About these ads

The Two-Year Lag from Web 2.0 to Enterprise 2.0

The Enterprise 2.0 sector draws heavy inspiration from innovations in the Web 2.0 world. Indeed, the name itself, Enterprise “2.0” reflects this influence. From a product management perspective, Web 2.0, and its derivations social networking and social media are great proving grounds for features before coding them into your application.

A fruitful area to review is how long it takes for a feature to go from some level of decent adoption in the consumer realm to becoming part of the mainstream Enterprise 2.0 vendor landscape. The list of features that have made the jump – forums, wikis, blogs, tagging, social networking, activity streams, status updates – is impressive. Let’s look at three features that made the leap, with an eye toward how long it took.

Tool Year of Web Adoption Year of E2.0 Adoption
Wikis 2002 2004
Social networking 2006 2008
Microblogging 2007 2009

Here’s the back-up for those dates.

Wikis: Wikis got their start back in 1995. From there they grew, and the application became popular with computer programmers. But it hadn’t caught hold outside that culture. Wikipedia was launched in January 2001, and grew rapidly over its first two years. It wasn’t yet mainstream, but it clearly had caught a wave among early adopters. As recounted on the history of wikis page in Wikipedia, 2004 – 2006 saw an explosion of interest in wikis from companies.

Social networking: Defined as enabling social profiles, and connecting with others. Facebook started in 2004, and grew very popular among colleges. In 2006, it opened up its membership beyond college students, and turned down a $1 billion offer from Yahoo! Clearly, the company was on fire (even then).

In April 2008, Jive released Clearspace 2.0, which was touted as Facebook for the enterprise. Socialtext 3.0 was released in September 2008, and it included Socialtext People, its social networking feature. And I can tell you that at BEA Systems, there was a second quarter 2008 release of a Facebook for the enterprise in the Aqualogic product line.

Microblogging: Twitter. The source of it all. Twitter actually was conceived as an idea back in 2000, and company was started from a 2006 brainstorming session at Odeo. But it really hit big with the early adopter set at 2007’s South by Southwest.

Microblogging broke into the Enterprise 2.0 world when Yammer won best-of-show at the September 2008 TechCrunch 50. But that doesn’t count as mainstreaming into Enterprise 2.0. Yammer proceeded to grow strongly the next few months. And Socialtext introduced Signals in March 2009.

So there’s some documentation backing my 2-year cycle for Web 2.0 innovations to move from hitting the early adopter set to the Enterprise 2.0 sector. Note that this doesn’t apply to every Web 2.0 innovation. No one ever talked about “MySpace for the Enterprise” and there’s really not a Flickr in the Enterprise 2.0 umbrella.

Which raises a question about today’s hottest Web 2.0 trend…

Foursquare for the Enterprise?

Foursquare, and its up-n-coming competitor Gowalla, are all the rage these days. These location-based social networks are good for seeing what friends are doing. Foursquare also integrates features that reward participation (points), add a sense of competition (mayors) and provide recognition (badges).

Mark Fidelman recently wrote about Foursquare and Enterprise 2.0. And using our handy two-year lag calculation, somewhere in early 2012 the first mainstream Enterprise 2.0 will integrate Foursquare features. Actually, two of them.

Location check-ins

Employees will check in their locations from all around the globe. Sales meetings, customer on-site deployments, sourcing trips, conferences, etc. Sure, this info might be in the Outlook Calendar. But even if it is, Outlook Calendar entries aren’t social objects. These check-ins will allow you to know where colleagues are, including those you don’t know well. But wouldn’t it be nice to know if some other employee visited someplace you’re investigating?

These check-ins can be even more tactical. Folks who are part of a meeting in a conference room all check-in. Voila! Meeting attendance, which everyone can see. For an individual employee, these check-ins become a personal history of what you did over the past week.

Mayorships, Badges, Points

Foursquare makes it fun, and for many people, addicting, to check-in. You get points and *bonuses* when you check into the places you go. If you check in to the same place enough times, you get to be mayor of a venue and tweet it about it. You earn badges for accomplishing different things in the Foursquare system.

