Many current approaches to finding useful meaning within the massive content in Web 2.0 and Enterprise 2.0 are rooted in Management 1.0 thinking. In contrast, the Darwin Awareness Engine™ uses content visualizations modeled on human thought to uncover the unexpected in the Web or the enterprise for better informed management decisions. This post starts a six part series on how the Awareness Engine can enable content discovery and make it accessible. First, we will look at the problem in more depth and two existing technologies targeted at it: search and semantic technology.
Web 2.0 has created massive amounts of content, much of it user generated and unstructured, making information overload grow exponentially. Now as Enterprise 2.0 infiltrates organizations, the potential for content overload is reaching into new spaces. At the same time, many researchers and analysts are saying that there are great opportunities for Management 2.0 to take advantage of this growth in information by finding relevant meaning in the mass of content both on the Web and within the enterprise. For example, research by MIT’s Erik Brynjolfsson and colleagues support the business value of “data-driven decision making” for management as organizations adopting this model achieved higher productivity rates.
However, Management 2.0 is at risk to take a few steps backward with the current options to deriving meaning from the massive new content. Unfortunately the exponential growth of information is now calling to duty the data crunchers and process management junkies that are using old-school methods to control and measure through machine-based logic what is emerging in a more human and organic form of content. This approach can conceal much of the potential value, hide anomalies, and mask innovation.
This danger lies in the fact that many of the approaches to finding useful content and making sense of this information explosion are rooted in management and philosophical approaches from the early 20th century (Taylorism, behaviorism, and radical empiricism), and were conceived in the 1990s or earlier before the rise of Web 2.0. These approaches will do little to create a democracy of information, to capture the advantage of diversity, and to amplify imagination. They will not provide what management needs to take full advantage of the explosion of unstructured content both within the enterprise and on the Web.
Next we will look at two of these technologies both rooted in old approaches to management: search and semantic technology.