In the oral traditions of early indigenous cultures, knowledge was preserved and passed on through storytelling and used to help others understand their cultures and the dangers and pleasures embedded in them. In essence, stories were a way of creating frames for decision-making based on conveyed knowledge and experience. These were the earliest knowledge management systems.
Knowledge was later captured in paintings, then in symbols that evolved into written languages, and so on until now we have libraries of books, access to boundless amounts of information via the Internet, and standard cataloging systems that help us find and organize information.
There are also more obscure notions of what knowledge is and where it comes from. Have you ever had a Eureka! moment, for instance, when all of a sudden you reach, from seemingly out of nowhere, a point of total clarity around an idea? Author/philosopher Joseph Chilton Pearce would tell you that you’ve tapped into a field of knowledge, an unseen quantum-level source of information existing in an almost ethereal form that our brains can, most often unconsciously, tap into (Pearce has posited that savants with unexplainable skills are connected to such fields).
OK, so maybe that’s a bit out of reach using web services and Web 2.0 utilities, but in this time of technology-based business transaction, communication, and socializing, the organization and representation of knowledge is certainly reaching new levels of potential. The notion of knowledge management is becoming more popular, as in the organizational realms we leave the age of data warehousing and celebrate the rising tide of business analytics, while in the social realms we continue to share information in exponentially rising quantities and organize in ever-growing numbers via the plethora of community building platforms available today.
In her book “Momentum: Igniting Social Change in the Connected Age,” Allison Fine explains the phenomenon as one of moving from the proprietary, protectionist “Information Age” into the participatory, open “Connected Age.” She describes the fears organizations have in releasing their grip on information they have come to value as core to the worth of their work and services. “They falsely believe,” says Fine, “that this information alone equals power.” So this brings us to the question, what is knowledge worth?
First lets consider types of knowledge. There is raw knowledge, in which specific, targeted information becomes valuable to a research topic. There is strategic knowledge, which helps guide decision-making, drive marketing activities and measure productivity. There is operational knowledge, which is the dull yet sensitive financial and human resource information used by businesses to inform their plans and budgets and improve performance. There is tacit knowledge, which is the kind that is often not captured because it resides in people’s minds and on sticky notes and is leveraged by its holders to do their jobs. There is sociocultural knowledge which steers us toward areas and activities we align with, both recreational and purpose-driven. In other words, knowledge tends to get categorized in ways that keeps it neatly boxed for us to engage with it in contextual ways, and the systems we use to access knowledge are thus equally fragmented. At the same time, every type of knowledge area we draw upon and feed carries value.
What is more important to recognize is not only the convergence we are seeing in tools for accessing and sharing knowledge, but the paradigm itself to which we are shifting; one which values the social network as the core component for spreading and retrieving knowledge. Just ask your Facebook or LinkedIn networks what the best cell phone plan is for a family of four (the more specific the question, the better), and see how much time it takes to get some experienced, well-vetted answers compared to how much time it would take you to research the plans for even the top four or five cell service providers. Not everyone will answer your questions, but the answers you get will usually be quick and substantive, and the more answers you get, the more likely it is they will coagulate around a common solution.
This may be an easy experiment as an individual, but how can this be extrapolated to the organizatinoal level? First of all, today’s organizations do not even necessarily include social networking potential as part of a knowledge management strategy, especially those that are in the early stages of integrating their internal data sources to achieve a higher level of operational and strategic knowledge management. I’ve been working through an O’Reilly book called “Visualizing Data,” by Ben Fry, in which he outlines his seven stages of visualizing data: acquire, parse, filter, mine, represent, refine, and interact. It was the last step that inspired me to come up with a similar list of steps to consider when building a knowledge management system.
But first, let me step back for a moment so I can explain that I have built many enterprise systems in the past, some of which dealt with specific types of data, and some of which spanned and integrated data from multiple sources. These systems really only achieved knowledge management at the operations level. Today I am faced with building systems that pull together potentially all available knowledge types I listed above, and what I’ve discovered as I pursue this monstrous task is that there is no way to draw a diagram that fits the pieces together nicely and lays out a single path to integration. This effort requires iterations of layering across all of these areas, a persistent weaving of these areas into deepening levels of interaction across the knowledge spectrum. So, it is Fry’s last step, “interact,” that prompted me to create this initial list of steps toward building not just a knowledge management system, but a platform upon which to collaboratively continue to grow solutions:
- Assess: Make a list of the data you currently collect across various systems as a starting point, and figure out what makes sense to leverage into metrics, to share more broadly, and to collect more efficiently (especially look for areas where the same data is collected in more than one place). Then extend your list to include data you should be collecting that you are not.
- Organize: The traditional way to organize data is to develop a taxonomy by which data can be categorized, and although that’s a good start, it is a top-down approach to the problem. What is better suited in the Connected Age is the accommodation of the bottom-up approach using a “folksonomy,” by which those who access the information can “tag” it and organize it more organically.
- Integrate: Ideally, your various sources of data exist within systems that have some way of exporting and importing data between them. XML-based web services is probably the most common technique used for data exchange, but there are a number of ways to achieve this, including the establishment of a central data mart where data can be put together in creative and informative ways. Warning: big black hole potential here–be wary of time, labor, and expertise requirements that can translate into high cost.
- Report: Reports are commonplace and should continue to be developed as you integrate your data sources based on your desired metrics.
- Represent: Data representation is the next step above reporting and includes charts, graphs, and combinations of visualization methods into dashboards and widgets. It is at this step that having some sort of central, often browser-based portal becomes handy, espeically if you want your representations to be real-time based on the most current data.
- Refine: Although this is labeled as step number six, it is really an iterative process that applies to all of the previous steps. You should always be looking for opportunities to incorporate connections to new data sources as well as areas to deepen and improve upon what you already have.
- Interact: Finally, the step that raises this system to the social, connected level is interaction, or giving people inside and outside the organization the ability to not only view reports and representations, but also to create their own reports and visualizations. That, of course, would only be scratching the surface. Adding functionality that encourages sharing, tagging, commenting, exploring, and collaborating would truly extend the organizational knowledge base into the sociocultural realm where the real potential lies.
I know I haven’t yet reached any answers to the question of what knowledge is worth, but I have outlined the considerations for what I believe provides a framework for assessing the value of knowledge from an organizational standpoint. I’ll pick up next week with reflections on the role of participation in the framework, what that means for organizations still mired in the Information Age, and how the social networking paradigm adds value to knowledge systems.