By the time I was ten, before household scanners existed, I was done typing my reports on school computers after spending hours etching them on paper. My handwriting wasn’t terrible, but it took real effort to make it “final product worthy” and so I wanted a shortcut. I asked my older brother to gather samples of handwriting from everyone in his class (as I did the same), and we’d create a catalog of variations of each letter that we could “teach” to a camera with some kind of computer attached. From there we could just take pictures of our handwritten work and have the camera interpret it all and spit it out as a Wordperfect document (yes – this was in the pre-Word era). I had no idea if this was even feasible, but from a 5th graders perspective, it was my top priority and just seemed like it should be true.
I’m not staking claim to have invented scanners or natural writing conversion tools here. The lesson I learned (albeit much later) was that sometimes the best way to a solution wasn’t just thinking “outside the box”, but was more akin to creating a new box. It’s extraordinarily difficult to remove ourselves from what we know are existing paradigms and limitations. However, sometimes the best new ideas come more from our inner 10 year-old selves than they do from PowerPoints and extensive market research and industry benchmarks. And more often than not, it takes a series of failures to get to the right (or at least more right) idea.
Here’s a boring idea: treat knowledge like an asset and employ the “best practices” of business intelligence and rigors of data governance to gain a tremendous return on investment.
When history majors try to organize themselves and describe their work like data scientists, it doesn’t just sound boring, it sounds perilous. Knowledge Management 1.0 failed. The entire billion dollar wasteland of Knowledge Management tried to do just that – and it cost businesses a lot of money and the field just about all of its credibility. The catch is that it should have worked.
Here’s a revolutionary idea: treat knowledge like Google does.
If you want to find one of the most vague, misunderstood, but critical roles in an enterprise it’s probably in a division called “knowledge management.” There’s a good chance that it’s not actually called that for fear of reprival. Fate wasn’t kind – and for that matter those pursuing the early stages of KM didn’t have it right. Organizations spent a large part of the new millennium investing in large toolsets, people, and infrastructure that largely became obsolete with the surge of web 2.0. Britannica vs Wikipedia… we know how that story went.
At the same time, it doesn’t take much of a leap of logic to connect the needs (and promises) of Knowledge Management with the reemergence of a world focused on “social business”, both in and out of the enterprise. Call it Enterprise 2.0, Social Business, or Knowledge Management, it’s all fundamentally the same thing – organizing knowledge and data in a way that’s most useful to those that want it and those that have it… simultaneously.
Usually big trends in business follow on the footsteps of new research or data staking the claim of transformational ROI. Whether it’s a system (HRM, CRM, ERP/M), a process (six sigma) or a style (management rotations, profit sharing) just about all of these major business trends came about after extensive trial and error, piloting, testing, and researching. We live in a fundamentally changed world if you didn’t notice.
Everything that is now “social” went just about backwards – all of a sudden “social” was producing disruptive amounts of data that cut across organizational units and so a new business trend emerged… big data.
As we’re just beginning to see the way big data plays out across different functions and industries, it got its start in some way as a way to find ROI for everything “social”. In fact, as Dion Hinchcliffe pointed out last month, just about everyone is trying to buy their way into “social” (but more on that another time). Whether it’s because staff expect it (they use it in their personal lives) or it’s how their customers are spending their time (mobile, social, both), for- and not-for profit organizations have dramatically amped up their digital analytics teams to make the most of the change.
But there’s a bigger question that comes first: is Big Data for you?
Like pioneers, the early adopters found ways to bring in the tools that were exploding in the consumer web experience into the enterprise – or really the small business. They didn’t have a good case – no ROI – to justify it, but it felt right and they saw a reason to pursue it. So they did.
In phase two, some of these companies got bigger, supported by healthy venture capital and, equally important, had their technologies adopted by other tech companies that thought “hey, that might work here too.” It was during this time when the sample size grew to be just large enough to start doing some legitimate research on the topic.
After last month’s SAP Sapphire event where all the buzz was about SAP’s big “move to the cloud” there have been a few notable articles and posts around the web about how businesses are starting to adopt to the changing ecosystem of big data, user-driven technologies, and all things mobile. Here are a few key ones not to miss, many by the folks at Enterprise Irregulars.
Like many involved in some type of non-profit management, over the last year I’ve had the opportunity to sit on both sides of a growing organization – one that has reached maturation but continues to learn, expand, and grow and one that is just getting its feet wet and off the ground. A question I’ve been grappling with in both worlds boils down to something like this: “what are the organizational barriers to growth, and how can technology best be applied to solve them?” What I’ve discovered is that the levers don’t change much between the old and new orgs, but how leaders apply them does.