If enough people are in a conversation, one of them will be an expert. The larger the crowd, the more unexpected will be the expertise contained within it.
Of course, “larger” in this case may mean thousands, or tens of thousands. And, to uncover really obscure expertise, you may need millions of people. Of course that also means that you’ll need a social environment where obscure expertise can rise to the top. But that’s supposed to be impossible: Conversation doesn’t scale, we were told.
We were told wrong.
Finally, however, in the last decade Hinton and other researchers made some fundamental conceptual breakthroughs. In 2006, Hinton developed a more efficient way to teach individual layers of neurons. The first layer learns primitive features, like an edge in an image or the tiniest unit of speech sound. It does this by finding combinations of digitized pixels or sound waves that occur more often than they should by chance. Once that layer accurately recognizes those features, they’re fed to the next layer, which trains itself to recognize more complex features, like a corner or a combination of speech sounds. The process is repeated in successive layers until the system can reliably recognize phonemes or objects.
David Kay is one of the best knowledge management consultants (if not best consultants) I’ve known. As anyone who knows him will attest, David’s one of the few consultants that ‘gets it’. Real change in organizations, particularly with knowledge management, is not as much about technology implementation as it is about process transformation. And, process transformation rarely happens unless there is an organizational culture that is amenable to change.
Over at his blog, David has an excellent post about warning signs he’s seen in corporate cultures over the last decade of consulting. While he’s focused on the knowledge sharing process, the post could apply to just about any corporate transformation effort. Representing the technology vendor’s point of view in many instances, I found myself nodding with each of his eleven points, especially point number eleven:
11. A lousy work environment, food service, and coffee. Look, we’re not all going to work in the Googleplex with free gourmet lunches and company-branded ice cream treats. But we spend a lot of time at work, and our mental state there matters, and our heads are influenced by our environment. (There’s a reason they spent so much time building cathedrals in the Middle Ages.) If I go to an office building that’s dingy, dreary, sterile, and cut off from natural sunlight, I know something. If the coffee service comes out of 1950s-style glass carafes and hotplates with generic pre-ground beans in foil packets, I know something. If people resign themselves to the depressing burger-and-fries or meatloaf options at the cafeteria, I know something. And if the company hasn’t spent the money for decent computers, double monitors, comfortable ergonomic chairs, and IT that works, I really know something. I know the company doesn’t really care about the employees, no matter what they say, and it’s going to be wickedly hard to get the team excited about taking on a new challenge.
The cafeteria comment made me laugh as I was reminded of a large company cafeteria I visited where there was a five cent up-charge to use plastic utensils (for EACH utensil). You can only imagine what the morale level was at that now defunct large company.
Check out David’s post, I’m certain it’ll remind you of places you’ve seen as well.
Earlier today, Oracle announced an agreement to acquire knowledge management vendor InQuira. Given InQuira’s deep integration with legacy Oracle products, and despite partnerships with SAP and Genesys, it was just a matter of time that Oracle absorbed InQuira. R.Ray Wang explains why Oracle finally pulled the trigger:
InQuira “is one of the top knowledge management vendors in the business,” said analyst Ray Wang, CEO of Constellation Research. “They’ve been positioning for a sale to Oracle or SAP for the past 24 months.”
While knowledge management is “a critical component” of CRM systems, most have “a big gap in this area,” Wang added.
It might seem that a vendor such as Oracle, which already had content management and enterprise search capabilities, could build out its own knowledge management system. But the fact is that knowledge management is “a specialized niche,” not only in terms of technology but the customer base, Wang said.
The last point that Ray makes is key, knowledge management is a specialized niche, a niche that ultimately wasn’t big enough to sustain standalone vendors. To put it another way, enterprise KM turned out to be a small pond.
Having spent many years in that pond, I can tell you it was a tough place to swim. While we all might have thought we were creating a blue ocean for ourselves, market realities and shortsighted sales strategies ended up creating a red ocean. Knowledge management in this red ocean required access to channels, or flows of knowledge. That meant ultimate dependency on the owners of those channels – the CRM vendors. So it comes as no surprise that the last fish in that small pond gets gobbled up by the largest CRM vendor.
The era of bulky, on-premise enterprise KM is over, but that doesn’t mean a blue ocean doesn’t exist for KM.
Forrester’s Kate Leggett also offers some good insight on the announcement as well.
Since the rumor about Microsoft’s $100M acquisition broke last week (now no longer a rumor, but a fact), I’ve had several people ask me on my take of where Microsoft is headed with this new tool in its search toolbox. First let me frame my angle here. Over the last four years I’ve worked in the small but interesting enterprise software space of knowledge management. One of the key elements of successful knowledge management is the ability to ‘find’ knowledge. As I recently wrote in a KM World article (Your Customers can Search, but do they Find?), finding implies a level of intelligence beyond simple keyword search. This is where natural language processing (NLP) technologies come into play. As with the field of knowledge management, NLP has been in and out of favor over the last decade. With the Powerset acquisition, Microsoft is clearly betting that NLP is not only back in favor, but Powerset’s brand of NLP is the best available in the market. That being said, here’s my take:
Most of the quick analysis of Microsoft’s move was focused too narrowly on the entire Yahoo acquisition drama, and Microsoft’s attempts to challenge Google, but Microsoft’s own Don Dodge stepped in with an excellent post of where the real potential of the Powerset acquisition lies:
1. Powerset technology is more about indexing the content and understanding its meaning, than the query itself. This has enormous implications.
2. There are many lucrative markets for this technology…not just consumer web search.
The second point is worth noting first. Of course Microsoft will use Powerset to enhance its struggling consumer search properties, but incorporating Powerset into its many enterprise applications has as much potential as a consumer solution. The enterprise approach can manifest itself in two of Microsoft’s most critical corporate infrastructure properties, Sharepoint and Exchange. Once a clunky file sharing server, Sharepoint has evolved into a venerable knowledge management platform that can also handle many modes of collaboration. If Microsoft incorporates Powerset’s NLP into Sharepoint, that platform will emerge as a serious threat to many of the pure enterprise knowledge management, content management software vendors that currently dot these markets. Many of these vendors routinely sell their technology as a replacement for the inadequate built-in search for Sharepoint. A Powerset integration could change the equation. Additionally, incorporating Powerset NLP into Exchange, Microsoft’s anchor platform in the enterprise, could add a layer of intelligent search that has yet to be addressed by other vendors. While it may prove impossible to regain significant marketshare in the consumer world, Microsoft has a significant opportunity to consolidate control in the enterprise knowledge management arena. Powerset’s technologies could play an integral part of this consolidation.
Now, back to Dodge’s first point. Indexing and enabling textual search on content is a relatively old, and easy task. Grafting meaning to that index is where the game changes. Intelligent search, or search with an implied meaning, will return ‘answers’ as opposed to ‘results’. There is a significant point to be understood here. In the traditional mode of searching, search engines are designed to bring back the entire subset of content where there are keyword matches. This can result in hundreds, thousands, and often times hundreds of thousands of ‘hits’ that are returned. Google’s strength is identifying these hits and then representing the most popular results at the top of the result set. Intelligent search is different. In fact a good measure of intelligent search is how few results are returned. Since intelligent search first attempts to find meaning on indexed content, the resulting hits returned by an engine like Powerset should only include that content which is in context to the entered query. This can have a huge impact in enterprise deployments of traditional search, but as Dodge says in his post, the utility of receiving ‘answers’ can be extended beyond content search to include advertisement targeting, and other enterprise focused solutions.
While it’s too early to know exactly what Microsoft will do with Powerset, I think it is as important to watch the enterprise software angle on this acquisition as the consumer angle.