Infovark

One of the recurring themes at E2.0 Last week was the notion of Generational Adoption. It’s the idea that Baby Boomers, Gen X and Gen Y all had an innate relationship with various ways of working, and that these different work habits are a major factor in the adoption of new technology. Jay Hariani at the e2.oh blog has a nice wrap up of the generational adoption meme. Since then, Ross Mayfield, Jeff Nolan, and Larry Dignan have all chimed in, with various cases for and against.

I was lucky enough to share a drink last week with with Rob Salkowitz, Author of Generation Blend: Managing Across the Technology Age Gap, who was presenting at the E2.0 conference. I haven’t read Rob’s book yet, but In the wake of our conversation, I am definitely going to check it out. (Venkat’s Review over on RibbonFarm is also a good read).

The Millenials Are Coming is the new Y2K Bug

I have big problems with using the generational argument to drive adoption of Enterprise 2.0. It feels like another vendor-inspired bogeyman designed to convince companies to buy heaps of software they don’t need. (Install our compliance software or Sarbanes-Oxley will get you!)

The notion that the millennials are going to “demand” some kind of “Facebook” to do their work is just plain rubbish. Think about when you joined the workforce. What exactly did you demand?

When I first left school for the workforce, I wasn’t in a position to demand anything. It took me five years of working within the system before I realized which parts were broken. And it was only because I’d put in the time working within the system that I was trusted to actually influence things a bit.

Generational change happens gradually. There’s not going to be some giant “MySpace Revolution” where “The Kids” take over with their externally hosted collaborative tools. Instead, these people will join the workplace as wide-eyed and impressionable new starters, and they’ll do their best to work within the framework that they are given with the tools that are allocated to them. Then, slowly, their own ideas will become part of the way people work, including their favorite tools and technologies.

Sure, the generational issue is interesting from an anthropological perspective. It’s indicative of a lot of things, most notably progress in society. But as a call to arms for business to rush out and spend cash on some new-fangled social media tool for your enterprise, it leaves a lot to be desired.

(But hey, what would I know. I’m just a disgruntled Gen X’er who has no respect for authority, right?)

I sat in on the enterprise architecture session on the third day of the Enterprise 2.0 conference. We spent much of our time in that session attempting to come up with shared definitions for core E2.0 concepts. Then we attempted to find where those concepts fit within a traditional enterprise architecture stack.

Here’s my definition of social software: Social software is software that incorporates human behavior in its system functions. This contrasts with a traditional software engineering approach, which considers system users to be external forces that act upon software. Including human social factors in our software designs is a real challenge. You have to have a team familiar not only with writing code, but psychology, group behavior, organizational theory, ergonomics, aesthetics, and a wide array of other “soft” sciences.

But it’s not something new. Even in the earliest multi-user systems and groupware, software engineers have had to deal with the messy human element. Many of the business rules baked into enterprise applications have as much to do with corporate culture as with policies and procedures.

Er…Where does the Social Go?

So naturally the session attendees had a hard time trying to place the collaborative social elements into an architecture diagram. Corporate culture permeates all aspects of enterprise systems. You can’t point to any one place on the chart and say, “the social stuff goes here.”

(Incidentally, this is also why issues of security and identity management are so difficult. They are social constructs that cut across system boundaries. Like Enterprise 2.0 communication and collaboration technologies, they are both everywhere and nowhere.)

Stowe Boyd listed 10 suggestions for next year’s conference. I seconded his call for more participation from the social sciences. We’ll need help from designers, economists, psychologists, and practitioners from many other disciplines if social software is going to live up to its name.

Puneet Gupta over at ConnectBeam has an interesting post about the Enterprise Knowledge market. He references an intriguing study from McKinsey:

…An individual’s knowledge is self-contained, always available. But in companies—including small ones—it can be hard to exploit the valuable knowledge in the heads of even a few hundred employees, particularly if they are scattered in different locations…

Knowledge Management as a technology discipline is one that I’ve never really been comfortable with. And it’s really only been since I started working on Infovark that I realized why — because using your computer for knowledge is like trying to get your pocket calculator to write you a love song.

