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ThoughtFarmer published a must-read article on the New Laws of Intranet ROI. It discusses how the mathematical models used to describe social network effects have evolved over time.
For the less mathematically inclined, you can skip ahead to their summary of the changes. The new thinking on how to evaluate the impact of a social network (emphasis by ThoughtFarmer) is to:
This is excellent advice. And it might help to explain why we’ve found that the most successful Enterprise 2.0 roll-outs tend to be bottom-up, emergent efforts.
Social Media is a great platform for the extroverts among us, but not all of us are extroverts. Where do the rest of us fit in?
ConnectBeam pointed me at a study conducted by HP of Twitter connections. It suggests that people interact with very few of the contacts in their social network regularly. ConnectBeam suggests that ”Social Network Analytics” — figuring out which contacts are more important than others — will become increasingly valuable as we explore social networking within the enterprise.
These findings are interesting from a social perspective (Hey, it turns out that most people with 1000 friends on Facebook don’t have more ‘active’ connections than you do!) but when it comes to leveraging your network inside the corporate firewall, they are much more important.
Dean and I have always known that some people within the organization are more important than others — as senior technical consultants in our last company, TOWER Software (which, in a nice twist, ended up being bought by HP), we were constantly in demand. We provided our expertise to sales, services, support, pre-sales… In short, nearly everyone in the company depended on us for at least some part of their job. We would get calls from people we knew on behalf of people we didn’t, and be brought in on everything from sales calls to marketing events. Our manager spent a lot of his time ‘running interference’, when we actually had work to get done. The nature of enterprises tends to create these information hubs and dependencies between each other:
Here we can see that there are two discrete information pathways between Sales and R&D, and two between Marketing and R&D, all based on ‘who knows who’. Sometimes these channels are formal, often they’re informal, and the one thing we’re learning here, is that it doesn’t really matter, because the information will flow anyway!
Like most human social systems, these relationships tend to break down when you exceed about 200 people. As long as everyone knows everyone else, these systems operate wonderfully. When your organization grows bigger than that, you end up with two major problems:
1. Where can we get the information? People often know they need more information, but they don’t know where to get it. This is the classic discoverability problem: you don’t know what you don’t know. In our example above, Bridget in Sales isn’t getting any information directly from Charles — the only possible route is fourth-hand information via marketing, or third-hand through Aaron. Is this lack of information affecting Bridget’s commission? Who knows? Bridget doesn’t.
Addressing the discoverability problem from an information-only perspective i.e. the way Google fixes the problem doesn’t appear to be ideal within the enterprise. People can misinterpret information and corrupt its original intent. Information-only solutions can lead to situations where Bridget quotes technical specs from an R&D product that doesn’t exist to a potential customer.
It’s much better to be able to get the people involved in this information transaction connected than to pass raw data around. That’s why a lot of this enterprise social networking stuff is so interesting. Having done that, we still have the second issue.
2. How can we evaluate the quality of the information source? How can we determine that information from one contact tends to be more correct or useful to us than information from another contact? This is a much harder problem. Small, subtle errors can have cumulative effects that degrade productivity.
Here at Infovark, these are the kind of things that we lay awake at night pondering.
The way we attempt to solve this problem is to make a few assumptions.
First, we assume that your enterprise is generally successful at whatever it is you do. We figure that the current mode of operation within your enterprise has led to some kind of success. Once we assume this, we can watch how people work within the organization, and build a pattern of communication pathways — just like the ones that HP studied on Twitter.
Having an idea of how people communicate with each other is the beginning of solving the problem, but we still need to address the quality issue. How do we know which are the best ones? What characteristics define best anyway?
Trying to find an answer to those sorts of questions is impossibly hard for two guys in a basement. Hence our second simplifying assumption: we figure that “repeat business comes from previous success”. Instead of trying to teach Infovark how to evaluate different sources of data, we simply watch what you do with the information. If you consistently re-use an information pathway, we assume you must have a reason for that. It must be more useful somehow. So we strengthen that relationship in our calculations. “Stronger” isn’t the same as “better”, but we’re banking on people to be lazy and gravitate to the pathways that require them to do the least amount of work for the most reward. It’s kind of an Invisible Hand principle.
So, the individual needs to be presented with all the options — the strong and weak connections. People can try out the other paths, and if they become more used, we assume that they are ‘better’, and adjust them accordingly.
