I had a very interesting talk a little while back with Gregg Petersmeyer and a couple of his colleagues. Petersmeyer is the CEO of Personal Pathways, a startup that aims to increase levels of trust and confidence among people within an enterprise “who need to collaborate successfully, but who don’t really know one another.” (I have no financial interest in or business relationship with PP)

PP believes in the power of technology to increase trust and confidence among weakly-tied colleagues (and perhaps even to convert potential ties into actual ones). The company harnesses this power by creating “internal corporate social networks that accelerate, deepen and extend purposeful relationships around the work that needs to be done. Users develop a unique 360° user profile of depth and substance, celebrate one another’s large and small successes, and create meaningful groups and communities of interest.”

As they explained this to me I was, of course, nodding my head vigorously in agreement. As I’ve written before, I believe that the new crop of digital tools for building, maintaining, and exploiting social networks are both novel and powerful for individuals and enterprises alike.

The element of PP’s offering that I found most thought-provoking was the “360° user profile, ” which is composed in large part of responses to questions that PP has come up with. These questions are designed to reveal what kind of person a respondent is, and what kind of colleague she’d be. If I understand correctly, they’re intended to accelerate the process of getting to know someone who might work half a world away, and to facilitate the process of building a trust relationship with that person. Presumably, the PP questions and user profiles will also be used by managers to select people into teams.

After they described their company I responded to what I’d heard by brutally oversimplifying, then further insulted PP by implying that it was derivative. “So this is Facebook meets eHarmony for the enterprise?” I said (I was evidently channeling a screenwriter pitching a script to a studio executive). Petersmeyer replied, with more grace than I warranted, that this was a fair summary.

We then had a fascinating discussion about whether this was the right approach. We talked not so much about the Facebook part (everyone in the room agreed that some type of digital social weak-tie-maintaining glue is valuable) as about the eHarmony part.

eHarmony advertises that its “patented Compatibility Matching System® narrows the field from millions of candidates to a highly select group of singles that are compatible with you. Unlike other sites where you can post a picture and paragraph and then browse the profiles of other users, eHarmony does the matching for you based on 29 Dimensions^TM of personality that are scientifically-based predictors of long-term relationship success.” These 29 dimensions are determined from an individual’s responses to 258 questions. I have not attempted to complete an eHarmony application myself, but friends who have tell me that it is quite a bit of work.

The quote above indicates eHarmony’s confidence that its algorithms will do a better job matching people than the people themselves could. The company as much as asserts that in the important task of looking for love we don’t know what we’re looking for as well as the brains behind and computers within eHarmony do.

eHarmony’s approach to connecting people is to first collect a large amount of structured data from them, then have the people themselves sit by while computers and algorithms go to work on this data. The company claims a great deal of success with this approach and has become popular, with perhaps as many as 25 million members.

Craigslist, another extremely popular website, takes exactly the opposite approach to facilitating personal connections. Craigslist asks its users to categorize their postings (’jobs,’ ‘housing,’ ‘personals,’ etc.) and to specify a geographic area, but makes no further attempt to specify or standardize the information posted. And as everyone who has spent time on the site knows, the diversity of posts is simply astonishing. If you’re a CL newbie and want to get an idea of this variety, check out the best-of-craigslist (Be forewarned, though, that a great deal of viewer discretion is advised.).

CL’s approach is to let people describe what they have and/or what they’re looking for with no rules, guidelines, or requirements (beyond a few intended to keep things legal). There are few communities more freeform on the Web, and its personals sections is, like eHarmony, highly popular.

Is one of these two approaches better than the other? Leave aside for the moment the fact that eHarmony automates the work of connecting people, and concentrate only on the fact that it requires them to supply a large amount of structured information. And compare this to CL’s almost completely unstructured environment. Which of these two types of digital connective tissue would you rather have throughout your organization?

This is far from an idle or academic question. At present most social networking applications –  Facebook, Twitter, etc. –  are close to CL. They require very little and offer great freedom of self-expression. Underlying their architectures is a conscious or unconscious philosophy that if left to their own devices people will do a good job of expressing themselves, and that their self-portraits will be both accurate and revealing.

The success of these communities strongly indicates that this philosophy is not bankrupt. In other words, there’s clearly some validity to the idea that unguided self-description leads to connection. But would guided self-description work better?