These features have had the effect of motivating legions of people to participate. It’s fun to see your stats. It’s fun to get a little competitive.  It’s great when you get that notification that you’ve earned a new badge.

Andrew McAfee wrote a series of posts exploring the question of whether knowledge workers should have Enterprise 2.0 ratings. This chart was from one of his posts:

Well, the Foursquare approach certainly takes us down this path, albeit in a fun way. I’d be remiss if I didn’t call out that Spigit already has these tools in place (ahead of its time?).

So what do you think? Personally, I’m looking forward to more Foursquare in the enterprise.

I’m @bhc3 on Twitter.

About these ads

My Ten Favorite Tweets – Week Ending 012210

From the home office in Massachusetts, where I’m saying, “Kennedy who?”

#1: the six types of ideas http://bit.ly/6pKGGZ #innovation

#2: RT @InfoWeekSMB Spigit Introduces ‘Idea Management’ for SMBs http://bit.ly/6CGhWO

#3: RT @johnt Systems that eliminate failure, eliminate innovation by @snowded http://icio.us/xoupma

#4: This is really cool: @tyler_thompson decided to redesign airline boarding passes: http://bit.ly/75OWtU What do you think?

#5: RT @markfidelman My new Post: Hutch Carpenter on the Innovation X Factor http://tinyurl.com/y9hfvrq

#6: RT @stu: New Blog Post: Celebrating the Web at 20 http://bit.ly/6Vtjo5 incl interviews w/ @bhc3 @louisgray #emc #innovation

#7: @pgkiran Good to know Kiran! Got no beef with Conan, he’s getting a raw deal. But I don’t blame it on Leno.

#8: RT @MarkDykeman: I hereby coin the term “nanocause”. It’s a thing that you care about for no more than 15 min. before you get bored.

#9: Seventh Generation (cleaning products) ad on TV just referenced the vaunted “5-second rule” for food on the floor. #lifelessons

#10: There truly are times a parent can look at his lovely little children, and think: “savages”.

My Ten Favorite Tweets – Week Ending 031309

From the home office in Austin, Texas…

#1: @defrag has been saying he thinks the economy is slowly coming around. To that end: http://bit.ly/pP5bd and http://bit.ly/nRkzv

#2: “I think the days of the traditional San Francisco startup approach are numbered.” http://bit.ly/jyw4H

#3: @petefields Companies should follow all who follow them. I’d bet companies’ tweet reading is more keyword & @reply based, not person based.

#4: Maybe it’s just me, but Techmeme has improved a lot recently in terms of the variety of interesting stories. Human editor + user tips = +1

#5: “Facebook is the SharePoint of the Internet” http://bit.ly/4fu73o

#6: This shouldn’t be too controversial…The Case Against Breast-Feeding in April’s Atlantic Magazine http://bit.ly/Xs4ZG

#7: If browsers were women http://bit.ly/kO1su (h/t @mona)

#8: I’ve been blissfully unaware of what Sophie’s Choice is about all these years. My wife told me about it last night. Never gonna watch that.

#9: Actively banishing artists showing up in my Last.fm recommendations: Peter Cetera, Richard Marx, John Parr.

#10: In an email f/ my son’s preschool: One kid: “We’ll take them home in the future”. My son Harrison: “But I’ve never been to the future.”

Social-Filtered Search

Recently, there was a lot of discussion about running searches on Twitter, using authority as a filter. The idea is to reduce Twitter search results to only those with a minimum number of followers. The idea garnered plenty of discussion. From that discussion, I saw some perspectives that I liked:

Frederic Lardinois: I would love to have the option to see results from my own friends (or those who I have communicated with through @replies) bubble up to the top.

Jeremiah Owyang: Organizing Twitter Search by Authority is the wrong attribute. Instead, focus search by your OWN social connections. People you actually know score higher relevancy. http://www.loiclemeur.com/engl…

Robert Scoble: On both services you should see a bias of tweets made by people you’re actually following. Who you are following is a LOT more important than who is following you.

