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Book Summary/Review: Working Knowledge

This article is based on the following book:
Working Knowledge
"How Organizations Manage What They Know"
by Thomas H. Davenport & Laurence Prusak

Printed with permission from:

Recently, many firms have come to understand that they require more than a casual (and even unconscious) approach to corporate knowledge if they are to succeed in today’s and tomorrow’s economies. A company truly is a collection of people organised to produce goods, services or some combination of the two. Their ability to produce depends on what they currently know and on the knowledge that has become embedded in the routines and machinery of production. The material assets of a firm are of limited worth unless people know what to do with them.

1. What do we talk about when we talk about knowledge?

Data is a set of discrete, objective facts about events. In an organisational context, data is most usefully described as structured records of transactions. Gather enough data, the argument goes, and objectively correct decisions will automatically suggest themselves. But gathering too much data can make it harder to identify and make sense of the data that matters. Second, there is no inherent meaning in data. Data provides no judgement or interpretation or basis of action.

Information is a message, usually in the form or a document or an audible or visible communication. It has a sender and a receiver. Information is meant to change the way the receiver perceives something. Information moves around organisations through hard and soft networks. Unlike data, information has meaning. Data becomes information when its creator adds meaning, for example by contextualising, condensing or categorising it. It should be noted, though, that information (or knowledge) should not be confused with the technology that delivers it: The medium is not the message.

The word knowledge is very difficult to define comprehensively, as one should first understand what it means to know something. Thus, Davenport and Prusak do not even try to give us a definition of knowledge but focus instead on a “working definition” more suitable for the purposes of their book: Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organisations, it often becomes I embedded not only in documents or repositories but also in organisational routines, processes, practices, and norms. Knowledge derives from information as information derives from data. The transformation happens for example through connecting, conversating or comparing information.

Knowledge is valuable because it is close to action. Knowledge should be evaluated by the decisions or actions to which it leads. Better knowledge can lead, for example, to more efficient product development and production. Knowledge can also move down the value chain, returning to information and data. The most common cause of this is having too much knowledge present to be able to handle it.

Knowledge is aware of what it doesn’t know. Since what you don’t know can hurt you, this awareness is important.

Values and beliefs are integral to knowledge, determining in large part what the knower sees, absorbs, and concludes from his observations. People with different values see different things in the same situations and organise their knowledge by their values1.

Experience refers to what we have done and what has happened to us in the past. Knowledge born of experience recognises familiar patterns and can make connections between what is happening now and what happened then. Experience based understanding that knowledge of the everyday, complex, often messy reality of work is generally more valuable than theories about it.

Knowledge works through rules of thumb (or as AI people call them, heuristics): flexible guides to action that developed through trial and error and over experience and observation. Intuition can be called “compressed expertise”, that is, the steps leading to the intuition have been so throughoutly learned that they happen without conscious thought.

Increasingly, knowledge and related intangibles not only make businesses go but are part or all of the “products” firms offer. Old distinctions between manufactured objects, services, and ideas are breaking down. Even traditional manufacturing firms are increasingly both users and sellers of knowledge. The intangibles that add value to most products and services are knowledge-based.

At a time when firms need to “know what they know” and must use that knowledge effectively, the size and geographic dispersion of many of them make it especially difficult to locate existing knowledge and get it to where it is needed. The maximum size of an organisation in which people know one another well enough to have a reliable grasp of collective organisational knowledge is 200-300 people. In larger organisations people solve the same problems from scratch again and again, duplicating effort because knowledge of already developed solutions has not been shared within the company.

The low cost of computers and networks has created a potential infrastructure for knowledge exchange and opened up new knowledge management opportunities. But this new technology is only the pipeline and storage system for knowledge exchange. It does not create knowledge and cannot guarantee or even promote knowledge creation or knowledge sharing in a corporate culture that doesn’t factor those activities.

