Using Social Business Software to See Over the Mountains

If you’ve never seen the movie Alive, the clip below may not make a lot of sense. It’s based on a true story about a Uruguayan rugby team surviving an airplane crash in the Andes. Many of them die, but eventually three team members set out to try to find help.  At one point (about six minutes into this clip), they climb a steep ridge only to see nothing but more mountains.

So here’s the odd thing – this clip reminds me of email.

I don’t think anything in the normal working world is in any way as tragic and harrowing as what happened to these people. But here are the parallels I see in this scene:

1. After one mountain, it’s just more mountains.
2. The situation is impossible.
3. Part of surviving is seeing beyond the mountains.

The reason this reminds me of email is the whole never-ending nature of the mountain range.  I’m writing this blog post at 12:30am in a hotel room while trading emails with co-workers.  In a typical work day I receive between 200 and 500 emails, and I don’t think I’m at the crazy end of the curve. In the majority of meetings I have with people inside and outside my company, a laptop or a smartphone is open for nearly all participants. While those of us who work in software may feel like we’re uniquely overwhelmed by mountains of data, I’m reminded that we are not alone when I take a glance at my wife’s laptop to see all the emails and events involved with my family’s daily life.

At one point in the Alive movie clip, one of the characters describes the entire situation as “impossible” - impossible that they had survived for so long and climbed these mountains. The rate of information creation today is impossible. A recent comment from Eric Schmidt at the Techonomy Conference stated that every two days we now create as much information as we did from the beginning of time until 2003. To me, that is almost the same as saying “the mountains not only go on to the horizon, but they are also getting taller.” It’s impossible. While human brains are phenomenal, we all have limits. Just as one of the guys in the movie has to turn back from the climb, we are similarly using filters to make it possible to avoid the worst parts of our daily avalanche of data.

The third parallel I see is the promise of technology to help us get through these mountains. For the climb through the hills of data, there will never be an ending like the movie where the two teammates actually emerge into a valley. It’s hard to imagine some force that will constrain data creation. On the flip side, it’s easy to see things like the proliferation of smart phones that will drive ever higher volumes of data. But one of the coolest things about humans is that we continuously find interesting solutions when the problems become impactful enough. And, while I can’t see any “silver bullet” that makes me think we’ll get through our mountains of information, I do think we will see a lot of innovations over the next couple of years that will make our climb much easier.

For me, the most exciting innovation is the combined potential of social and semantic technologies. At the heart of increased data creation is that so many more humans are creating so much more data much more quickly. The value of social business software in this context is if a system knows a lot about me and a lot about the other people creating the data and a lot about my connections with those people, it has the potential to do a lot of work carving a path through the mountains of data on my behalf. As a trivial example, content created by my boss has distinctly different characteristics than things created by my peers. 

But only knowing how I map to other people is insufficient. My boss is a prolific information producer and sharer within our internal Social Sites activity stream. My colleagues and I cannot consume all the information he sends our way (through @ targeting). One of the key behaviors for filtering my way through the streams of data is to quickly glean the substance of the message – the “what.” Semantic technologies offer a lot of promise for this problem. Most people experience these technologies when they search for something on the web, but I like to think about these technologies as being a really friendly and capable personal assistant who helps to proactively push some pieces of information to the top of the “mountain” while tossing other chunks away.

While many more data points could be incorporated, these two elements already lend a lot of power to addressing information overload. In my experience, the increase in data tends to be primarily “nice-to-know” or “should know” data versus “must do” tasks. Of course automated systems have their faults (just like people who suffer from information overload), therefore, focusing automation systems on knocking down the “nice-to-know” mountains is a lot less risky than having software try to automatically manage your “must do” items. That’s why we’re really interested in looking at ways social and semantic technologies can make activity streams even more powerful by elevating crucial items, eliminating the noise, and ultimately, creating enterprise transparency. What makes this technology even more exciting is a simple brainstorming session with my team produced 35 different data points that could all be used by an intelligent, automated activity stream filter.

I don’t anticipate ever facing a challenge like the one the rugby team encountered in the Andes. The physical and emotional costs illustrated in the movie were intense. However, on a much smaller scale in an everyday parallel, watching the mountains of data in front of you get broader and taller can be truly daunting. Fortunately, I think we’ll be able to see some green valleys in the coming year, and I’m looking forward to the journey.