Those ideas make sense to me, because they reflect the way we seek out information. I do think there’s room for search results beyond only your friends. Here’s what I mean:

social-filtered-search

The idea above can best be described as follows:

I’ll take any quality level of search results for my close connections, but want only the most useful content from distant connections.

The logic behind this is that any quality “deficiencies” in content generated by my close connections can be made up for by reaching and having a conversation with them. That’s not something I’d do with more distant connections.

The chart above has two axes: strength of ties and usefulness signals. Let’s run through those.

Strength of Ties

Harvard professor Andrew McAfee blogged about the strength of ties back in 2007. With an eye toward employees inside companies, he segmented our connections as follows:

strong-weak-potential-ties-mcafee

The segmentation works inside companies, and it also applies in the personal world. For example, on FriendFeed, my Favorites List is akin to Strong Ties. The rest of the hundreds of people I follow are my Weak Ties. Friend-of-a-Friend entries I see are my Potential Ties. And of course there are a lot of people I never see. Those would be the “None” Ties.

The hardest part of this segmentation is that people aren’t likely to take the time to create and update their Strong Ties. Rather, Strong Ties should be tracked via implicit signals. Whose content do you click/rate/comment on/bookmark/share/etc.? Extend this out to email – who do you correspond with the most?

For example, I tried out the social search of Delver. It lets you load in your social networks, from places such as Facebook and FriendFeed, and uses content from those connections as your search index. Innovative idea. What happened though is that when I run a search, I get a deluge of content. My social networks are too big to make the service really useful.

Here’s where apps that handle a large percentage of my clicks and interactions will have an advantage. FriendFeed, with an extensive library of content from my connections, has this quality. Inside the enterprise, workers interact with a limited set of applications. The company’s IT department can set up tracking of interactions to identify implicit Strong Ties.

Bottom line: determining Strong Ties via implicit interactions is scalable and useful.

Signals of Usefulness

I’ve already described these in the paragraphs above:

  • Clicks
  • Ratings
  • Comments
  • Bookmarking
  • Sharing

Implicit data + explicit signals are the most powerful indication of usefulness.

Putting These into Place for Social-Filtered Search

When I say that I’d want to receive search results, even without many signals of usefulness, from my Strong Ties, here’s an example.

  1. I’m planning to run a marathon
  2. What marathon training plan should I use?
  3. I run a search for marathon training.
  4. I see a tweet from one of my Strong Ties: “Just started my marathon training this weekend. 4 miles FTW!”
  5. I @reply my Strong Tie, ask what training program he’s using.
  6. I now can leverage someone else’s work on this subject.

Of course, I’d want to see well-rated marathon training programs too, like Pete Pfitzinger’s Advanced Marathoning. I’d want to see the content from my distant/non-existent connections that had the highest signals of usefulness. Not unlike Google’s algorithm.

But the key here is that I’ll make up for any deficiencies in the utility of content for someone I’m close to by contacting them. A search on ‘marathon training‘ in Twitter shows a lot of results. But I’m not going to reach out to most of these folks, because I don’t know them. I only want those with whom I can have a conversation.

As I said, the ability to track both implicit and explicit activity is key to making this work. Facebook, FriendFeed, Twitter and Enterprise 2.0 all seem like good candidates for this type of search.

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22Social-Filtered+Search%22&who=everyone

Why I Like Buzzwords (Enterprise 2.0, Web 2.0, Social Media, etc.)

Via Annie Mole on Flickr

Via Annie Mole on Flickr

UK-based The Register has an article out, They used ‘em, you reeled: the year’s most overused phrases. The article lists “tech terms that were so overused and misapplied during the last 12 months that they began to lose their meaning.” Included in the list?

  • The cloud
  • Web 2.0
  • Enterprise 2.0
  • Software as a service
  • Agile
  • Green

Then I saw this tweet from Lawrence Liu of Telligent:

I hope “social media” & “Web/Enterprise 2.0″ die as way too overloaded buzzwords in 2009. As New Yr reso, I’ll try to avoid using them.

