Six ways to make Web 2.0 work: Hoppe vs McKinsey

Nat Welch brought to my attention "Six ways to make Web 2.0 work" in the McKinsey Quarterly of Feb 2009.

Here are the six ways (quoted verbatim):

1. The transformation to a bottom-up culture needs help from the top
2. The best uses come from users -- but they need help to scale
3. What's in the workflow is what gets used
4. Appeal to the particpants' egos and needs -- not just their wallets
5. The right solution comes from the right participants
6. Balance the top-down and self-management of risk

Maybe it's because I am jealous of the clout wielded by McKinsey, but I do find the above list awfully repetitive. Someone please help me understand the important distinctions between numbers 1, 2, 5, and 6. I'll give the benefit of the doubt to 3 & 4 for being not repeats of 1, 2, 5, 6.

In preparation for an upcoming Web 2.0 panel discussion hosted by the Boston Club, I made my own list--with inspiration & edits from Nat W.

Bruce's Technology Tips

Focus on your business goals and let those drive your technology strategy. For example, consider the following goals:

• Sales
• Marketing
• Recruiting
• Talent management
• Business development
• Innovation of core products & services

Each one of those goals implies a different technology strategy, so it's important to know which goals matter as a basis for evaluating which technologies are helpful.

Web 2.0 Strategy Map

Technology for business is largely about storing, finding, synthesizing, and communicating information. Think about how these different tasks relate to your specific business goals. The table below summarizes how some Web 2.0 technologies relate to finding and synthesizing information:

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Ethics, Social Networks, and Web 2.0

Earlier this week the Human Resource Planning Society hosted a convention on Social Networks and Web 2.0. Nat Welch (CFAR) and I co-led a session on "Organizational Barriers and Web 2.0: Don't just sit there; find something." Afterward we were part of a panel discussion on ethics, social networks, and Web 2.0.

Somewhere there is a joke to be written about the time when a lawyer, a computational sociologist, and a human resource director all answer questions from St. Peter about ethics. Playing the straight man in the joke, my conversation with St. Peter will be a discussion about informed consent. Do people in my life know what they are getting into, and can they exercise choice based on that knowledge?

In many ways, the "informed" part is far slipperier than the "consensual" part of this combination (e.g., dating). And so it is with social network surveys. Years ago I read Borgatti and Molina's framework for ethics and SNA, and their paper has been a trusted compass of mine ever since. Mostly, it reminds me to respect the privacy of my clients and their employees (i.e., to offer them informed consent). Based my experiences since then, I have made the following chart that summarizes how privacy and informed consent are so problematic in a network context:

Lack of Privacy in Network Surveys
	Traditional survey	Network survey
Questions: 1st-person vs. 3rd-person	Each individual reports information about himself.	Each individual reports information about others by name.
Results: averages vs. specifics	Responses are aggregated so that individual respondents and non-respondents cannot be distinguished.	The presentation of results reveals specific responses attributed to specific individuals.
Visibility: informed consent vs. leap of faith	Survey results allow each individual to compare himself silently with the group average. Each individual can then decide what to share about himself with whom.	Survey results expose how each individual is seen by others. Each individual has no ability to preview what others have said about him before it is published.

For me the insight of the above chart is the separation of all three rows. Each of the them can be considered as an independent risk factor with its own unique set of mitigation strategies.

All the LinkedIns and Facebooks of the world are tackling these three issues head-on (and surely more that I have not thought of).

As for social network surveys, I am not aware of one that allows truly informed consent: the ability to preview what others say about you before consenting to publication of that information. Perhaps my readers can enlighten me.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Lincoln and Darwin on Networks and Web 2.0

"Online social tools are great weapons for world peace and unity."

--Overheard at a discussion about LinkedIn, Blogs, and Twitter.

How appropriate that peace and unity cross my desk as we approach the 200th birthdays of Abraham Lincoln and Charles Darwin. Their historically coincidental births (12 Feb '09) and monumental legacies were brought to my attention by the latest cover of Smithsonian magazine, an issue I highly recommend.

Each of these great men speaks to the ages in a way that changes from era to era and from person to person. For me now, Lincoln shrewdly speaks of our sacred devotion to Liberty and equality as he leads the bloodiest war in American history:

"Four score and seven years ago our fathers brought forth on this continent, a new nation, conceived in Liberty, and dedicated to the proposition that all men are created equal. Now we are engaged in a great civil war, testing whether that nation, or any nation so conceived and so dedicated, can long endure." (Read on.)

