For anyone new to knowledge management systems, the idea may seem dauntingly complex and technical. But if you break it down, it’s simple. When a company or organization needs a way to organize their knowledge, whether it’s digitized or in some other form, and share it rationally among many individuals, they need a knowledge management system.
In today’s increasingly technology-driven business world, a knowledge management system is more and more becoming an indispensible part of any competitive company’s organizational infrastructure. Without one, data gets lost or sent to the wrong places, there is no framework for sharing and restricting information, and people end up relying on comparatively sloppy ways of sharing information. Drawers of documents, fax, and even email are rapidly becoming modes of the past. Today, more organized, high-tech solutions are needed, and a few old nondigitial standbys are still useful.
There are many models widely used for knowledge management systems. Because there are many types of organizations with a wide diversity of needs, the world of knowledge management systems has developed into a thriving and creative field with many innovators continually coming up with novel new solutions for information sharing and processing. Let’s look at a few of the more common types of knowledge management systems used in today’s business world.
Document sharing
One of the most widely used types of knowledge management systems includes those that enable multiple people in an organization to share documents such as word processing files and spreadsheets through a network. There are a few major tech companies that provide easily accessible types of document sharing. Google Docs, for instance, is used by many businesses to share and collaborate on documents.
Several issues often arise with this type of knowledge management system. First, companies often must deal with different levels of permission for types of documents and for individual documents. Especially when it comes to larger companies with a large pool of lower-level employees, it is often important to make sure that only individuals with a certain degree of authority can alter and save documents. Fortunately, permissions are usually pretty easy to set up, but such top-down organizational structures do have downsides. For one, when lower-level employees are blocked and don’t feel their ideas or contributions are welcome, it can hurt morale.
Another issue that arises with document sharing is how to handle collaboration. When multiple people are working together on a document, it is easy for things to get confused, especially when two or more people try to edit a document at the same time. Meanwhile, edit tracking can quickly drown the document in markup. These, too, have relatively simple solutions, however, and most of the top document sharing platforms have built-in solutions.
Another issue with document sharing is the way a shared directory of documents can quickly become chaotic. With directories, subdirectories, overlapping documents, and multiple versions of the same thing, such systems often require someone to keep things organized.
Community knowledge databases
There is a reason why Wikipedia, despite its flaws, has grown into not just one of the most trafficked sites online but also a go-to source for basic information about practically anything. The fact that it makes virtually everyone in the world a potential contributor and editor gives it unprecedented potential. And indeed, it’s living up to this potential with nearly 4 million articles now live on the English site, a good portion of which actually contain reliable information. Such a large information cache has never been possible in the history of the world.
Seeing the success of Wikipedia and similar projects, many organizations are seeking to replicate that success, albeit on a much smaller scale. Many companies have established large Wikis for customer reference, and while these can be helpful, there is usually little incentive for anyone to voluntarily contribute. As a result, many such Wikis languish and provide poor customer service. Much more effective are internal Wikis for use within large companies. Many companies are secretive about these projects, but it’s well known that many of the largest corporations in the world have user-generated communal knowledge databases, and they can be great resources for employees.
Of course, it can be difficult to get people within an organization to set time aside to share their knowledge on the centralized knowledge database. That’s why many companies incentivize this work. Although no immediate benefits of doing so may be apparent, the knowledge database inevitably becomes more useful as it grows. It’s helpful, for example, for orienting new employees who are unfamiliar with company procedures. And it can be great for employees whose jobs involve complex and manifold procedures that are difficult to remember. In this sense, it’s a sort of flexible, digitized policies and procedures manual.
Expert-run systems
While vast libraries of information can be built through community systems like the ones described above, some companies desire a more centralized approach, with one or more individuals compiling information and putting it into an accessible form for all the members of the organization to use according to their needs. The obvious disadvantage of expert-run systems is that they require a great deal of work on the part of the experts who run them. But the advantage is that all users know the information is reliable because it has been vetted by a knowledge authority.
Companies that have expert-run knowledge management systems typically must have the resources to be able to a support a staff of multiple individuals tasked with doing nothing but running the knowledge system. For this reason, organizations usually try to minimize this aspect of their business during lean times. This raises all sorts of issues when company employees perceive that work that should rightly be left to the experts is now being asked of workers whose jobs and expertise lie elsewhere.