2. The promise and challenge of knowledge markets.

Market forces power the movement of knowledge in organisations. Like markets for goods and services, the knowledge market has buyers and sellers who negotiate to reach a mutually satisfactory price for the goods exchanged. Knowledge market transactions occur because all of the participants in them believe that they will benefit from them in some particular way.

Many knowledge initiatives have been based on the utopian assumption that knowledge moves without friction or motivating force, that people will share knowledge with no concern for what they may gain or lose by doing so. But such one-sided transactions do not happen in most of life. Just because the object of exchange is intangible does not mean that the market forces are less strong. Knowledge initiatives tat ignore the dynamics of markets (and human nature) are doomed to fail.

Of course, there really are no such things as “pure” markets. In addition to “economic”, social and political realities of the organisation have also to be taken into account. For example, if the political reality of an organisation is such that calculating and secretive hoarders of knowledge thrive, then potential knowledge buyers will have no currency valuable enough to tempt them to share their expertise. The knowledge market won’t operate well.

In order to understand the operations of the knowledge market, we have to look at the players involved:

• Knowledge buyers are people trying to resolve an issue whose complexity and uncertainty precludes an easy answer. They are looking for insights, judgements, and understanding.
• Knowledge sellers are people in an organisation with an internal market reputation for having substantial knowledge about a process or subject. One of the challenges of knowledge management is to ensure that knowledge sharing is rewarded more than knowledge hoarding.
• Knowledge brokers (gatekeepers, boundary spanners) make connections between buyers and sellers.

For the knowledge market to operate, mutual trust must be established in a visible and ubiquitous manner. The knowledge market – with no written contracts and no court of appeals – is very much based on credit instead of cash. What is more, trustworthiness must start at the top.

Knowledge market signals indicate both where knowledge actually resides in the organisation and how to gain access to it. There are formal market signals like position and education of potential sellers, but informal signals are generally more accurate guides to where knowledge can be “bought”. For example, informal networks are probably the best market signals. As informal networks consist of people continually in communication with one another, they tend to update themselves as conditions change. The updating process is called gossiping. In comparison, more formal systems, such as electronic repositories of employee skills and interest, begin to get stale as soon as they are established.

Communities of practice are a more focused version of an informal network, and managers should regard them as company assets and look for ways to preserve them. For example reengineering can discourage the conversations and self-forming groups in which so much of the firm’s knowledge work is done.

In practice, efficient markets generate the most good at the least cost. Markets for knowledge, however, are notably inefficient in most organisations. Much of the current interest in knowledge management derives from the fact that organisations lack good information about where their knowledge is and therefore have difficulty getting it and making use of it. Three factors in particular often cause knowledge markets to operate inefficiently:

• Time zone shifting, where the resource of time seems to expand or shrink at will.
• Incompleteness of information: For example lack of maps etc. to guide buyers to sellers, and absence of explicit pricing structure.
• Asymmetry of knowledge: A certain amount of asymmetry is needed in any market, but strong asymmetry prevents knowledge from getting where it is needed.
• Localness of knowledge: Market depends on trust, and individuals generally trust the people they know. Face-to-face meetings are often the best way to get knowledge. Also, mechanisms for getting access to distant knowledge tend to be weak or nonexistent.

3. Knowledge Generation

There are five modes of knowledge generation that cover both knowledge acquired by an organisation as well as that developed within it:

Acquisition means that knowledge does not have to be newly created, only new to the organisation. For example British Petroleum gives a “Thief of the year” award to the person that has “stolen” the best ideas, and Texas Instruments has a corresponding “Not Invented Here, but I Did It Anyway” award. The most direct and often most effective way to acquire knowledge is to buy it – to buy an organisation or hire individuals that have it. But attempts to devise formal measures to guide knowledge purchases have so far been imperfect and incomplete and the purchaser may end up with only a fraction of the knowledge that existed before the sale. Many of the people whose knowledge makes the purchased organisation work are not often identified or officially responsible for the results that they achieve. The knowledge you think you’re buying may walk out the door.