Personal Pathways is betting that it will. A large part of their value proposition (as I understand it) is the survey they ask people to complete when they join their organization’s PP-built social network. This survey is intended to provide valuable information to their current and prospective colleagues, in particular the kind of information that people might not have thought to provide if left to their own devices.

Given what I’ve learned about the strength of weak ties and the value of converting potential ties into actual ones, if PP’s approach is better than CL’s for interconnecting people than it’s the one enterprises should adopt. But is it the better approach?

My intuition tells me that I’d learn a lot more about someone from reading their Facebook profile, 50(?) of their tweets, or even a couple paragraphs of freeform self-description than I would from reviewing their answers to a standardized questionnaire, no matter how carefully constructed it was. I find that responses to standardized questions look, well, standardized; they tend to flatten out variety rather than highlight it. Because of this, when I’m getting to know someone I want to hear what they want to say, not what any third party (no matter how smart or well-intentioned) wants us to talk about.

Do you share this preference, or do you find more structure beneficial? Some sophisticated organizations are in the latter camp. McKinsey, for example, has a highly standardized interviewing process for new hires. Hiring is, of course, a crucially important type of interconnection; McKinsey believes that it’s far too important to be handled in a freeform manner, and so has adopted a PP-like approach.

For other kinds of personal connection in professional settings, do you think an at least somewhat standardized approach is best, or do you have more faith in the freeform? Are you closer to the eHarmony or craigslist philosophy of interconnection? Leave a comment, please, and let us know. And if you have any data on this topic or know of any good research in the area, let us know that as well.

Journalist and apparent baseball fanatic Dan Rosenheck had an article in Sunday’s New York Times sports page about the use of steroids within the sport. As he wrote,

“Given the advances in baseball statistics, one might hope it would be possible to deploy modern analytical tools to adjust today’s chemically enhanced stats and put them on a level playing field with those of yesteryear. But while number crunchers can tell you how to reorganize a batting lineup, they find it much tougher to interpret the effects of drugs.

The biggest challenge in attempting to measure the consequences of steroids is that it is impossible to know who used what, and when. Even if the supposedly anonymous results of all 104 players who tested positive in 2003 are revealed, there will still be more questions than answers. Steroids come in more combinations than Tony La Russa’s lineup cards, and they can further be paired with an array of workout programs and nutritional regimens.”

Furthermore, because both pitchers and hitters were evidently juicing, we shouldn’t expect either offensive or defensive performance to skyrocket, even if the drugs are powerful. Instead, if all players were taking the drugs we’d anticipate that the sport would reach a new steroid-based equilibrium that might not actually look all that different than the old one.

But not all players were taking the drugs. Even the most hyperbolic accounts of steroid use in baseball don’t allege that all, or even most, major league players were devotees of the cream, the clear, human growth hormone, etc..

Rosenheck realized that this lack of 100% adoption opened the door to a clever test of steriods’ impact, a test that didn’t depend on knowing or even guessing who the users were. He reasoned that if steroids provided a significant performance boost to a player, and if not all players took them, then we should expect to see the performance gaps between juicers and clean players get bigger — the juicers as a group would (unfortunately) pull away from those that were not taking drugs. More specifically, we’d expect to see increases in the standard deviation (a measure of spread) of all hitters’ batting averages, all pitchers’ walks+hits per inning pitched (WHIP), and other such statistics. And we’d expect to see these increases only during baseball’s alleged steriod era, which was commonly assumed to start in 1993 and ended with the start of a testing regimen in 2005.

Rosenheck has conducted these analyses, and found that

“performances by both hitters and pitchers were more spread out [between 1993 and 2004] than in any 12-year period since World War II. Although some of the difference was caused by adding new teams, expansion was much more rapid in the 1960s than the 1990s, and standard deviations were still lower back then.

None of this means that steroids are necessarily the cause of the separation. But the game’s fans are probably in no mood to write off the association as mere coincidence.”

It’s not automatically the case, of course, that a player with a high batting average or low WHIP between 1993 and 2004 was on the juice. Rosenheck’s analyses don’t prove who was taking drugs, and as he says they also don’t prove that steroids were responsible for the increased spread in performance. But I find it very interesting that what we see in the data is exactly what we’d expect to see if steroids were powerful, and were being used by some players. I’m pretty confident that this is not a coincidence.

My colleagues and I have documented that beginning in the mid 1990s corporate performance also started to diverge –  the gaps between high-performing and low-performing firms in an industry started to widen (and have stayed wide ever since). We also found that the gaps were wider in industries that spent more on IT. This is exactly what we’d expect to find it IT were powerful, and if not all firms were equally good at adopting or exploiting it.

