms + Ranking Algorithm > Filters?

This brings me back to Kingsley’s point of view that ranking algorithms are optimal for noise control. Ranking algorithms are absolutely terrific. I love them. They provide a lot of benefits in a number of areas (e.g. Google Search).

I’m should also note FriendFeed’s Rooms as the other initiative for isolating topics and controlling noise.

Are they enough to control the noise? It’s hard to say yet. For Rooms to be effective, members are going to need to use them pretty frequently. That can happen over time, but it’s still dependent on the broadcasting member using them. There won’t be 100% compliance because:

  • I can’t perfectly predict what my subscribers will think is noise
  • Likes and Comments on something outside my usual programming put entries into my subscribers’ streams

The ranking algorithms will be interesting. Looking forward to seeing what gets rolled out. Knowing the FriendFeed gang, it’ll be good.

The difficult part is finding the middle ground between the hard core signalists and the discoverers, who like a fair amount of entries outside the stuff they seek. Neither group wants noise, but the threshold for the number of unseeked items varies greatly. My tolerance is pretty high, so I guess you’d call me a discoverer.

Balancing the desires of the signalists and the discoverers, and the varying thresholds of individuals will be the challenge. Let’s see what the ranking algorithms do.

I’m @bhc3 on Twitter.

Tag Recommendations for Content: Ready to Filter Noise?

In a recent post, I suggested that the semantic web might hold a solution for managing noise in social media. The semantic web can auto-generate tags for content, and these tags can be used to filter out subjects you don’t want to see.

As a follow-up, I wanted to see how four different services perform in terms of recommending tags for different content.

I’ve looked at the four services, each of which provide tag recommendations. Here they are, along with some information about how they approach their tag recommendations:

  • del.icio.us: Popular tags are what other people have tagged this page as, and recommended tags are a combination of tags you have already used and tags that other people have used.
  • Twine: Applies natural language processing and semantic indexing to just that data (via TechCrunch)
  • Diigo: We’ll automatically analyze the page content and recommend suitable tags for you
  • Faviki: Allows you to tag webpages you want to remember with Wikipedia terms.

Twine and Diigo take the initiaitve, and apply tags based on analyzing the content. del.icio.us and Faviki follow a crowdsourced approach, leveraging the previous tag work of members to provide recommendations.

Note that Faviki just opened its public beta. So it suffers from a lack of activity around content thus far. That will be noticed in the following analysis.

I ran the six articles through the four tagging services:

  1. The Guessing Game Has Begun on the Next iPhone – New York Times
  2. TiVo: The Gossip Girl of DVRs – Robert Seidman’s ‘TV by the Numbers’ blog
  3. Twitter! – TechCrunch
  4. Injury ‘bombshell’ hits Radcliffe – BBC Sport
  5. Why FriendFeed Is Disruptive: There’s Only 24 Hours in a Day – this blog
  6. Antioxidant Users Don’t Live Longer, Analysis Of Studies Concludes – Science Daily

The tag recommendations are below. Headline on the results? Recommendations appear to be a work in progress.

First, the New York Times iPhone article. Twine wins. Handily. At Diigo gave it a shot, but the nytimes tags really miss the mark. del.icio.us and Faviki weren’t even in the game.

Next, Robert Seidman’s post about Tivo. Twine comes up with several good tags. Diigo has something relevant. And again, del.icio.us and Faviki weren’t even in the game.

Now we get to the trick article, Michael Arrington’s no text blog entry Twitter! The table turn here. Twine comes up empty for the post. Based on the post’s presence on Techmeme and the 400+ comments on the blog post, a lot of people apparently bookmarked this post. This gives del.icio.us and Faviki something to work with, as seen below. And Diigo offers the single tag of…twitter!

Switching gears, this is a running-related article covering one of the top athletes in the world, Paula Radcliffe. Twine comes up the best here. Diigo manages “bombshell”…nice. del.icio.us and Faviki come up empty, presumably because no users bookmarked this article. And none of them could come up with tags of “running” or “marathon”.

I figured I’d run one of my own blog posts through this test. The post has been saved to del.icio.us a few times, so I figured there’d be something to work with there. Strangely, Twine comes up empty. Faviki…nuthin’.


Finally, I threw some science at the services. This article says that antioxidants don’t actually deliver what is promised. Twine comes up with a lot of tags, but misses the word “antioxidants”. Diigo only gets antioxidant. And someone must have bookmarked the article on del.icio.us, because it has a tag. Faviki…nada.

Conclusions

Twine clearly has the most advanced tag recommendation engine. It generates a bevy of tags. One thing I noticed between Twine and Diigo:

  • Twine most often draws tags from the content
  • Diigo more often draws tags from the title

Obviously my sample size isn’t statistically relevant, but I see that pattern in the above results.

The other thing to note is that these services do a really great job with auto-generating tags. For instance, the antioxidant article has 685 words. Both Twine and Diigo were able to come up with only what’s relevant out of all those words.

With del.icio.us and Faviki, if someone else hasn’t previously tagged the content, they don’t generate tags. Crowdsourced tagging – free form on del.icio.us, structured per Wikipedia on Faviki – still has a lot of value though. Nothing like human eyes assessing what an article is about. Faviki will get better with time and activity.

Note that both Twine and Diigo allow manually entered tags as well, getting the best of both auto-generated and human-generated.

When it comes to using tags as a way to filter noise in social media, both system- and human-generated tags will be needed.

  • System-generated tags ensures some level of tagging for most new content. This is important in an app like FriendFeed, where new content is constantly streaming in.
  • Human-generated tags pick up where the system leaves off. In the Paula Radcliffe example above, I’d expect people to use common sense tags like “running” and “marathon”.

The results of this simple test show the promise of tagging, and where the work lies ahead to create a robust semantic tagging system that could be used for noise control.

*****

See this item on FriendFeed: http://friendfeed.com/search?q=%22Tag+Recommendations+for+Content%3A+Ready+to+Filter+Noise%3F%22&public=1

FriendFeed Noise Control, Semantic Web and Dave Winer

On a FriendFeed discussion about the noise on the Web in general, Lindsay Donaghe posted this comment:

Actually I think it’s the same problem we have in general with the firehose of information we’re exposed (or expose ourselves) to on a daily basis. The struggle of where to apply our attention will only be resolved once someone develops intelligent agents to filter the bad stuff and alert us to the good stuff. Wish someone would hurry up and make those. That will be the ultimate killer app.

