As I continue to have more and more opportunities to share and discuss the concept of the Snowflake Effect with more and more diverse groups of people around the planet, I am finding that one of the most surprising things to many is the degree to which I see this affecting the people, the snowflakes, themselves. For example I often talk about the “obviation of the org chart” as I put it, which is my reference to the pattern I see both necessary and already happening whereby we group ourselves less and less with the traditional departmental model. for most organizations, be they business, government, academia or non profits, we’ve evolved to a common model of grouping people into departments of shared function; sales, marketing, engineering, IT, etc. I understand this model and it can be argued to have served us well for a very long time.
So what’s the problem? In a word; projects. Almost all work is now project based, be they small or large, short or long term, it is rare that we do anything outside of the project structure. Projects are by definition very multifunctional and therefore they are at odds with the departmental model. Departments and the org chart model make it increasingly difficult to find “just the right” people across departmental lines and most of us have experienced the difficulty of trying to manage budgets across departments. These and many other examples show how the very organizational structure that we’ve put into place to increase efficiency and effectiveness has become one of the greatest barriers we face in trying to get good work done.
What’s the alternative? Snowflake organizations and all the snowflakes within them. Treat each person as the unique snowflake they are by capturing more and more detailed and granular data of the millions of attributes and characteristics that describe each of us. Our skills, knowledge, attitudes, aptitudes, experiences, etc. This is not a trivial task in itself, but it is absolutely doable and there are increasing ways of automating and otherwise generating more and more of what could be thought of as personal metadata. We would also be developing an infrastructure to enable the generation of this personal metadata to be more and more dynamic and constantly changing over time as we work and learn and develop new skills, new knowledge and experiences. And also as we loose some skills from lack of use and unlearn others.
With this type of personal metadata available we are now able to do some extraordinarily valuable and pragmatic things that get us closer to that state of “just right” as we are able to find just the right person at just the right time. The person to talk to, to ask a question, to ask onto a project team, to read their writing, listen to their podcasts, etc. While the volume of such personal metadata is staggeringly large when you consider how many attributes there would likely be for any one of us and that there are already 6.6 Billion of us on the planet. But how different is this than the problem of how do you find “just the right” information in the rising sea of content that is out there? While we still have lost of room for improvement I suspect we all too easily take for granted just how amazing even today’s search capabilities are. And these very same technologies and methodologies can be applied to searching across vast oceans of personal metadata to help us find just the right person at just the right time.
As you think about this, consider how well this enables us to utilize mashups as as conceptual model we can now apply to people. We would be able to find the person with just the right combination of skills, knowledge, abilities, experiences, availability, affordability, etc. who we are looking for a project team, for a phone call, for a meeting, and so on. Think of the increased flexibility this would produce. the speed at which we could find the right people, assemble teams, hire the right people, have the right people on a phone call or in a meeting. And perhaps most of all, think of how we would start to be able to use this personal metadata to help each of us see patterns and trends for ourselves and see patterns that lead to peak performance.