Computer’s can’t actually know anything.

To your computer, that brilliantly composed document you just wrote is a bunch of bits on a disk. They are no different to the bits that make up the pictures of your cat or your operating system.

The real knowledge in your enterprise is in your colleagues’ brains. There may be a great deal of information lying around the place too, but that isn’t knowledge.

Let’s look at Twitter. Somewhere, Twitter is a collection of servers siting in a dark server room. Those computers are managing lots of bits on lots of disks. The only thing that Twitter really “knows” is how to connect blobs of data that represent people to the blobs of data that represent tweets.

So Twitter is certainly not a knowledge management system — there’s no managing of anything going on. And yet Twitter is an immensely powerful knowledge catalyst. Huge volumes of information are exchanged every minute. I learn something nearly every day by using Twitter, not because Twitter itself has much to say, but because my twitterfriends are so interesting.

Knowledge, in the Oxford English sense of “expertise gained through experience or study”, can’t be effectively stored, retained, or disposed of. It can’t be centralized or codified easily. Most attempts at knowledge management to date amount to little more than information collection and storage.

This “build a giant library of things we know” approach is a lousy way to transmit knowledge from one person to another. And distributing knowledge is the only sure way of making sure that your organization will retain it. The reason that this “social revolution” is sweeping the enterprise is that by connecting people with better communication and collaboration tools, we facilitate the exchange of information and increase the opportunity to learn.

Most people learn more things from each other than from reading a procedure manual or browsing the corporate library. They learn through on-the-job training and through discussion with their colleagues.

Let’s leave the technology to manage the bits — knowledge is for humans.

Software vendors, ourselves included, love to talk about productivity. On that note…

Productivity can be roughly defined as: Output per unit of input: a measure of efficiency.

Perhaps the only reason to buy any piece of business software is to increase this ratio. “You can do more with what you already have!”. “Think smarter, not harder!”. These are the silver bullets that enterprise software has been touting since its inception. But as the world shifts more and more towards knowledge-based work — work that often involves abstract concepts and ‘ideation’, how can we effectively measure it?

As Jon Husband pointed out on the FASTForward blog, productivity as we know it had its genesis with the Scientific Management of F.W. Taylor at the turn of the 20th century. Right at the heart of the industrial revolution, the ratio of inputs to outputs was a very measurable thing. An automobile factory had discrete, tangible output: a car. The number of cars produced per employee was a measure of the factory’s productivity.

Modern knowledge workers, on the other hand, don’t have such clear and measurable outputs. I was speaking to a friend who works for a consulting firm here in DC, and she was saying that her deliverables were status reports. Quarterly status reports, written by her, based on the services provided in the quarter. Now obviously, Paula isn’t more efficient if she produces twice as many status reports. The traditional manufacturing approach to management doesn’t work here.

Instead, Paula’s employer gauges her efficiency by evaluating the content of those status reports and by surveying her customers to find out how well she is doing. These measures are extremely subjective, and as a result are prone to errors, bias, or manipulation. (Not that any of these things actually happen, of course. We’re speaking hypothetically.)

Enterprise 2.0 claims to improve efficiency by increasing social productivity. The theory is that by making more information available to more people, and allowing them to connect with each other easily, we can collectively get more done. But does this claim hold true? I’m seeing more and more posts from good folks who can’t deal with the overload of this new social graph. The time spent keeping track of all the communications from all of your contacts might actually make you less productive.

There’s no doubt that a more aware and better connected knowledge worker has the potential to be a more productive one. But the social dimension is only one part of the Enterprise 2.0 equation. In a business context, making connections and managing relationships is a means, not an end.

This is the Big Difference between Web 2.0 and Enterprise 2.0. Enterprise 2.0 needs to deliver measurable value - not just get a bunch of people together to click on advertisements.