Louis Gray wrote this recently in his post Content Filters Proving Evasive for RSS, Social Media Sites:

So far, despite many users calling for content-based filters, solutions to block keywords or topics are missing from the vast majority of information spigots.

The recent meme about FriendFeed noise points to the frustration of some people with an inability to manage what content hits their screens. The two comments above underscore this feeling.

Here’s me own example. Dave Winer has two passions: technology and politics. For me personally, technology = signal. Politics = noise. I went through his FriendFeed stream for the month of May, and here are the 38 different political terms that show up:

So what to do? I’d like to suggest that the semantic web might be a solution for down the road.

What Is the Semantic Web?

Semantic web is still a confusing term. Two quotes from Wikipedia help describe it. This quote tells you generally what it’s about and importantly notes that there’s much development for the future:

The Semantic Web is an evolving extension of the World Wide Web in which the semantics of information and services on the web is defined, making it possible for the web to understand and satisfy the requests of people and machines to use the web content. At its core, the semantic web comprises a set of design principles, collaborative working groups, and a variety of enabling technologies. Some elements of the semantic web are expressed as prospective future possibilities that are yet to be implemented or realized.

This quote describes the problem that the semantic web will solve:

With HTML and a tool to render it (perhaps Web browser software, perhaps another user agent), one can create and present a page that lists items for sale. The HTML of this catalog page can make simple, document-level assertions such as “this document’s title is ‘Widget Superstore'”. But there is no capability within the HTML itself to assert unambiguously that, for example, item number X586172 is an Acme Gizmo with a retail price of €199, or that it is a consumer product.

It’s that last sentence there that addresses the noise issue. How does a server know that part X586172 can be categorized as a “consumer product”? That’s where the semantic web comes into play.

And how the noise can be controlled on FriendFeed.

Noise Control: Simplify Users’ Lives

One way to think of the semantic web is as tagging on steroids. In the example above, part X586172 is tagged as “consumer product”. And the tagging occurs without human intervention.

This is what’s needed on FriendFeed. The ability to take a wide range of terms that humans can understand are related. The relationship among the terms is tag.

Here’s what such an algorithm would do for Dave Winer’s political terms:

Now, imagine this in FriendFeed. Semantically-derived tags are appended to every item that flows through. Meanwhile, users have a new ‘Hide’ feature. Hide by topic. They could elect to hide streams with terms on a one-by-one basis. For instance, I’ll hide “robert reich”. I’ll hide “republicans”. I’ll hide “congress”. I’ll hide “obama”. I’ll hide “mitt romney”. I’ll hide…well, you get the picture.

In addition, users could just hide all items with the tag “politics”, and be done with it. Simple.

This could apply for all manner of topics: football, banking, Iraq, etc.

Just How Would These Semantic Tags Be Generated?

I’m not sure anything quite with this purpose exists yet. Reuters has been a leading player in the semantic web with its Open Calais initiative. However, Open Calais focuses of its tagging on people, places, and companies. So if Open Calais was applied to Dave Winder’s FriendFeed stream would have a lot of tags related to those topics. But not metadata tags.

A company called GroupSwim described their semantic tagging approach:

We use natural language processing to analyze the data our customers put into their sites. Our datasets tend to be much smaller but are high quality since someone doesn’t add something to GroupSwim unless they want to share it. Then, we compare the language used in the content to other semantic sources including WordNet, Wikipedia, etc. to do our automatic tagging and analysis.

Interesting, not sure what the tags they produce are. But it does give insight into a requirement: a core foundation of data against which all other data can be compared to derive tags. Something that would correctly map Obama and Clinton to a politics tag.

I’m sure there are other interesting approaches. It’d be great if someone was working on something in this area.

If anyone reading this knows of any semantic approaches that can apply metadata type of tags, feel free to leave a comment.

*****

See this item on FriendFeed: http://friendfeed.com/search?q=who%3Aeveryone+%22friendfeed+noise+control+semantic+web+dave+winer%22

The Noise About FriendFeed Noise

I’m actually enjoying the “noise” of FriendFeed. Anyone else?

Corvida, one of my favorite bloggers, has a post up on ReadWriteWeb titled Don’t Be So Naive: Friendfeed Adds to the Noise. In the post, she argues that FriendFeed is contributing to the noise with a lot of stream that hold no interest to her. Her examples include Flickr and Seesmic streams, as well as Twitters without a comment.

Now there is some truth to the noise issue, but I don’t think it rises to a “we’ve GOT to correct this ASAP” level.

In fact, I find the whole thing somewhat confusing. I love seeing the variety of topics and services that cross my FriendFeed page. Heck, I even added the Greasemonkey script to expand the list of items per page to 100 from the current 30. I hated missing stuff by relying only on the 30 items that appear on the first page.

So what am I doing differently from Corvida? Not sure really. Here’s what I know.

Number subscribers. I checked her subscriptions, and I’m subscribed to 55 more people than she is. So seemingly my risk of noise is higher. But it doesn’t bother me.

Blogger bias. I choose my subscriptions carefully. When I’m deciding whether to subscribe to someone, I tend to prefer someone who blogs. That requirement right there is a good one for managing noise. Bloggers seem to have a good level of signal in their FriendFeed streams. If someone only Twitters or shares items on Google Reader, I tend to hold off on subscribing. These rules aren’t ironclad, but they guide me.

Hiding. As I said, I’m not hiding much. I subscribe to one person, whose friends tend to blog in Chinese. I can’t read those, so I’ve been hiding these friends-of-friend on a one-by-one basis. I may need to hide all of his friends. I’m also close to hiding Jason Calacanis tweets as well. His tweets have a low signal-to-noise ratio for me. But it’s only a fraction of what I’m seeing.

See Louis Gray’s post about the various Hide features FriendFeed has – they’ll help clean up any noise issues you have.

Let’s Keep It Simple

Over-engineering a solution to noise is exactly the wrong thing to do. Beware the unintended consequences. The FriendFeed guys have put a lot of power in users’ hands to manage what is seen.

I have suggested a couple possibilities for cleaning up the duplicate links that can show up in FriendFeed. My guess is the FriendFeed guys are working on something related to that. That would be a help.