Meanwhile, in one of the greatest discoveries of science, Darwin writes about the consequences of the simple truth that no one is created equal:

"As many more individuals of each species are born than can possibly survive; and as, consequently, there is a frequently recurrent struggle for existence, it follows that any being, if it vary however slightly in any manner profitable to itself, under the complex and sometimes varying conditions of life, will have a better chance of surviving, and thus be naturally selected. From the strong principle of inheritance, any selected variety will tend to propagate its new and modified form." (Read on.)

Darwin writes reluctantly, forced by outside events into a public announcement of his work, which he kept secret for many years in part to avoid the backlash he knew it would generate.

That backlash remains strong (at least in America), resulting in notions like intelligent design. Personally, I find intelligent design to be an absurd bastardization that dishonors both science and religion. And yet paradoxically I am continually tempted to take on the role of intelligent designer--pronouncing truths from the digital scriptures. I guess that's easier than emulating Lincoln or Darwin.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

In praise of editing

Thank you to everyone who commented on the Working Wikily thread. Comments on this blog are rare (which is probably to be expected) and 99% of them are complaints about kitchen appliances (which is agonizingly hilarious), and so it is a wonderful surprise to receive comments about a topic of ongoing interest to me.

A blizzard of holiday celebrations have passed since then, so to recap: In my Working Wikily series of posts, I spoke to the healthy priorities of those who do not write and publish on wikis and merely use information shared by others. This seemed to provoke violent agreement.

During the holiday season, I thought a great deal about those who do write and publish. The contemplation was entirely self-serving: Claire Reinelt and I spent those months slavishly editing our paper, "SNA and Evaluation of Leadership Networks."

We are optimistic that the result will be accepted for publication in Leadership Quarterly (LQ), and hopeful that LQ will allow us to share the manuscript before its estimated publishing date in 2010. You'll see it here first, if/when LQ does allow us to share it.

Most germane to this post, Claire and I are incredibly grateful to the anonymous reviewers of LQ. Their extremely pointed criticisms and their constructive suggestions for improvements enabled Claire and me to improve our originally submitted draft into something exponentially better. The extra time also gave Claire a chance to convince me to read Skye Bender-deMoll's overview of SNA. Again, I am grateful.

In my networked world, I very rarely encounter editorial demands as stringent as those imposed by an old-school academic peer-reviewed printed-on-paper journal. What an invaluable experience this has been.

More often in a networked world, editorial demands are sub-consciously self-imposed. Every day, it gets easier to avoid those with a different point of view and simply google our way to information that confirms what we already believed. That, at least, is what is suggested by this recent press release from the NSF, which I originally commented about here. Of course, the NSF only suggests that this phenomenon applies to the behavior scientists. Perhaps we non-scientists are more dedicated to the tireless pursuit of truth.

Certainly I credit Skye Bender-deMoll for scientific pursuit of truth. In this May 2008 paper, Skye presents the network Tree of Knowledge; then presents the Babel-izing confounding of terminology and lack of synthesis that characterize the field; and then suggests some editorial advice that is worth taking. For example:

"Although many people are advocating that network techniques will help a great deal with evaluation tasks, there have not been any large scale systematic studies comparing the various pilot projects. Most projects have been fairly small, both in sizes of networks and numbers of participants.

"The majority of projects appear to be doing more diagnosis than assessment. This may be partially because in most cases there is no “known standard” for comparing assessments. Also, researchers tend to be cautious because the data collection is not rigorous or comprehensive enough to be safely used for evaluation at this time.

"Although a few of the academic studies show high methodological maturity, much of the work still seems quite exploratory. In several papers the insight appears to come more from the in-depth interviews and data collection process, with the network analysis component serving as a parallel approach."

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2009 by Connective Associates LLC except where otherwise noted.

Wikis, surveys, and webwhompers

Continuing on the thread of when have I seen wikis work the best... In my last post I answered that I have seen wikis work quite well when they are tightly controlled. I described the LeaderNetwork wiki, which only allows editing by Claire Reinelt and me.

Another good way of controlling a wiki is not by limiting the number of editors (as in the previous example) but by limiting the contributions asked of each editor.

Used in this way, a wiki is quite similar to an online survey. The wiki begins with a clear list of questions and a well-defined framework to hold each response contributed by each wiki editor --- just like SurveyMonkey. However, a wiki-survey has two important differences:

1. Transparent sharing of all wiki-survey responses is a given. There is no waiting for the survey administrator to publish anything, no option for the survey administrator to hold anything back.
   
2. The questions themselves can be added to and/or edited on the fly by wiki-survey respondents. This frees the survey administrator from having to ask just the right questions; if someone does not see the question they wanted to answer, they can add that question in a place where everyone can respond to it.

