I was discussing with one of our execs the progress we’d been making on social media proficiency internally.

And he asked a great question that made me think:

“So, has anyone fundamentally changed their work processes because of the platform?”

And I realized this is the next frontier on what’s turning out to be a large-scale social engineering project.

Getting Business Value Out Of Our Social Software

As we make progress in this journey, I’ve got my eye out for different catagories of business value we’re seeing.  I suppose, at the same time, I should also be keeping my eye out for business value we’re NOT seeing yet.

And, as I’ve mentioned before, we’re seeing business value — in many forms — across the board:

People with specific interests are finding other people with similar interests
Rather than searching big content repositories, people are asking other people for help and answers
A pan-organizational “social fabric” has been created that wasn’t really there before
Folks who spend time on the platform are better educated — and more engaged — in EMC’ business

And more And, just to be clear, there’s no shortage of business benefits — I still stand behind the broad assertion that this has been one of the most ROI-positive IT projects I’ve seen in my career.

Interesting “value nugget” of the week: 

EMC runs a healthy program to bring a large number of interns and co-op students into the company.  They started introducing themselves to each other on the platform.

What started with “name, rank, serial number” blossomed into a wonderfully diverse set of conversations about careers, favorite hangouts, what it means to work at EMC, what is everybody doing, and so on.

I would argue that — whatever millions that EMC spends on this intern/coop program — we’ve now made it 10-20% more valuable, simply because we connected people to each other, and connected them all to the broader company. 

At zero incremental cost.

But we want more. Much more.
[More]

If the data are plotted as the cumulative adoption of the innovation, it looked like this:

Both of these types of curves have been seen again and again when the diffusion of innovation is examined. They seem to be derived from basic forces present in human social networks.

Ryan and Gross made several key contributions besides the identification of the S-shaped curve. One was the process by which the innovation diffused. The other was the type of farmer who used the innovation.

They found that there were five stages in the adoption of an innovation by an individual: awareness, interest, evaluation, trial, and adoption. And there were at least 4 different types of farmers, of which the early adopters were the most important.

Early adopters heard about the corn from traveling salesmen and tried small plots to see how well it worked. Later adopters relied on the personal experience of other farmers, usually the early adopters. When there were enough positive reactions from the early adopters, when there were more stories of personal experience, the adoption rate took off.

It was the human social network that was critical for the rate at which the innovation was adopted. The more social connections an early adopter had, the more cosmopolitan they were, the more likely it would be that others would adopt use of the innovation.

Everett Rogers was instrumental in codifying many of the principles of innovation diffusion. Here is his famous rendition of the distribution:

Only 16% of a population is usually made up of the early adopters, the ones that are critical for spreading the innovation to the early majority. The key to the adoption of any innovation is the rate at which early adopters can transmit the knowledge of the benefits to the early majority. In the case of the farmers, it would often take 4 or more years for this to be converted form awareness to adoption.

In many areas of our world today, this is much too slow. Technology is disruptive, meaning that the people who adopt this technology actually deal with the world in entirely different ways than those who do not. It is similar to a paradigm shift, in that those on either side of the shift have a hard time communicating with each other. It is almost as if they inhabit separate worlds.

This can cause some problems because the early adopters are required to communicate with the early majority if an innovation is to diffuse throughout an organization. If they can not, it creates a chasm, which has been described by Geoffrey Moore in his book.

The organization has to take strong action to recognize that this chasm is present and to span it, either with training or, more effectively, with people who have been specially designated as chasm spanners. In many cases using Web 2.0 technologies, they are called online community managers.

Disruptive innovations seem to arrive almost yearly. Without a directed and defined process to increase the rate of diffusion in an organization, if just standard channels of communication are used, innovation will diffuse at too slow a rate for many organizations to remain competitive.

Because there is usually not just one innovation disrupting an organization at a time. Life is not that clean. There can be multiple innovations coursing through different departments, moving early adopters even further away from the rest of the group and expanding the chasm. This only makes communication harder.

It can no longer be possible to simply let the early adopters go through their 5 stages of adoption and then tell others about it at the water cooler. Designated online community managers, with the training needed to enhance communication channels, will be critical in getting this information dispersed throughout an organization.

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