But really, let the streams flow. Your noise is my signal. I’m enjoying the content and conversations a lot. I even like the multiple times the same link shows up, because I’m piecing together an implicit social network based on that.

Bring the noise!

*****

See this item on FriendFeed: http://friendfeed.com/search?q=%22the+noise+about+friendfeed+noise%22&public=1

Top posts for: Innovation

Shown below are top blog posts related to innovation:


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What is Innovation Management?

The field of innovation management is much richer and collaborative than the term might connote. It’s not so much “control” management as it is “optimization” management. It’s a recognition that companies have significant margin for improvement in their innovation processes and outcomes.

With that in mind, I wanted to put forth eight elements that help describe “innovation management”. This list is by no means exhaustive, but it should give you a feel for what the field is about today.

  1. Innovation benefits from a range of perspectives
  2. Four of the most damaging words an employee can say: “Aww, forget about it”
  3. Create a culture of constant choices
  4. Looking at innovation as a discipline
  5. Focus employees’ innovation priorities
  6. Recognizing innovation as a funnel with valuable leaks
  7. Establishing a common platform for innovation is a revolutionary step forward
  8. Innovation must be more than purely emergent, disorganized and viral

Read full post >>

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The Four Quadrants of Innovation: Disruptive vs Incremental

People often describe innovation in a fairly narrow sense: disruptive, technological breakthroughs. These are certainly drivers of advances in markets and societies. But they’re not the only types of innovation. The graphic below outlines a fuller view of innovation opportunities:

technology vs market innovations - disruptive or incremental

In each quadrant, there are different rationales and issues that apply.

Read full post >>

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Crowdsourced or Elite Unit Innovation?

The graphic below highlight two very different ways to approach innovation. And that’s a good thing.

Innovation Work Structures

Separate Division: As advised by Clayton Christensen, this approach is best for companies that need to address disruptive innovations. And all companies need to address disruptive innovations.These days, it’s not a matter of if, but when. For fundamental market shifts, too much is invested in the current operations for companies to address changes. Freeing a group of people from these constraints is critical, if the corporate culture is not open to big-bet innovations.

Integrated into Daily Work: In this work structure, everyone is involved in innovation. The company sets expectations, and encourages employees’ to share ideas. Done right, this is in-the-flow stuff. Employees are encountering issues to be addressed daily, and they’re hearing new customer feedback all the time. They are well-positioned to come up with innovative solutions and products, if senior management makes that a priority.

Read full post >>

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Tapping Communities to Accelerate Corporate Innovation

I gave a webinar with Oliver Young of Forrester. The webinar focused on deriving ideas from organizations’ communities: employees, customers, partners. The presentation is built around four themes:

  1. Strategic importance of innovation
  2. Email <> community
  3. Corporate innovation is more than a popularity contest
  4. You can’t manage what you can’t measure

Rather than rely on ad hoc, siloed forms of communicating ideas (like email), social networks provide a new way to tap communities. The diagram below shows the process by which innovation is fostered with a social innovation platform:

Community-Driven Idea Management

Read full post >>

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Does Self-Censorship Help Innovation? The Enterprise 2.0 Approach

Credit: gerriet

Credit: gerriet

The gist of Mark’s post is that encouraging the contribution of ideas from all quarters is actually counterproductive. He prescribes the concept of an “appropriate” number of ideas.

Wow. Really?

The post makes some good points, but I’m not in agreement with its overall tone. As I read the post, it struck me that there are really only two ways to reduce the number of ideas:

  • Limit who gets to contribute ideas
  • Have everyone self-censor ideas that they “know” will be noise

This perspective is quite different from the tenets that are driving the Enterprise 2.0 movement.

Read full post >>

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Your Brainstorming Sessions Suck? Four Drivers of Success and Where the Web Helps

Here are the four drivers for getting the best ideas from brainstorming:

  1. The sheer volume of ideas generated
  2. Average quality of all ideas generated by brainstorming
  3. The amount of variance in the quality of generated ideas
  4. Ability to evaluate what the best ideas are

INSEAD and University of Pennsylvania researchers studied existing literature. A must for any researcher. They then created their own field study, using Wharton students in brainstorming experiments. Now whether that fairly models company brainstorming…let’s see what they found, eh?

Two styles of brainstorming were analyzed:

two-methods-for-brainstorming

Read full post >>

My Ten Favorite Tweets – Week Ending 073109

From the home office in Honolulu, Hawaii…

#1: Gartner Social Software Hype Cycle is out. See where 45 technologies are in the cycle (via Spigit blog) http://bit.ly/19Uw6k #e20

#2: Does Silicon Valley noise detract from long-term value creation? http://bit.ly/188Trx by @andrew_chen #innovation

#3: CNET: A Google Wave reality check http://bit.ly/34fv21 I, for one, love seeing the painful process of development, even at Google.

#4: I think we need a recount: EvanCarmichael.com ranks the Top 50 Geek Entrepreneur blogs http://bit.ly/YT1nn I come in #7 behind @louisgray

#5: The Atlantic: The Truth About IQ http://bit.ly/1l0qfR “Being branded with a low IQ at a young age, in other words, is like being born poor”

#6: The science of hunches? http://bit.ly/CDTJi by @berkun Like his take about the importance of emotions in the decision process

#7: Creating psychological distance f/ a problem is key to increasing your creativity. Make it abstract http://bit.ly/f7XUy #innovation

#8: BofA to Shut 600 Branches Due to Surge in Online & Mobile Banking http://bit.ly/14S4mg I never go in branches. Purely web + ATM.

#9: Ever wonder why we swing our arms when we walk? Research finds it’s more efficient than keeping our arms still http://bit.ly/O0Pwj

#10: Our friends’ 3 y.o. son cut the ribbon on remodeled SF playground today. He has spinal muscular atrophy, & can now play http://bit.ly/Z3DZR

Does Self-Censorship Help Innovation? The Enterprise 2.0 Approach

Credit: gerriet

Credit: gerriet

Came across this interesting perspective on the blog of Mark Turrell, CEO of idea management software company Imaginatik, in his post Myth #3: “We need lots of ideas”:

The next time someone tells you that you need lots of ideas, stop, think and work out the outcomes you want before you go collecting thousands, and thousands, and potentially more thousands of fluffy, non-relevant ideas that go nowhere.