To which Gia Lyons of Jive Software tweeted:

@LLiu I’m with you re the death of “social media” & E/W 2.0 buzzwords. I’m not gonna use ‘em either.

I get the sentiment, getting away from the overselling of benefits and hype associated with these terms. But man, at this rate, we’re not going to have any words left to describe Enterprise 2.0, Web 2.0, social media, or anything.

So What Terms Do We Use?

If we stop using terms like ‘Enterprise 2.0′, what would be the replacement(s)? Here’s what Lawrence thought:

@karitas Use real terms like team, community, Facebook, sharing, commenting, rating, discussing. :-)

Cannot disagree with Lawrence here. Those all are valuable terms. But I wonder how he meant this? Have people been using buzzwords in lieu of those?

  • “We need to get the enterprise 2.0 team together to collaborate”
  • “Let’s put this idea out into our social media community to see what they think”
  • “When employees are web 2.0-ing discussing ideas, make sure the record is accessible everywhere”

What those silly examples show is that there are plenty of points where you shouldn’t use buzzwords. I’m not convinced that people have been abusing the language that badly though.

There are two good reasons that those buzzwords should continue to be part of Lawrence and Gia’s vocabulary in 2009.

Buzzwords Provide Context and Findability

The first reason buzzwords have value is context. When I say ‘Enterprise 2.0′, I’m standing on the shoulders of others who have been working in the field for some time. It’s short hand for:

  • Employees are better off when they can find more content that colleagues create, not less
  • Workers can offer much more value than being just the cog they were hired for
  • People from different locations and units should be able to work together far more easily than they do
  • Companies’ culture needs to be open to empowering employees to drive and critique what’s happening internally
  • Adoption is an ongoing work-in-progress as employees shed old ways of thinking about sharing their contributions

Yup, I get the benefit of those connotations when I say ‘Enterprise 2.0′. You know I’m not talking about CRM or accounting software.

The second reason buzzwords are valuable is they increase findability of content and people. As I’ve written before, I’m tracking the Enterprise 2.0 industry by following specific people (such as Lawrence and Gia) on FriendFeed, plus people who are using terms related to Enterprise 2.0. That’s the whole premise of the Enterprise 2.0 Room on FriendFeed.

If people wholesale stop using buzzwords, the ability to find others with common interests reduces dramatically. When some one writes or tags with ‘Enterprise 2.0′, ‘e2.0′ or ‘social software’, it’s pretty clear what their subject is. But if someone interested in social software inside the enterprise decides to only use terms like ‘Facebook’ or ‘sharing’, they will never be found. To see what I mean, here are Twitter searches for those terms:

Facebook

Sharing

Good luck figuring out who is talking about the enterprise in those results.

When Change Comes, It Will Be Organic, Not Declared

There is a time and place for usage of buzzwords, and it’s possible the language has been abused. But that doesn’t mean you throw the baby out with the bath water. Smart people can discern when to use a buzzword for what they mean, and when to use something more specific (or generic, as the case may be).  I have yet to be troubled by irresponsible use of these terms.

That’s not to say things won’t change. People will use terms like ‘social media’ and ‘Enterprise 2.0′ until better, more descriptive terms emerge. Those new terms will make sense, and will provide the context someone needs when they use them. Right now, our buzzwords fit that bill.

Besides, if we couldn’t simply say ‘Enterprise 2.0′, what would we say?

Software-that-lets-employees-contribute-from anywhere-and-make-it-accessible-to-all-to-improve-a-company’s-ability-to-know-what-it-knows-and-which-requires-a-strong-employees-are-more-than-cogs-culture

I’ll take brevity on this one.

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22Why+I+Like+Buzzwords+(Enterprise+2.0%2C+Web+2.0%2C+Social+Media%2C+etc.)%22&who=everyone

Supply-Demand Curves for Attention

The basic ideas behind the Attention Economy are simple. Such an economy facilitates a marketplace where consumers agree to receives services in exchange for their attention.