Rental means that outside knowledge can be leased or rented, for example by providing financial support to an university or research institution in exchange for the right to first commercially use promising results. Renting knowledge really means renting a knowledge source, for example a consultant. One should just make certain that a considerable portion of the rented knowledge is retained, too.

Dedicated Resources a units or groups established specifically for knowledge generation: R&D departments, centres for business, innovation, etc. Because dedicated knowledge resources are by definition somewhat distinct from the everyday work, transferring knowledge to where it can be used is often complicated.

Fusion brings together people with different perspectives to work on a problem or project. But while chaos and complexity can create new synergies, total chaos is not creative, though. Group members must developed enough of a common language to understand one another. In addition, the group has to be aware of the value of the knowledge sought.

Adaptation if brought about by external (and internal) changes. Some companies even try to instil a sense of artificial crisis in order to foster continuous innovation. A firm’s ability to adapt is based on two principal factors: Having existing internal resources and capabilities that can be utilised in new ways and being open to change or having a high “absorptive capacity”.

Networks, communities of knowers, brought together by common interests, informal, selforganising networks within organisation generate knowledge, and may over time become more formalised. In the absence of formal knowledge policies and processes, networks act as critical conduits for more innovative thinking.

The common denominator for all these efforts is a need for adequate time and space devoted to knowledge creation and acquisition. In some instances, the shared space may be electronic, but meeting places of some kind must exist. Unfortunately, time, not space, is the resource most likely to be begrudged to knowledge activists. The third critical factor is a recognition by managers that knowledge generation is both an important activity for business success and a process that can be nurtured.

What is more, Kanouse and Jacoby’s words should be heeded: “There are good reasons to believe that behaviour change is a much rarer event than acquisition of knowledge.

Velocity of knowledge transfer is the speed with which knowledge moves through an organisation. Viscosity refers to the richness of the knowledge transferred.

It is time for firms to shift their attention from access to attention, from velocity to viscosity, from documents to discussions.

6. Knowledge roles and skills

Despite the corporate mantra that employee knowledge is a valuable resource, most firms do not make concerted efforts to cultivate the knowledge-oriented activities of their personnel. Ultimately, managers and workers, who do not do knowledge management for a living have to do the bulk of the day-to-day activities of knowledge management, it is to succeed.

There are four levels of knowledge management roles: line workers who must also manage knowledge within their own jobs; knowledge management workers; knowledge project managers; and the senior knowledge executive.

Instead of technologists, the most intriguing new knowledge jobs are integrators, librarians, synthesisers, reporters, and editors. Few organisation have many workers who are skilled at framing and structuring their own knowledge; even fewer of them have tome to sit down and input it into a system. Thus, organisations need people who will extract knowledge from those who have it, put it in structured form, and maintain or refine it over time.

Good knowledge workers at any level should have a combination of “hard” skills (structured knowledge, technical abilities, and professional expertise) with “softer” traits (a sure sense of the cultural, political, and personal aspects of knowledge). The human resource issues, – setting up structures for the development and maintenance of knowledge bases – are more difficult to create and manage.

Knowledge initiative managers should have facility in project management, change management, and technology management. But managing knowledge projects isn’t just about project management. The role demands an unusual mix of technological, psychological , and business skills. They also need a certain humility so that they understand that they must not become the primary source and arbiter of particular knowledge for the organisation.

The chief knowledge officer in an organisation must:

• Advocate for knowledge and learning from it.
• Design, implement, and oversee a firm’s knowledge infrastructure.
• Manage relationships with external providers of knowledge.
• Provide critical input to the process of knowledge creation and use around the firm.
• Design and implement a firm’s knowledge codification approaches.
• Measure an mange the value of knowledge.
• manage the organisation’s professional knowledge managers.
• Lead the development of knowledge strategy.

If you’re thinking you’d like to be a chief knowledge officer (CKO), you should have:

• deep experience in some aspect of knowledge management, including its creation, dissemination, or application.
• Familiarity with knowledge-oriented organisations and technologies.
• Display of a high level of “knowledgeability” directly related to one’s professional stature.
• Comfort (and ideally experience) with the primary operational processes of the business.

