One of the things I like most about Dell’s Toad community is how millions of professionals from all types of businesses and industries come together to solve database management problems. There is a common purpose that often goes a step or two beyond typical collaboration to unlock universal truths.
I call this “collective resourcing”—tapping the combined intelligence of a community to find and fix ubiquitous problems. Individual contributors and collaborators can add their unique spin to drive increased value for the entire community. The result: a universal solution to a universal problem, a vertical solution to a universal problem or even a universal solution to a vertical problem.
Not only does collective resourcing widen the depth and breadth of the underlying community, it’s also the key to enabling the open-source market to grow and thrive. Last month, I wrote about the conundrum caused by countless “Big Data or Hadoop science projects” dying on the vine.
One reason these projects struggle is that companies focus too much on solving individual problems for individual purposes, and miss the bigger picture in the process. We need more outside-the-box thinking on how to apply a particular body of knowledge to deliver broader, deeper and sustainable business value. Perhaps the best example of the massive potential of collective resourcing is Open Source Ecology (OSE), a network of farmers, engineers, architects and supporters developing the Global Village Construction Set (GVCS)—a LEGO-like set of tools for building the 50 most important machines that it takes for modern life to exist.
In an inspirational TED talk, OSE founder Marcin Jakubowski describes a world of innovation accelerated by open, collaborative development and interdisciplinary, synergistic thinking. While OSE’s blueprints make it easier to build everything from a farm tractor to a bread oven and even a circuit maker, the ultimate goal isn’t to simplify how individual machines are made. Rather, it’s about developing a complete machine construction system that can be used over and over to build any machine whatsoever.
That’s the essence of collective resourcing—the sharing of ideas and knowledge to unearth universal truths. This approach can be applied to any business across any sector or industry. For example, I’ve been working with a large, multi-national construction company striving to lower worksite accidents and ultimately, worker’s compensation claims. So, they set up a Hadoop cluster to correlate safety and weather data to preemptive and prescriptive actions, such as recalling crews as storms approach or rescheduling welding tasks during high winds.
While the basic correlations proved useful, the company wanted to do more with their data. They wanted to know which worksites might be more accident prone and why. Now, they could hire more developers, stand up more Hadoop clusters and create additional science projects to unlock new discoveries. In doing so, though, they incur more expense and end up with yet another interesting but isolated science project. Since they have many other data discoveries underway, chances are high they’ll abandon this one.
But, what if they could tap the collective intelligence of other construction firms grappling with similar safety concerns? By aligning with other like-minded companies, they could identify the most prevalent safety issues common to everyone. Then the combined insight around the shared experiences could produce more accurate safety models and precise predictive analytics.
This would likely propel a move forward because they could quickly reduce their own worksite accidents, while producing a valuable, universal solution to a universal problem. I bet other firms would be interested in buying packaged safety reports, metrics and models from them. Now, that’s what I call taking your science project to the big time!
Science projects that evolve in this fashion return the greatest value to the business—either as something others can use to speed their own discoveries or as solutions that can be packaged and sold. And, it paves the way for what my Dell colleague John K. Thompson calls an “analytic model marketplace,” where companies can reap the benefits of collective resourcing and true cross-community collaboration.
At the end of the day, we’ve seen many examples of how collective resourcing works among the four million members of our Toad community. Members continually join forces to solve simple problems and accelerate major breakthroughs. It’s proof this concept can unlock universal truths faster, cheaper and better than other approaches. What do you think? Connect with me on Twitter at @joschloss to share your thoughts.