In a blog post a little while back I made an explicit analogy between baseball and business competition, building on the work of Stephen Jay Gould. Gould documented that standard deviations of baseball players’ performance had been declining steadily throughout the game’s history, and advanced a powerful hypothesis about why:

“Complex systems improve when the best performers play by the same rules over extended periods of time.  As systems improve, they equilibrate and variation decreases.”

If Rosenheck’s analyses hold up, they strongly suggest that steroids in baseball were such a big deal that they amounted to a rule change in the game itself, a change significant enough to disturb a longstanding equilibrium. This change was a particularly unfair one since it only affected the players who took the drugs. Those who stayed clean were playing by the old rules, and evidently found themselves outperformed as a group.

One of the themes of my research and this blog is that advent of modern corporate technologies like enterprise systems, analytics, and Enterprise 2.0 tools is a big enough deal that it amounts to a rules change in the game of business. In sharp contrast to steroids in baseball, though, IT is legal, acceptable, and kosher in every way in business and competition. A-Rod is probably in for some serious abuse from the fans at Fenway and many other parks this year, but no one’s going to cry foul and hurl abuse at your company if you deploy  technology.

In addition to being a performance enhancer, IT is similar to steriods in another way: effective use can be very hard to detect from the outside. Back acne and swelling craniums aside, it’s usually not easy to tell which athletes are taking drugs, exactly what types they’re on, and how much good it’s doing them. It’s also not always easy to determine what kinds of technology a company has, and how exactly they’re contributing to its overall value proposition.

But I have great confidence that companies in many sectors are using performance-enhancing tech effectively, thereby widening the gap between the best and the rest in the game they’re playing. My question is: why would any competitor turn their back on this perfectly legal and acceptable performance booster?

Late in 2008 I started asking a question every day on Twitter. I designate it with the hashtag #andyasks and suggest that all those responding do the same. In a November 2008 blog post I talked about what kinds of questions I was planning to ask:

“I have no clear idea what I’ll ask about over time. I’ll try to make andyasks questions varied, and of broad interest. I know that they’ll reflect my interests, which include good writing of all kinds, movies, modern American culture (OK, pop culture), the arts of living well, baseball, technology, and whatever catches my eye in the paper and online.

I imagine that most questions will be lighthearted; there’s more than enough somber material floating around the ether these days. And there will rarely if ever be right vs. wrong answers. This is not intended to be a trivia contest (in the age of Google, how much sport would there be in an online trivia contest?).

I hope you’ll find andyasks to be fun and engaging, and I hope you’ll frequently take the few seconds required to fire off an answer.”

The past couple months of #andyasks have been great fun for me, and judging from the volume of responses and steady participation of some folk in the twitterverse it’s also been of interest to others.

If you’d like to see the #andyasks traffic, do a Twitter search like this one. I’m working to have each day’s #andyasks questions, responses, and follow-on tweets automatically collected and displayed somehow here; watch this space for updates on this project.

In the meantime, I’d like to ask for your help in coming up with good questions. A few people have asked if there’s a way to suggest new topics and questions for #andyasks. Well, now there is. Leave your question as a comment to this page, and I’ll harvest the best of them. If I use yours I’ll credit you by including your Twitter username when I ask the question (if you’d like to be credited a different way or to remain anonymous, please let me know).

Thanks!

A little while back I critiqued some claims made by Oliver Young about the impact of 2.0 technologies. I saw these claims as too broad and sweeping, and tried to articulate why.

Instead of getting defensive or hostile Oliver responded with a thoughtful comment, which read in part:

“… I do think this is a more fundamental shift that you are giving it credit for. [The] big reason [is] scale. Outsourcing, joint ventures, industry consortia, partnerships with academia, network organizations, etc. all bring outside value into the enterprise, but all require major infrastructure and expenditure to manage. The average enterprise simply cannot execute these initiatives in any sort of repeatable, scalable manner. Today it is almost all bespoke.”

Young’s point, if I read him right, is that modern IT, in particular 2.0 technologies, have drastically reduced the investment required to connect with external constituencies and work with them to create value.

I find this a compelling argument. It’s closely related to the argument that IT in general reduces barriers to entry, making it feasible for smaller players to do things that were previously possible only for the big boys. When the computer in your briefcase is as powerful as the supercomputers of the not-too-distant past, it’s not too hard to believe that technology is the friend of the little guy.

