I’ll be speaking at the upcoming APQC conference on Knowledge Management, about how KM programs can and should leverage the Long Tail of Collective Knowledge. Often, traditional knowledge management programs focus on distilling knowledge into systems of record, which end up being under-utilized for a number of reasons, chief among them because they cannot contain the Long Tail of Knowledge. (Just as Chris Anderson’s Long Tail theory applied to ecommerce describes the large number of unique items available in small quantities—unconfined by physical boundaries or systems—when applied to Knowledge Management, such digital capabilities eliminate physical and IT boundaries to employees’ sharing of even highly specific knowledge and expertise.)
Where is the Long Tail of Knowledge, if not in systems of record? It’s spread throughout all systems, both within and external to the organization, and it resides in the knowledge, often implicit, of employees and other constituencies. Both the explicit knowledge and information itself and traces of employees’ implicit knowledge may be found in IMs and emails, phone records, databases, social media, ECM systems, KBs, CRM systems, blogs, desktop content, collaboration tools, file shares, etc. It is spread among global offices and often with employees who may be working remotely. Activating it requires a combination of change management, process and a systems approach to connecting data and information, and relevant people.
The vast amount of data contained in all of these systems, the variety of its forms, and its fast rate of change sound quite like the challenges associated with managing Big Data: Volume, velocity and variety. According to Gartner, Big Data “is high-volume, -velocity and -variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.”
Also according to Gartner, the primary challenges with Big Data are focused on variety and velocity as opposed to volume, as data storage capacities increase so frequently that too much data this year will not be a challenge next year.
Rather, the challenge with Big Data, as with enabling the Long Tail of knowledge, is relating the information to uncover insights and make better decisions. Inside the enterprise, and arguably outside the enterprise, among customers and prospects, the challenge comes down to matching often highly specific and fragmented information to the context of the individual, so that it is relevant to them. When this is accomplished, it’s easy to know who does what and knows what, as well as allowing every employee to know what your company knows, relevant to their context.
What similarities do you find between Big Data and your collective enterprise knowledge?