Alex Iskold, ReadWriteWeb, The Attention Economy: An Overview

The attention economy. It’s a natural evolution of our ever-growing thirst for information, and the easier means to create it. It’s everywhere, and it’s not going anywhere. The democratization of content production, the endless array of choices for consumption.

In Alex’s post, he listed four attention services, as they relate to e-commerce: alerts, news, search, shopping.  In the world of information, I focus on three use cases for the consumption of information:

  1. Search = you have a specific need now
  2. Serendipity = you happen across useful information
  3. Notifications = you’re tracking specific areas of interest

I’ve previously talked about these three use cases. In a post over on the Connectbeam blog, I wrote a longer post about the supply demand curves for content in the Attention Economy. What are the different ways to increase share of mind for workers’ contributions, in the context of those three consumption use cases.

The chart below is from that post. It charts the content demand curves for search, serendipity and notifications.

micro-economies-of-attention-3-demand-curves-for-content

Following the blue dotted line…

  • For a given quantity of user generated content, people are willing to invest more attention on Search than on Notifications or Serendipity
  • For a given “price” of attention, people will consume more content via Search than for Notifications or Serendipity

Search has always been a primary use case. Google leveraged the power of that attention to dominate online ads.

Serendipity is relatively new entry in the world of consumption. Putting content in front of someone, content that they had not expressed any prior interest in. A lot of the e-commerce recommendation systems are built on this premise, such as Amazon.com’s recommendations. And companies like Aggregate Knowledge put related content in front of readers of media websites.

Notifications are content you have expressed a prior interest in, but don’t have an acute, immediate need for like you do with Search. I use the Enterprise 2.0 Room on FriendFeed for this purpose.

The demand curves above have two important qualities that differentiate them:

  • Where they fall in relation to each other on the X and Y axes
  • Their curves

As you can see with how I’ve drawn them, Search and Notifications are still the best way to command someone’s attention. Search = relevance + need. Notifications = relevance.

Serendipity commands less attention, but it can have the property of not requiring opt-in by a user. Which means you can put a lot of content in front of users, and some percentage of it will be useful. The risk is that a site overdoes it, and dumps too much Serendipitous-type content in front of users. That’s a good way to drive them away because they have to put too much attention on what they’re seeing. Hence the Serendipity curve. If you demand too much attention, you will greatly reduce the amount of content consumed. Aggregate Knowledge typically puts a limited number of recommendations in front of readers.

On the Connectbeam blog post, I connect these subjects to employee adoption of social software. Check it out if that’s an area of interest for you.

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22Supply-Demand+Curves+for+Attention%22&who=everyone

My Ten Favorite Tweets – Week Ending 120508

From the home office in Truth or Consequences, NM…

#1: Love this post by Atlassian’s @barconati Connectbeam Connects | Confluence Customers Beam http://bit.ly/5VhY >> why E2.0 integrati …

#2: Noticing that my tweets that hit 140 characters are having text cut off well before 140. Anyone else?

#3: @twitter A bug. Char. < and > are stored as 4 char. in ur DB, not 1. Means each use cuts max char. of tweet by 3. This tweet’s max=134

#4: One effect of BackType – I am more conscientious than ever about commenting. Comments have the effect of Google Reader shares.

#5: Lump by Presidents of the USA comes on radio. Says 20-something, “Oh that’s the classic rock station.” Lump is classic rock? Ouch!

#6: One thing vacations with little kids ain’t…restful.

#7: RT @timoreilly Derived intelligence from large data sets is a kind of interest or “float” on data. Analogy of Web 2.0 data to capital.

#8: The H-P Social Computing Lab is doing some really interesting research http://bit.ly/k7dI

#9: RT @jbordeaux re: enterprise 2.0 “And like pornography: they’ll pay too much, get over-excited after tiny results, but soon regret it.”

#10: But at least I’ve got a Sam Adams.

Follow

Get every new post delivered to your Inbox.

Join 677 other followers