The next time someone tells you that you need lots of ideas, stop, think and work out the outcomes you want before you go collecting thousands, and thousands, and potentially more thousands of fluffy, non-relevant ideas that go nowhere.

The gist of Mark’s post is that encouraging the contribution of ideas from all quarters is actually counterproductive. He prescribes the concept of an “appropriate” number of ideas.

Wow. Really?

The post makes some good points, but I’m not in agreement with its overall tone. As I read the post, it struck me that there are really only two ways to reduce the number of ideas:

  • Limit who gets to contribute ideas
  • Have everyone self-censor ideas that they “know” will be noise

This perspective is quite different from the tenets that are driving the Enterprise 2.0 movement. There are three elements of Enterprise 2.0 that are relevant here:

  1. Emergence
  2. Filters
  3. Culture

One disclaimer. My company is Spigit, which provides an enterprise innovation platform. We integrate social software heavily into our application, so naturally my take on Mark’s post will differ. But readers of this blog know I’ve been part of the Enterprise 2.0 field for a while. Perhaps my perspective isn’t so surprising.

On to it then!

Emergence

Credit: Dion Hinchcliffe

Credit: Dion Hinchcliffe

Are ideas the province of a privileged few?

Emergence is a cornerstone of Enterprise 2.0. The principle says that ideas and knowledge are found throughout an organization, not just in the executive suite. In the daily rhythms of their work, employees everywhere build up an immense trove of experience and learnings. They encounter the “why don’t we?” questions every day. It’s tapping these ideas and knowledge that drives the value proposition of Enterprise 2.0, and is reshaping the corporate workplace.

In the graphic to the right, Dion Hinchcliffe provides a basis for considering traditional software versus social software. There is, obviously, a need for both inside companies. For instance, financial accounting is not an emergent activity. The SEC and FASB have very specific standards for companies to follow. Auditors have a series of criteria they use to confirm the integrity of a company’s financial statements. Centralized control and access are important here.

Innovation, on the other hand, does not have similar constraints. There are really two limits for business innovation:

  1. Do ideas meet the strategic direction of the company?
  2. Does the company have the resources to turn an idea into an innovation?

The nature of innovation – what’s next? – means that tapping the full power of an organization is important. That doesn’t mean that everyone is constantly ideating. Things do need to be done. But as Stefan Lindegaard writes in his post Should everyone work with innovation?

On the other hand, every employee should be given the opportunity to work with innovation even at a certain radical level through a variety of initiatives setup by your innovation leaders. This could be idea generating campaigns, internal business plan competitions and innovation camps.

That strikes me as the right answer. No limits on employees’ opportunities to contribute ideas.

Filters

“It’s not information overload. It’s filter failure.” Clay Shirky, Web 2.0 Expo.

The issue of how to handle an avalanche of contributions – ideas, requests, information – has emerged as an acute issue with the proliferation of online media. You’ll find people discussing issues of noise vs. signal, “email bankruptcy” and the need to pare down their social networks.

Clay Shirky gets it right in his philosophical positioning. The capacity of every individual to generate contributions is significant. That’s not going away, and as we’ve seen with the use of Twitter in the Iranian election protests, it shouldn’t.

Rather, the focus needs to be in refining the ways people manage information. Instinctively, you know when a piece of information is valuable. Have you stopped to consider why it was valuable? What were the contextual variables that made it so?

The application of filters is an ongoing effort by the industry, made more pertinent by the “roll-your-own” approach of many social media sites. But think about this: Google has been employing filters for a decade. The Google PageRank is an important filter for displaying search results. PageRank is a form of authority, based on a website’s inbound links.

Here in 2009, an array of tools are available for filtering contributions. A key tool is leveraging what a community finds valuable. Distributing the work of defining value to thousands of different people is proving to be a powerful way to identify signal. Take for example, the My Starbucks Idea site, there are currently 9,500 ideas there. Sure, it’s a lot. But the community has done a tremendous job of filtering those ideas. You can see that when you compare the top 20 to the bottom 20.

What are some other filters? For idea management, here are just a few:

  • Minimum community approval level
  • Tags and key words
  • Latest ideas
  • Ideas within specific categories
  • Ideas with minimum number of votes
  • Ideas with minimum number of views
  • Ideas with minimum number of comments
  • Ideas in a specified stage of evaluation

You get the gist of this. Social software is evolving to provide better and better ways to filter through contributions.

One other issue with following a hard-coded view of what’s signal and what’s noise: Your noise might be my signal. It depends on what you’re working on. As the graphic below shows, it’s really about stuff you’re seeking. And even the stuff you’re not seeking can be classified as discovery, fuel for innovation.

a-definition-of-noise

This is the value of a rich quantity of ideas. Signal and discovery can come from anywhere.

Culture

If you treat everyone like sheep, you’ll end up with employees who are sheep.

My view here is informed by working in several different companies, both large and small. I’ve been exposed to cultures where employees are assumed and expected to contribute fully and meaningfully, and to cultures where the attitude is “when I want your opinion, I’ll give it to you.”

Changing the latter mindset is what Enterprise 2.0 is about. It taps a rich vein of contributions that have value in their own right. It also creates a work environment that most employee surveys show is highly desired and sought after.

Talk of there being an “appropriate” amount of ideas, and that most employee contributions constitute “noise” is antithetical to the direction companies are heading. For example, AT&T published a white paper several months ago, The Business Aspects of Social Networking. The paper looks at the opportunities that the rise of social networks is bringing, both externally with customers and internally with employees. Included in that paper is this table:

AT&T white paper - leadership styles

AT&T has 300,000 employees and a long history in the United States. The fact that they’re talking this way is a good indicator that the market is moving towards a more collaborative, participatory environment, away from the same old controls that have marked work for centuries.

If employees are expected to self-censor their noisy ideas, that will have a chilling effect on participation. After all, you might risk embarrassing yourself, and incurring the wrath of people who monitor for noise. Why bother?

Bring the Noise

Innovation is built on the contributions of many people, and many experiences. This is something stressed in both Scott Berkun’s Myths of Innovation and William Duggan’s Strategic Intuition. Incorporating these three elements of Enterprise 2.0 – emergence, filters, culture – are powerful drivers of innovation for companies.

So let a thousand ideas bloom!