There are three options for the location of the CKO role in a firm’s organisational chart. It can be a senior stand-alone role, or it can be combined with either the human resources or information systems functions. The stand-alone role is the most desirable situation, as combining knowledge management with other functions is bound to dilute its importance.

If there is one overriding principle to keep in mind, it is that knowledge management roles and responsibilities should be real jobs requiring dedicated resources.

7. Technologies for Knowledge Management

In spite of the fact that knowledge management is much more than technology, so called “techknowledgy” is a part of knowledge management. When Hewlett-Packard information systems managers convened a workshop to discuss knowledge management applications, they were surprised to hear about more than twenty.

Technology’s most valuable role in knowledge management is extending the reach and enhancing the speed of knowledge transfer. Information technology enables the knowledge of an individual or group to be extracted and structured, and then used by other members of the organisation or its trading partners world-wide. Technology also helps in the codification of knowledge and occasionally even in its generation.

While knowledge management is a relatively recent field of study, attempts to use technology to capture and manipulate knowledge have been underway for decades under the name of “artificial intelligence”. The efforts have concentrated on managing narrow domains of knowledge. AI technologies include6: Expert systems, Case-based reasoning and Neural networks.

Since it is the value added by people – context, experience, and interpretation – that transforms data and information into knowledge, it is the ability to capture and manage those human addition that make information technologies particularly suited to dealing with knowledge. Knowledge technologies are more likely to be employed in an interactive and iterative manner than, say, data management technologies. Therefore, the roles of people in knowledge technologies are integral to their success.

A critical differentiating factor is the level of knowledge required to successfully use a particular technology. The other key dimension is the time required to find a knowledge management solution in a particular tool. Some knowledge-work environments allow time for search, synthesis, and reflection; others require real-time or near real-time performance:

One of the best-known approaches to using technology in KM is the repository of structured, explicit knowledge – usually in document form. Lotus Notes and Intranet-based Webs are the two leading toolkits for managing knowledge repositories today. Notes excels at database management, discussion-group creation and management, and replication of databases for remote disconnected use in the field. The Web is ideal for publishing information across multiple types of computer platforms, for multimedia databases, and for displaying knowledge that is linked to other knowledge through hypertext links. In the fairly near future these capabilities will be available in both technologies.

Repositories based on the World Wide Web are rapidly picking up steam. The Web is a very intuitive technology, and deals easily with audio, graphic, and video representations of knowledge. However, if you plan to use Web for knowledge management (particularly the search-and-retrieval of structured, document-based knowledge), don’t think that a Web browser and server software is all you need. A complex suite of tools is necessary to capture the information, to store, and to allow broad access. Another requirement for search-and-retrieval KM is the development of an on-line thesaurus. Searchers will be looking for knowledge using terms that you can’t anticipate. The idea behind a thesaurus is to connect the terms by which you’ve structured the knowledge with the terms employed by the searcher.

The underlying technique for both web and Notes-base knowledge repositories is text search-andretrieval. On the positive side, the knowledge itself typically has plenty of meaningful context that was created by the original author. However, the knowledge in textual databases is indexed on the basis of keywords and their proximity in the text, which are relatively shallow aspects of the knowledge.

Another popular application is the expert locator, which allows users to search through a set of biographies for an expert on a particular knowledge domain.

It should be noted that the emergence of human Internet brokers or librarians would enhance the value of the Internet as a knowledge tool more significantly than the purely technical improvements going on at the moment.

Some organisations have concentrated knowledge domains rather than a community of expert users. This is the best situation for expert systems, which can enable the knowledge of a few experts to be used by a much broader group of workers who need the knowledge. However, it can be difficult to extract knowledge for an expert in the first place. He or she may not know what he or she knows of he or she may not be willing to surrender the knowledge. What is more, as expert systems are difficult to maintain or add knowledge to, the knowledge domain needs to be fairly stable. One study found that only a third of the expert systems developed in the 1980s were still in use by 1992. The systems were abandoned less for technical reason than for organisational ones.