Now Bridget can see that it would be best for her to connect to Anthony, Charles or Brenda — but most of the Sales/R&D communication seems to go to Anthony. Armed with this information, she can choose to follow the same path, or connect directly with Charles, or even talk to marketing. The awareness of the most used pathways, and the available contacts, give her a better idea of how to go about solving her discoverability problem.
Over our experience with Infovark we’ve found time and time again, that the best way to improve productivity is not some huge mathematical scary algorithm to divine hidden trends, but simply to watch the way that people work and how they work with each other.
Social Networking Analysis? Or just remembering what works?
It’s odd that it’s taken so long for social software to make inroads in the business world. Social networking has a natural home in the enterprise because the relationships there have a purpose.
Gordon uses Facebook. My wife hung out on MySpace for a while. I never joined any particular network, because I just didn’t see the point. It’s just a bunch of folks hanging out, after all. I’d much rather do that in person.
I eventually signed up for LinkedIn, because it was a good way of staying in touch with former coworkers. It’s also a great resource for finding a new job, and it sure beats carrying around a stack of paper resumes. But I only check in occasionally.
I think it’s inside the firewall that the social networks really come into their own. Rands explains the importance of the corporate social network by contrasting the official organization chart with the culture chart. The boxes and arrows on the org chart barely scratch the surface of what’s going on within most companies. Knowing who’s connected with whom, what they do and how they do it… now that’s valuable insight.
Ross Mayfield, co-founder of SocialText, and Stowe Boyd, a leading social software consultant, have been discussing whether the focus of Enterprise 2.0 is the individual or the group. You can read Ross’ latest thoughts in his groups and networks post. We’ve weighed in on the topic, too. Gordon wrote that there is no enterprise — it’s made of people.
Unfortunately, Enterprise 2.0 means different things to different people. But it does imply a change in priorities and a different way of doing business. You’ll find those two concepts present in most definitions of Enterprise 2.0.
For the last century or so, we’ve structured the corporate engines of the economy to handle problems of scale. We’ve seen major revolutions in manufacturing, logistics, and transportation as a result. Mass production and mass distribution have changed the way we live and work and vastly improved our standard of living.
But not every business problem is a problem of scale. The same managerial techniques and organizational structures that make today’s cars and computers won’t work well for producing television dramas or delivering health care. Yet if you skimmed the business and economics section of your local bookstore, you wouldn’t find much good advice for in running those sorts of enterprises. Nor would you find many off-the-shelf software applications to help you run those businesses — until E2.0 came along.
Other sectors of the economy haven’t seen the dramatic productivity gains that manufacturing and distribution have. And most of those companies don’t follow the rigid corporate hierarchy lampooned in Dilbert. Law firms, medical practices, and consultancies often run on a partner model. In entertainment or design it’s not uncommon for the highest paid individual to be a member of the staff rather than the managers or directors. Where’s the Michael Porter for these companies?
That’s what Enterprise 2.0 is about. It’s about adapting some of the successful tools and communications technologies found on the open web to solve problems faced by people working in creative, knowledge-based industries.
The priorities have shifted from problems of scale to problems of innovation.
Ross Mayfield is right when he says that “the fundamental unit of collaboration is the group.” Whether you’re managing a small team or large division, you’ll likely find dozens of products that can improve group dynamics or productivity. These range from old-school solutions, like hiring an information architect to redesign the internal web portal, to state-of-the-art E2.0 products from folks like SocialText, MindTouch or Jive Software.
But Stowe Boyd is also right. The primary difference between 1.0 and 2.0 solutions is the focus on individual users. Tim O’Reilly, who coined the phrase Web 2.0, famously summed the Web. 2.0 vibe by saying, “users add value.” Individuals can and should contribute directly to the content of sites they visit and the organizations to which they belong. If the fundamental unit of collaboration is the group, then the fundamental unit of knowledge work is the individual.
The challenge of enterprise social software is to make tools that work for both the individual and the group. It’s devilishly hard to do, and there’s no shortage of failed attempts, from custom IT projects that fail to high-flying dot.com companies that go bust. Getting ad hoc groups of intelligent, creative people to work together in harmony is an art.
But people thought the coordinated, mechanized dance of the assembly line was an art, too, before management science made it routine.