Tapping Communities to Accelerate Corporate Innovation

Jim Collins related a story back in 1999 that well-describes the problems with and opportunities for innovation inside organizations. In a Harvard Business Review article, he wrote about Phil Archuleta, a materials manager at a U.S Marines recruiting depot in San Diego.

The Marines would issue new enlistees a uniform on their first day in the service. After two weeks of intensive training, these recruits needed a new uniform because the initial ones no longer fit. Marine policy was that the recruits original uniforms were to be destroyed. That’s right, thrown away.

Archuleta thought that policy was daft, and that the uniforms could simply be washed and used for the next class of recruits. He asked his superior, and was told, “No. It’s against regulations. Forget about it.” Eventually, Archuleta got a new supervisor who thought he had a good idea, and promoted it up the military chain. The idea was well-received at the higher levels, and implemented across the Marines. It resulted in annual cost savings of half a million dollars.

How many ideas by the likes of a Phil Archuleta are buried inside organizations?

Tapping Communities to Accelerate Corporate Innovation

The presentation below is one that I gave for recent webinar with Oliver Young of Forrester. The webinar focused on deriving ideas from organizations’ communities: employees, customers, partners.

The presentation is built around four themes:

  1. Strategic importance of innovation
  2. Email <> community
  3. Corporate innovation is more than a popularity contest
  4. You can’t manage what you can’t measure

Strategic value of innovation

Certainly this qualifies as an obvious notion. Innovation is important to companies. It’s the source of organic growth. But in many ways, companies are not treating it as important as other processes, such as supply chain management and cost accounting. Thus, it is important to reiterate the obvious.

Boston Consulting Group analyzed the shareholder returns for companies in its Top 50 innovators list. It compared these returns to markets averages, and found that best-in-class innovators generated 430 basis points more in returns than did the market. Aberdeen Group surveyed 280 manufacturers, and characterized their innovation capabilities as best-in-class, average and laggard. Best-in-class innovators, who far more consistently hit new product revenue targets and launch dates, were 4.7 times more likely to create specific processes for idea generation.

No surprise then that senior executives rank innovation as a top 3 priority.  Accenture well-describes the goals and aspirations of companies: create repeatable and ongoing improvements in business performance.

Key, of course, is to consider innovation among the disciplines in which a company should excel. And create a program for it accordingly.

Email <> community

I’ve worked for large companies. I know how it goes when you have an idea. Jot it down somewhere. Talk it out with someone. Then email someone else about it. If you’re lucky, someone in that email will pick it up. Maybe.

More often than not, interesting ideas just sort of lie there, buried in the minutiae of the daily grind or not catching the interest of a particular individual. Which is what happened to Phil Arhuleta’s idea about the Marines’ uniforms.

Rather than rely on ad hoc, siloed forms of communicating ideas (like email), social networks provide a new way to tap communities. The diagram below shows the process by which innovation is fostered with a social innovation platform:

Ideas are the social objects for community interaction

Ideas are the social objects for community interaction

On the top left, it’s important that companies understand: ideas can come at any time, in any form. They’re rarely subject to scheduling. Once you have an idea, there’s needs to be an easily accessible, and easily usable,  site for the posting of those ideas. No more silos!

Creating a common site is critical aspect #1 of creating an innovation program. Employees, customers and partners should have a single place where each community can go to post the ideas that occur to them.

Critical aspect #2 is the ability of the community to provide feedback on an idea. Separating the good from the bad, and refining ideas to help them take shape are the heavy lifting of emergent, social systems.

In the upper right, the refinement of good ideas takes shape. This includes the feedback from the community, as well as offline activities around the idea, such as design work, marketing plans and financial analysis. Finally, in the lower right, the company selects an idea based on community feedback and refinement.

Aside from the benefit of actually knowing about a lot more valuable ideas, there’s another benefit to community-driven innovation management: ideas get better when they’re subject to diverse points of view and knowledge. See the earlier post What Enterprise Social Networks Do Well: Produce Higher Quality Ideas to understand that effect.

Finally, the graphic below describes the community innovation cycle:

Bottom-up innovation requires top-down support

Bottom-up innovation requires top-down support

I think the concepts of expand community and pipeline of ideas are relatively self-explanatory. And I just discussed the engage, access, refine, select part of the cycle. The other two are the top-down support needed to ensure the community feels their efforts matter.

Keep in mind that when people suggest ideas to companies, these aren’t just conversation starters with their fellow community members. People want to know that companies listen to good ideas and take action. That’s quite clear to a community when its ideas are actually implemented, and there is a reward and recognitions for its members.

Executives go a long way, particularly with employees, when they make the company innovation program a focus point. Employees will take their priorities from senior management, and executive sponsorship is an important factor for creating an ongoing, sustainable innovation program.

Corporate innovation is more than a popularity contest

The most common notion of community innovation is the principle of: one person = one vote. An idea that receives a lot of votes clearly is more useful and valuable than an idea receiving fewer votes. This “rule” works well with products that exhibit these characteristics:

  • End buyer requests
  • Lower complexity features
  • No concentration of buying power

That last bullet needs a little explaining. Dispersed buying power means that basically you can consider each vote to be the equivalent of one product purchase. If you have a few customers that generate a significant amount of your sales, their votes should carry more weight.

There are going to be plenty of ideas that require stronger stuff than basic popularity. I like the way Microsoft’s Haddow Wilson put it:

There are times when the collective wisdom is what we need. But what about those times when we need to make a strategic decision and only a few in the crowd have the necessary background and insight to help? How do we separate the knowledge from the noise? How do we know to whom to listen? How do we find them?

Innovation communities need a way to identify those whose opinions should carry greater weight. They essentially need reputation systems to identify members with greater standing among the community. This stature can be assigned or earned.

You can’t manage what you can’t measure

The ethos and value of Enterprise 2.0 focuses on the emergent, authentic nature of employee contributions. It’s historically been hard for employees to apply knowledge in a timely fashion. In this culture, “management” is often a loaded word, with connotations of over-processing and controlling the ways in which employees collaborate.

But that should not stand in the way of measurement. You can have measurement of outcomes, and inputs, and use that to guide the community generally in the direction you’d want to take an innovation program. On the flip side, if a community continues to generate ideas that aren’t squaring with the company’s vision of where it wants to go, it’s porbably wise to listen to them.