One of my favorite wiki-surveys is this one, which I have used to run a contest that recognizes the most popular student project of the semester. It is a simple and effective wiki-survey that leverages option #1 heavily and ignores option #2. I have previously posted two case studies about its use on these pages: "Pros and cons of male enhancement" and "Delete all your links, except to me." I have modified it for use in many client engagements as well, fully leveraging both options #1 and #2.

This fall I significantly upgraded my pseudo-survey technology by abandoning the wiki platform altogether. You can see my post-wiki pseudo-survey at http://webwhompers.net, where the blood from my students' recently fought competition is still fresh.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Wiki Whomping

"When have I seen wikis work the best?" Thanks to Noah Flower for posting his thoughtful response to my last post (about working wikily), and closing with that question.

By way of answering, I'd like to quote from the pre-eminent prophet of working wikily, Clay Shirky. In his award-winning essay "A group is its own worst enemy," Shirky states, "Prior to the Internet, the last technology that had any real effect on the way people sat down and talked together was the table."

You can click here to read my original argument that Shirky is crazy if he really believes that. Today, instead of arguing against Shirky, I'd like to use his quote to put Noah's question in clearer context:

"When have you seen tables work the best?"

If you find that question confusing, good. Tables are such a fantastic technology for collaboration, and so flexible in the ways we can use them, that asking for "best example of using a table" is more of a Rorschach test than a question. More specifically, it's a great question for a furniture salesman to ask, as the person answering will suddenly feel an urge to find some connection between tables and whatever "works the best."

Answering Noah more earnestly (sort of), I have seen wikis work very well when they are tightly controlled. For example, Claire Reinelt and I use a wiki to publish our favorite reading list about SNA and leadership networks for social change. Our reading list is a joint effort that neither of us could have assembled alone. The most important feature of the site, however, is that no one can edit the wiki but me and Claire.

I'll close today's post with this passage from Wikipedia. It's from an article on participation inequality, but it also works well as a manifesto for Wikipedia's own governance, which is much more tightly controlled than it used to be:

"A major reason why user-contributed content rarely turns into a true community is that ... a few users contribute the overwhelming majority of the content, while most users either post very rarely or not at all. Unfortunately, those people who have nothing better to do than post on the Internet all day long are rarely the ones who have the most insights. In other words, it is inherent in the nature of the Internet that any unedited stream of user-contributed content will be dominated by uninteresting material."

Next time we'll answer the question, "When have I seen social bookmarking work the best?"

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Working Wikily

Last month the Monitor Institute launched a blog http://workingwikily.net about how the social sector is adopting the new tools, strategies, and practices of networking.

They explain here that "Working Wikily" was coined "to describe the new ways that people are applying network theory and networked technology to do the work they’ve always done in a more collaborative form and also to begin working in new ways altogether."

As my contribution to "Working Wikily," I'd like to offer a reality check on what happens when people use a wiki. Before I continue, however, let me make clear that (1) collaboration is great, (2) wikis are great, and (3) the reality check I am about to deliver is aimed at people who associate "collaboration" with "wiki" and thereby set themselves up for disappointment when they learn this the hard way:

Jakob Nielsen summarizes Web collaboration in general with the 90-9-1 rule as pictured below.
90% do nothing, 9% do a little, and 1% do practically everything.

Blogs are even more skewed than average Web sites, with 95% doing nothing, 4.9% doing a little, and 0.1% doing practically everything.

Wikis are the most skewed of all.

Most community facilitators I know who have set up wikis lament that they can't get anyone else to edit it without resorting to bribery. That is 100% doing nothing while one outsider does everything.

With a hugely successful wiki like Wikipedia, the ratio is slightly better, 99.8% percent do nothing, 0.197% do very little, and 0.003% do practically everything.

The above dose of reality is called "participation inequality" by Nielsen. Let me reiterate that I do not see this inequality as a problem, even though Nielsen presents it that way (as would, I suspect, many who set out to "work wikily" and end up proving Nielsen's point).

Thank you to Laurie Damianos for alerting me to these statistics during her presentation on MITRE's use of social bookmarking on their corporate intranet. Her experience at MITRE was consistent with the general trends claimed by Nielsen. Unlike many others in her position, though, she did not get discouraged by low participation, nor did she try to change it. Instead, she did a great job explaining to the powers-that-be that MITRE's social bookmarking system was working great, even with most people contributing nothing.

So let's raise a toast to the 99.8% who have perfected the most popular way of "working wikily" -- those who do nothing and, when they feel like it, coast off the hard work of the 0.003% who give it all away.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.