(A couple weeks ago I taught my MBA students the great case written by my friend Alan MacCormack and Marco Iansiti about Team New Zealand’s upset victory in the 1995 America’s Cup competition. For TNZ, necessity was the mother of invention; they made smart use of relatively cheap simulation hardware and software in part because they simply couldn’t afford the state-of-the-art stuff.  After all, the case points out that simulations often required file sizes of between 8 and 16 gigabytes –  who could afford enough storage and processing power to work with such massive files!  In case anyone had missed the point about how far we’ve come since the time of the case I brandished my 16 gig iPhone in class.)

So cheap and powerful information technology of all kinds, 2.0 techs most certainly included, reduces the advantages of being big and puts smaller players in a more advantageous position than was previously the case. Right? Well, there’s evidence that the answer is yes.  And no.

As I wrote here earlier, it does appear that in the US economy in recent years IT has been lowering barriers to entry, and so benefiting smaller players. This is a little bizarre, since economic theory predicts that capital investment should act to raise barriers to entry, not lower them. Adam Saunders, a doctoral student at MIT, has found, though, that as an industry acquires more IT it also sees more new entrants rather than fewer ones.

Saunders also found, though, that these new arrivals tend not to do very well over time against incumbents in IT-intensive industries. In such industries he found that concentration –  the degree to which the industry was dominated by a few large players instead of being carved up among many small ones — rose more quickly than was the case in industries without as much IT.

Erik Brynjolfsson and I found exactly the same thing in our recent research on IT’s impact, which used different methodologies and data sources than did Saunders. We also documented an increase in concentration in the US since the mid 1990s, with the biggest increases occuring in the most IT-intensive industries.

A researcher with no focus on IT at all was the first to notice this strange and unexpected pattern in industry concentration. Prior to the mid 1990s c0ncentration had generally been decreasing in the US; in a 2002 paper NYU’s Lawrence White pointed out that the trend had recently reversed. He spent most of the paper carefuly documenting what was going on, and only at the end speculated about why. I love to quote one of his conjectures:

“Improved technologies of managing and monitoring may have helped overcome the inherent difficulties of managing larger organizations.”

As I’ve written in many places, and as Erik and I wrote in Harvard Business Review last year, the technologies of “Enterprise 1.0″ — ERP, CRM, SCM, procurement, and all the other applications that standardize data and workflows –  are exactly such technologies, and they became widely available starting in the mid 1990s. Believers in IT’s power, then, would not be at all surprised if the deployment of these novel tools were accompanied by increased concentration. They help overcome the dysfunctions associated with getting big, and so allow big firms to take more full advantage of their strengths.

So technology helps both small firms and big ones. Since the mid 1990s IT appears on balance to be helping big ones more. But what will happen going forward? Some believe that as we move deeper into the 2.0 era technology’s benefits to the small will outweigh the ones it offers to the big.

I’m not so sure. I can easily imagine that at least big companies will be able to combine the advantages and benefits of 1.0 and 2.0 technologies, and so get the best of both IT-enabled worlds. If this is the case, they will be less likely to be usurped from below.

At the end of the day, this is an empirical question –  one that can and will be settled by data. We’ll continue watching the competitive dynamics of industries to see if and how they change, and we’ll continue to investigate IT’s role in any changes.

What do you think we’ll find?  Going forward, do you think technology will benefit small or large companies more?  Leave a comment, please, and let us know what you think.

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UPDATE: Young left a comment to this post saying that I’ve misunderstood his views.  He says (in part):

“I do not in any way believe that 2.0 technology will primarily benefit the small. In fact my research and advice to clients consistently asserts that the benefits of 2.0 technology have disproportionately accrued to the very large. From all the research (quantitative and qualitative) I have conducted thus far blogs, social networks, wikis, and the rest all improve the ability to manage and orient large, globally distributed organizations far better than they improve the operations of smaller organizations.”

I’m sorry for the confusion.  In an attempt to alleviate it, I’ve modified this post. It originally said “Young believes that as we move deeper into the 2.0 era technology’s benefits to the small will outweigh the ones it offers to the big.” It now reads “Some believe that as we move deeper into the 2.0 era technology’s benefits to the small will outweigh the ones it offers to the big.”

For more of Young’s thinking on the topic, please read his comment below and his blog