Either way, measurement provides a view into the health of the community (posts, comments, views, etc.), the sources of the ideas (groups, categories, product lines, etc.) and the traction that ideas put on the platform are getting (stages, implementations).

Measurement is also the basis for analytics used to surface the best ideas from the rest. One other thing measurement does is this: it positively affects the culture of companies.

Performance and Culture

Breed performance, change culture

The transparency that measurement on an innovation management platform provides is healthy. Everyone can see the bases by which ideas advance. Everyone knows how their own ideas are faring, and can do something about it. This happens because of measurement.

It’s about creating ongoing, sustainable innovation

Companies will benefit greatly once they establish an ongoing program of innovation. It’s too often takes phenomenal acts of heroism to get an idea through the ad hoc channels and processes that dominate corporate innovation today.

Time to treat innovation as a discipline worthy of its own resources and focus.

Why Professionals Should Continue to Blog in the Era of Twitter

I’ll bet you’re smart.

I mean, you’re likely college educated. Maybe even grad school. You can probably remember some killer instances where you nailed some assignment. That clever C++ hack. The time you delivered an insightful analysis of Vonnegut. Navigated your way through a thorny financial analysis. Came up with an elegant solution  in the chemistry lab.

You’re good. You’ve got knowledge in your field, you’ve got a track record of accomplishments in your job. And you’ve got solid points of view about your field and its future.

And all you want to do is tweet?

A number of people have blogged about the uncertain future of…uh…blogging. I understand where they’re coming from. Here’s how Jevon MacDonald put it:

I don’t know what the fate of blogging is, but as I think about it I wonder if it can survive without changing. Just in the last 2 years we have seen massive uptake in the creation of content by users, but most of it is now outside of the blogosphere. Status Updates on Facebook, Twitter, new levels of photo sharing and geolocation based services and networks are all becoming the centerpiece of attention.

His point is that with the ease of Twitter and Tumblr, the relevancy of and desire to blog is diminishing. He’s not alone, it’s a theme that’s been popping up in the last several months.

To which I say:

If you’re a professional who’s just going to twitter, you are missing a golden opportunity to help yourself via blogging.

This post is geared towards those who have day jobs, and for whom blogging and tweeting is an extension of their professional lives.

OK, smart reader, let’s talk about this.

A Blog Is Your Stake in the Ground

Twitter is wonderful. I’ve been tweeting it up the past few months myself. I’ve gained a whole new appreciation for the power of Twitter. As I said in a recent post:

Twitter has established lightweight messaging as valuable and addictive. From the simple roots of “What are you doing?”, people have morphed Twitter into a range of use cases. Open channel chats. News updates. Sharing articles and blog posts found useful. Polls. Research. Updates peers on activities and travels.

It’s great for what it is. And an important part of your professional persona and career development.

But blogs are the professional’s curriculum vitae. They are a standing record of strong thin king about a subject. When you devote the time to put together a blog post covering your field, you’re likely doing this:

  • Research
  • Analysis
  • Linking to others
  • Establishing your voice
  • Influencing the thinking of others
  • Showing the ability to pull together longer form thinking, a requirement in professional work

My own experience is that if you blog, every so often you pop out a signature piece. The kind of post that resonates with others and establishes your position in your field. These blog posts receive a lot of views, get linked to and turn up in Google searches. When you get one of these, congratulations! You have successfully put your flag in the ground for your field.

Tweets don’t do that. Tweets create a tapestry of someone, they foster ambient awareness. This has value in its own right. But they’re not vehicles for heavier thinking. They don’t demonstrate your capacity to size up an issue or idea and bring it home.

Keep in mind that LinkedIn now lets you add blogs to your professional profile. What’s going to be more valuable to you when people are running searches? Tweets or well-thought blog posts?

There’s a Flow to This

I know this is definitely early adopter stuff. The number of professionals spending time tweeting and blogging is still limited. But I suspect this is going to happen:

Those who can work blogging and some twittering into their regular activities are going to earn more money and get promoted faster.

I can’t wait until some academic study comes out about this.

Here’s how I see the way Twitter and blogging mix:

professionals-social-media-flow

Tweets engage you in a flow of information, they let you pick up signals and connect with others in your field. From all that, you gain a healthy perspective on what’s happening in your industry. Once you write a post, you’ll find yourself energized to engage once again via Twitter. And on goes the cycle.

The mere act of writing out research, analysis and opinion is amazingly valuable. No burdens for how that memo plays with your boss, or keeping your thoughts on-topic for the upcoming meeting. Just you and your blog, working through what interests you.

Could You Really Tweet These?

As an example, I’ve selected three posts from this blog. They were some that really worked out there. And I’ve tried to convert them into a tweet. Take a look:

blog-posts-with-tweet-alternatives

There’s no replacing the permanence or deeper thinking that blogs provide.

So What Are You Waiting For?

That’s my view on why you should keep on blogging even as you tweet. Let’s take this one out with quotes from three bloggers:

Bill Ives:

TwiTip recently had a post on Ten People All Twitter Beginners Should be Following by Mark Hayward. I will let you guess who is on it and then go to the post. It is no surprise that a number of top bloggers are one the list.

With the continuing evolution of tools, blogging is becoming more focused on what it does well – moving beyond sound bytes and providing a permanent accessible record of thought.

Eric Berlin:

Here’s my new thinking: probably the best and most successful bloggers will also tend to be the best blogger/microblogger hybrids, and vice versa.

Steven Hodson:

For us this means less competition and less noise for us to fight our way through in order to get through to the readers. This of course is my first reason why bloggers should be thankful for services like Twitter and FriendFeed – they help clear out the noise makers.

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22Why+Professionals+Should+Continue+to+Blog+in+the+Era+of+Twitter%22&who=everyone

Use FriendFeed Lists and Rooms As Your Platform for Information Flow

Fred Wilson tweeted this recently:

i want to follow less people and more keywords in my twitter timeline. can’t wait for summize to get integrated into twitter

I agree with this sentiment – selected topics from a broad population, and broad topics from a selected population. When it comes to learning about particular subjects, it’s right on. FriendFeed’s beta version now gives you the ability to do exactly what Fred Wilson suggests for any topic. I’ll describe how I’m using them to track developments in the world of Enterprise 2.0.

Streaming Keyword-Based Content into the Enterprise 2.0 Room

About three months ago, I tried a little experiment. I created the Enterprise 2.0 Room on FriendFeed.