Hybrid knowledge management systems
To achieve a balance between community-generated knowledge systems and expert-run systems, many companies have sought hybrid models. In such systems, all members of the community are asked or encouraged to share their knowledge freely through the central system—which can take any number of forms—where it is moderated by an expert. It’s similar to the typical setup at a major newspaper, where journalists and other contributors are given assignments or submit their own ideas for stories, and all stories must pass through the editor before going to publication. The editor has the power to approve pieces or send them back for revision, and he or she can make appropriate changes.
In a hybrid knowledge system, an individual or a small team of people serves in the editorial role, acting as a sort of hub through which all the knowledge must pass before becoming accessible to all. The main advantage of this system is that all knowledge is vetted and polished before it goes live for others to access. The main disadvantages are that it can be a little clunky and that it can cause tensions that may lead to some employees becoming disengaged from the process.
Mentor-student knowledge sharing
When it comes to jobs that are complex or have a steep learning curve, new arrivals into an organization often feel in over their heads and do not get off to a good start. If not managed correctly, these situations can have bad results down the road. One way to subvert this problem and to make sure new employees gain all the knowledge they need is to set up a mentor-mentee system in which newcomers are formally attached to a veteran and encouraged to go to that person for all questions.
An added benefit of this type of system is that it can foster a sense of community within an organization. Conflicts between veterans and newcomers are common sources of tension inside organizations, and the mentor-mentee system sets up a spirit of cooperation right off the bat. The only disadvantage of this system is that the mentee’s experience with it can only be as strong as the mentor’s commitment to the process. When a newcomer gets paired with a veteran who doesn’t believe in the process or simply doesn’t have the motivation to participate, the system is worthless.
Another important characteristic of a good mentor-student system is that it should be long term. It’s not merely a training program that lasts a few days or weeks and then wraps up. The mentor-student relationship continues as long as both individuals are still with the company. Interactions between the two typically start off frequent and eventually taper off as the student becomes more comfortable. Even after that, however, the mentee always knows where to go if he or she needs some knowledge or wisdom about company operations.
Fostering ideas
Google famously allows its employees to devote 20 percent of the work week (or one full day per week) to working on special projects of their own devising. The only catch is that employees must be open about what they’re working on, and the project officially falls under the Google umbrella. Many of Google’s now-popular products and services developed this way.
While this type of policy may seem somewhat outside the concept of knowledge sharing, what’s relevant here is its openness. When Google employees develop interesting new technologies in their special projects, Google can then harness those technologies toward other large-scale projects. And when you have a company full of innovative people like Google has, it turns the organization into a virtual think tank, with everyone bouncing around ideas and feeding off each other in incredibly productive ways.
In other words, when people are given free rein to pursue projects they are passionate about, it assists in the development of knowledge that can be shared in the company. And perhaps equally important is the fact that this type of policy helps create happy employees. Of course, it is inevitable that many of these small projects falling under the Google umbrella will not succeed, but Google’s overall strategy of trying everything and sticking with what works has obviously done well for it so far. Other organizations should consider adopting similar models.
Social computing
In a large company, it is simply not practical for everyone to spend inordinate amounts of time chatting with coworkers. Social networking technologies make employee interactions quicker and more efficient, however. Consider a social network such as Twitter, and imagine that everyone within a company is following a company-related hashtag on the side of their computer screens. If someone has a question or needs a piece of data, all he or she has to do is post a quick tweet, and within seconds the answers will come in.
Of course, most companies don’t actually use Twitter or other mainstream social networks, but many are beginning to implement similar systems that enable companywide, instantaneous sharing of knowledge. The disadvantage of this type of system, of course, is that the interactions can be a little messy. Plus, the knowledge tends to fall out of the conversation stream as quickly as it arrives. So social networking systems are not solutions for gathering knowledge and giving everyone access to it, but one can certainly imagine hybrid models that harvest knowledge from the collective social brain and put it into permanent and accessible formats.
AI-based knowledge sharing
Artificial intelligence is still a futuristic technology in many people’s eyes, but innovators around the world have made great strides in recent years. Computer learning, for instance, has come a long way in a short period. To once again use Google as an example, over the last few years Google has gradually phased into its search algorithm elements that could fairly be described as artificial intelligence. Its machines follow user behavior and determine which search results please people and which do not. And since this is an ongoing process, the algorithm is no longer set in stone, but rather automatically updates on a continuous basis.
Of course, AI technologies are still far outside the realm of what most companies can implement, but watch for new developments in the coming years. Before long, AI-driven technologies will be serving as hubs for information processing and sharing within companies and organizations of all varieties and sizes.