Not having time to be a Room Community Manager, I set it up to stream in content related to Enterprise 2.0. I did this as a search on FriendFeed for “enterprise 2.0“.

Well, the idea was neat. The actual implementation pretty much blew.

Because a search on FriendFeed, piped into FriendFeed as an RSS? It produces a lot of recursive results. Made the room pretty noisy and not particularly attractive to follow.

So I’ve cleaned up my act. Here’s what’s up:

  • No more FriendFeed searches
  • Using Summize Twitter Search to source content
  • Using Del.icio.us tags to source content

I’m piping in RSS feeds from Twitter and Del.icio.us. Twitter is great for those little hits. The links to content. The expression of a single perspective. And Del.icio.us is great for leveraging what people decided was worth saving.

Here are the search terms I’m using for the two services:

  • Twitter: “enterprise 2.0”, “E2.0”, “social computing”
  • Del.icio.us: enterprise2.0, enterprise20

In Case You Don’t Want it in Your Home Feed

Rooms can be set so that their entries don’t hit your Main FriendFeed stream.

You can un-check the box there that says “Show me this room’s items on my FriendFeed home page”. This works fine for Original FriendFeed.

The other option is to use Beta FriendFeed. In Beta FriendFeed, Lists have become the cool new feature. I have to admit, I’m finding it a lot easier to manage content via Lists than Rooms.

You can create a List called Enterprise 2.0. Rooms can be added to Lists. As if the Room was some sort of person on FriendFeed, streaming all sorts of content. Cool idea.

So you can run the entire Enterprise Room through a List if you want:

As you can see in #2 above, I’ve taken the Enterprise 2.0 Room out of my Home Feed. It only pipes into my Enterprise 2.0 List.

The cool thing about using Lists is that you can supplement the Twitter and Del.icio.us feeds of the Enterprise 2.0 room with other people or Rooms you like. For instance, I’ve included the FriendFeed accounts of Dion Hinchcliffe, Charlene Li, Ross Mayfield, Thomas Vander Wal and others into my personal Enterprise 2.0 List. For people not on FriendFeed, I also have created imaginary friends to pipe them into my List, such as the tweets of Harvard professor Andrew McAfee.

The Future: Keywords + People

Repeating Fred Wilson tweet from above:

i want to follow less people and more keywords in my twitter timeline. can’t wait for summize to get integrated into twitter

That pretty much describes my List set-up of the Enterprise 2.0 Room + specific FriendFeeders.

If you’re interested in a single place to track the happenings of Enterprise 2.0, I invite you to join the Enterprise 2.0 Room. Then personalize things with your own List. If you think of any search terms or data sources I should add, please let me know.

And feel free to start your own Rooms and Lists for topics you care about.

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22Use+FriendFeed+Lists+and+Rooms+As+Your+Platform+for+Information+Flow%22&public=1

Tag Clouds for Our Lifestreams

We are marching down the lifestreaming road. There are a proliferation of lifestream apps, such as FriendFeed, SocialThing, Strands, Swurl and others. Lifestreaming is getting hotter, and there’s some thought that lifestreaming will be the new blogging:

Sites and social tools like these and many others encourage more participation on the social web than ever before. Although the social participants on these sites are often more active in socializing than they are in blogging, there’s still that need to stake out your own piece of real estate on the web. But we wonder: does that really need to be a blog anymore? Perhaps not.

It’s a great concept, one that Mark Krynsky has been chronicling for a while at the Lifestream Blog.

An area I think that is ripe for inn ovation here is the ability to find the meta data from one’s lifestream. On FriendFeed, people will have multiple services that fill up their lifestreams. A couple issues that crop up on FriendFeed are:

  • Figuring out whether to subscribe to someone
  • Catching up on what particular individuals have been streaming

Because there is one thing that has been noticed with all this lifestreaming – there’s a lot of information generated (or “noise” as some might say).

So here’s my idea:

Create tag clouds for our lifestreams

What do I mean? Read on.

FriendFeed Lifestream

I’ll use the lifestream service with which I’m most familiar, FriendFeed. Here are the tag clouds I’d like to see for each user’s lifestream:

  • Blog
  • Music
  • Google Reader shares
  • Bookmarks
  • Twitter
  • YouTube
  • Flickr
  • Digg
  • etc…

And I’d like to see tag clouds for what users Like and Comment on. Because on FriendFeed, Likes and Comments have the same effect as a direct feed of someone’s lifestream: they put the content into the feed of all their followers.

So via the tag cloud, I’m can quickly come up to speed on what someone is interested in.

Let’s Make Tagging Easy

I don’t propose that users suddenly tag their own streams. Rather, let’s leverage the work of others.

It’s de rigueur for Web 2.0 apps to include tagging. Bloggers tag. Social bookmarkers tag. Music lovers tag. Why not pull the tags applied to the source content into the lifestream?

Here’s what I mean. My blog has plenty of tags. These tags are included in the RSS feed of my blog. So any feed that includes my blog should include these tags. Let’s leverage:

  1. The tags that people apply to their own Web 2.0 content
  2. RSS/Atom feeds that include tags

For some background on this, click here for a page on Technorati that talks about tags in feeds.

By leveraging the tagging work already resident in user-generated content, one can quickly build up a tag cloud for lifestreams.

An Example: Google Reader Shares

Google Reader is a good example. People ‘share’ blog posts they read via their Google Readers. Sharing lets others see the articles that someone finds interesting and useful. And of course, those blog posts that someone is sharing have tags.

Here’s what the tag cloud of my recent Google Reader shares looks like. I’ve simulated the tag cloud by using Wordle for the tags.

You can see my interests lately: Enterprise 2.0, FriendFeed, social media. If someone wanted to get a quick sense of the things they’ll see by subscribing to me, this tag cloud answers that. And if someone is curious about the specific posts I’ve been sharing that relate to a subject, they could click on one of the tags and get a list of my Google Reader shares.

Curious, I ran the same analysis on the Google Reader shares of four people I follow on FriendFeed: Robert Scoble, Louis Gray, Sarah Perez, Mike Fruchter. Here are the topics they’ve been sharing lately:

Robert Scoble clearly is following the iPhone and Google. Louis Gray was following the happenings at Gnomedex. Sarah Perez is pretty even in her interests, with FireFox, social bookmarking, FriendFeed, Twitter, search and photos among her favorite topics. Mike Fruchter has been reading up on Twitter and social media.

Just like that, I’ve gotten a sense for their interests right now. And if those were true tag clouds, I could click the tag and see the Google Reader shares. Robert Scoble is really good at tracking useful relevant things. Clicking the ‘iPhone’ tag and reading his shares would be a quick way to understand what’s goin.

Tags + Wordles

As I said, most user generated content comes with tags these days. So pulling these into the feeds and representing them in a tag cloud would be a fantastic move forward in creating lifestream tag clouds.

But what about Twitter? There are no tags on tweets. Not a problem. FriendFeed and other lifestream services could do a Wordle-like tag cloud. Tally the most common words in someone’s tweets, represent it as a tag cloud. And make the tag cloud clickable, which would essentially run a Summize Twitter search of the user’s tweets for a given tag.

Use Existing Metadata to Solve Two Problems

The key here is to not make it onerous on the end user. Tag once, re-use everywhere. If desired, users could be given the option to add tags to their own lifestreams. But the core idea is to eliminate double tagging work for users.

If this could be done, you’ve got a visual representation of people’s lifestreams. And an easy way to find the specific entries in a lifestream that relate to a topic.

Lifestreamers – would you want something like this

I’m @bhc3 on Twitter.

I’ve Joined Connectbeam, and Social Media Got Me the Job

On Wednesday August 13, I start my new job as Senior Product Manager for Connectbeam. Connectbeam provides social bookmarking and networking to the enterprise. The goal is to foster better information management and discovery, and to connect colleagues around projects and common interests.

Going a bit further, here is a note from privately-held Connectbeam’s about page:

Connectbeam’s architecture and core application (Spotlight) were designed to help people in any role, across the enterprise, connect with both the growing pool of information and colleagues with the expertise and experience to help them get their jobs done more intelligently and more quickly. We enable this by aggregating the social metadata that is generated naturally by using the web into a single repository that everyone in the company can access and use.

Current customers include: Procter & Gamble, CSC, Bristol-Myers Squibb, Honeywell, 3M, Intel, Pfizer and Booz Allen Hamilton.

Why Connectbeam?

The problem Connectbeam is tackling greatly interests me. How to manage information to make individuals smarter, help people find information and determine the ways in which common interests establish and build relationships. There are many posts on this blog along those lines. Here are six of them:

  1. FriendFeed ‘Likes’ Compatibility Index
  2. Hey Yahoo! Forget MSFT, GOOG. Change the Search Rules.
  3. Who Is Your Information Filter?
  4. Knowledge & Innovation: The Journey Is as Valuable as the Destination
  5. Tag Recommendations for Content: Ready to Filter Noise?
  6. Social Media Consumption: You Want Signal or Discovery?

I also like Connectbeam’s delivery model. I am a fan of cloud computing, and in my experiences at eFinance and Pay By Touch, customers got comfortable. But I also ran into companies that only wanted applications behind their firewall, which is what we sold at BEA Systems. Security, control and reliability are still important, and recent outages at Amazon S3 and Gmail highlight those concerns. Connectbeam runs as an appliance behind companies’ firewalls.

Connectbeam delivers its model as an integration with existing search engines and other applications. For instance, Connectbeam now has an integration with Microsoft’s SharePoint, the most pervasive collaboration software out there. The Microsoft SharePoint Senior Technical PM even tweeted about it.

I’m a big believer in the ability of enterprises to improve the ways that information is created, disseminated and managed by employees. Those that get this right will be better-positioned in our information-centric economy.

FriendFeed Has Opened My Eyes

I joined BEA Systems to do product marketing for enterprise 2.0. Prior to that, I had done a little tweeting and had a Facebook profile. But not a whole lot of social media. I started blogging in February to eat my own dog food when I was marketing web 2.0 to companies. I needed to immerse myself in the world to really understand it.

Well, blogging has become quite important for me. FriendFeed has become just as important.

FriendFeed opened my eyes to the possibilities of knowledge as the basis of relationships. The ways in which content from a variety of sources is a powerful, addictive basis for learning, conversations and collaboration. How activity streams are compelling reads. I’ve been active on FriendFeed since March, and it shocks me how much I know about web 2.0 and technology in general versus last year. I’ve still got much to learn, and FriendFeed will continue to be a good source for that.

So why can’t companies get better around that too? Having eaten my own dog food on FriendFeed, I’m ready to work with employees and companies to improve the ways in which information is created, tracked and shared.

How Social Media Got Me the Job

You’ve probably seen more than a few posts saying that today’s resume is your Google search results. Your social network sites, content, updates, what others say about you…all of it is searchable.

Like me, Connectbeam CEO Puneet Gupta subscribes to Google Alerts for “enterprise 2.0”. Well one of my blog posts was listed in an alert. It caught Puneet’s attention, so he read the blog a bit more. Liking what he saw, he then investigated my name out on the web. Among the sites he found was one where I was a recommended blogger to follow (thanks Daryl, Franklin, Louis, Mark, Mike, Rob, Steven). Those recommendations were in part made due to the wonderful effects FriendFeed has for bloggers.

It didn’t hurt that I had been involved with enterprise 2.0 at BEA Systems. So after doing some due diligence, he left this comment on my blog:

Hutch:
Would love to connect with you and discuss some ideas.

I reached out to him, did some interviews, and the rest is history.

Looking Ahead

The new job will give me a more structured basis for looking at the ways in which information is managed. I plan to look more deeply at some of the consumer social bookmarking sites.I’m a product manager for Connectbeam, but a lot of my job will involve product marketing too.

I expect working in this area will influence my blogging subjects some. But I’ll blog about other fun stuff along the way as well.

Gotta go – my commute is from San Francisco to Mountain View. Need to battle the 101 traffic.

*****

If you want an easy way to stay on top of Enterprise 2.0, I invite you to join the Enterprise 2.0 Room on FriendFeed. The room takes feeds for Enterprise 2.0-related items on Twitter, Del.icio.us and SlideShare. To see this room, click here: http://friendfeed.com/rooms/enterprise-2-0

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22I%E2%80%99ve+Joined+Connectbeam%2C+and+Social+Media+Got+Me+the+Job%22&public=1