Constraint-based systems capture and model the constraints that govern complex decision making. Because constraint-based systems are usually object-oriented underneath rather than rule-based, they are easier to modify than expert systems; there are no complex interactions to understand and modify.

Case-based reasoning (CBR) applications require someone to input a series of “cases” which represent knowledge about a particular domain expressed as a series of problem characteristics and solutions. CBR works best when you have on or a few experts construct the cases and maintain them over time. There must also be a domain expert who can decide when a new case is worth creating, when an old case has become obsolete, and whether a newly submitted case is actually correct.

A neural network is a statistically oriented tool that excels at using data to classify cases into one category or another. The classifications become more accurate with more cases, and neural nets require a lot of (normally quantitative) data and a high-powered computer. Setting up the analysis and interpreting results can be very tricky, and these systems require a very knowledgeable user, at least to set up the initial model.

8. Knowledge management projects in practice

When people talk about knowledge management, the conversation often devolves into highly abstract and philosophical statements. But there is a real world of knowledge management, too. Knowledge management projects attempt to make practical use of knowledge, to accomplish some organisational objective through the structuring of people, technology, and knowledge content.

Knowledge management project share in common three broad types of knowledge management objectives: attempts to create knowledge repositories, attempts to improve knowledge access, and attempts to improve knowledge cultures and environments. In real life, knowledge management projects are combinations of the different types discussed below.

Many treat knowledge as an “it”, an entity separate from the people who create and use it. A typical goal of such a project is to take knowledge embodied in documents and put it into a repository. The authors have come across three basic types of knowledge repositories:
1. External knowledge (competitive intelligence).
2. Structured internal knowledge (research reports, marketing materials and methods).
3. Informal internal knowledge (discussion databases).

Another type of a project tries to provide access to knowledge or facilitating its transfer among individuals. Where knowledge repositories aim at capturing knowledge itself, knowledge access projects focus on the possessors and prospective users of knowledge. These projects acknowledge that finding the person with the knowledge one needs, and then transferring it from one person to another, can be daunting process.

The last type of project attempts to establish an environment conducive to knowledge management. The projects intend to measure or improve the value of knowledge capital, build awareness and cultural receptivity, change behaviour as it relates to knowledge and improve the knowledge management process. Some firms now treat knowledge as another kind of capital asset.

The primary attributes the authors use to define success in knowledge management:

• Growth in the resources attached to the project, including staffing and budgets.
• Growth in the volume of knowledge content and usage.
• The likelihood that the project will be sustaining beyond a particular individual or two (an organisational initiative, not an individual project).
• Comfort throughout the organisation with the concepts of “knowledge” and “knowledge management”.
• Some evidence of financial return, either for the knowledge management activity itself or for the larger organisation.

1. LEARNING IN ORGANISATIONS

In evaluating knowledge management projects, the authors have observed two degrees of success: The most impressive type involved the fundamental transformation of a company. The other type involved operational improvement limited to a bounded process or function. There were nine factors leading to knowledge project success:

• A knowledge oriented culture: A positive orientation to knowledge, the absence o knowledge inhibitors, and KM fits the culture. Employees may feel that their knowledge is critical to their unique value as an employee and thus their continued tenure in the organisation. A “hero” mentality may respect only individual achievements. Use of existing designs may be viewed as an admission of weakness.
• Technical and organisational infrastructure: Technological infrastructure is the easier of the two to put in place. Building an organisational infrastructure for KM means establishing a set of roles, organisational structures, and skills from which individual projects can benefit.
• Senior management support: Strong support from executives is critical for transformational knowledge projects. Sending out messages to the organisation that KM and organisational learning are critical. Clearing the way and providing funding for infrastructure. Clarifying what type of knowledge is most important to the company.
• A link to economics or industry value: The most impressive benefits involve money saved or earned. Benefit calculations may also be indirect, f.ex. cycle time, customer satisfaction, or even phone calls avoided.
• A modicum of process orientation.
• Clarity of vision and language: The terms used, f.ex. “knowledge” and “organisational learning” are subject to wide interpretation. Clarity of purpose and terminology is critical with any type of organisational change project.
• Nontrivial motivational aids: Motivational approaches for knowledge behaviours should be long-term incentives tied in with the rest of the evaluation and compensation structure.
• Some level of knowledge structure: Because knowledge is naturally fluid and closely linked to the people who hold it, its categories and meaning change frequently. However, if a knowledge repository has no structure at all, it won’t be able to serve its purpose.
• Multiple channels for knowledge transfer: Knowledge should be transferred through multiple channels that reinforce each other (especially when knowledge is transferred between individuals). People exchange knowledge in direct proportion to their level of personal contact. In a “high bandwidth” situation, trust can be established, structures for knowledge can be developed, and difficult issues can be resolved.

Unfortunately the factors that matter most tend to be the factors that are most difficult to develop: culture, human infrastructure, and senior management support. In the knowledge management initiatives the authors have observed, the level of human issues and problems was much higher than for most data or information management projects. Because of the prominent human element in knowledge, a flexible, evolving structure for knowledge is desirable. Furthermore, the motivational factors are critical. Data and information are constantly transferred electronically, but knowledge seems to travel most efficiently through a human network.

Successful knowledge management requires an unusual combination of human, technical, and economic skills.

9. The pragmatics of knowledge management

The good news about knowledge management is that good sense goes a long way:

• The place to start is with high-value knowledge.
• Start with a focused pilot project and let demand drive additional initiatives.
• Work along multiple fronts at once (technology, organisation, culture).
• Don’t put off what gives you the most trouble until it’s too late.
• Get help throughout the organisation as quickly as possible.

Knowledge management is not totally new. It draws from exiting resources that organisations may already have in place. While the ideas of KM are simple, it is the actual implementation that’s the hard part and it may make more sense to turn outside for help in implementation of a KM project than in its design. It is also sensible to look broadly for help inside the organisation. For knowledge management to prosper everyone has to help out.

In knowledge management it is important to start small, actually accomplish something and then trumpet what's been achieved. KM should start with a recognised business problem that relates to knowledge. The most important factors in deciding where to start are the importance of the specific knowledge domain to the firm and the feasibility of the project.

Whenever possible, firms should try to use existing management approaches and tactics as levers to assist in getting going with knowledge management. Many of them have better management of what the organisation knows as an important component.

Most firms make their first move with knowledge management in the domain of technology. They install Notes or an intranet, and then start searching for content to distribute with these tools. However, if you’re implementing new technology just for the purpose of KM, it may be a waste of money. The knowledge behaviours you’re seeking from users of knowledge systems may be slow to emerge. Getting content into those systems can also take a while. Since the market value of, say, a server for a knowledge repository decreases at about 7 percent a month, you may be better of buying the computers and software after you’ve got the other things in place. Unfortunately, it’s usually much harder to get organisational consensus for behaviour change and new roles than it is for technology.

To begin knowledge management with a focus on organisational learning would be a good idea, but firms rarely do so. The concepts and approaches involved may include:

• Thinking about the organisation as a “system”.
• Building and facilitating communities of learning and practice.
• Focusing on issues of personal development and “mastery”.
• Creating less hierarchical, more “self-organising” organisation structures.
• Planning with the use of scenarios.

However, the world of organisational learning places too little emphasis on structured knowledge and the use of technology to capture and leverage it. For example the word “knowledge” is not in the index of Peter Senge’s The Fifth Discipline. Without an approach to managing structured knowledge, organisational learning is too conceptual and abstract to make a long-term difference.

What makes knowledge valuable to organisations is ultimately the ability to make better the decisions and actions taken on the basis of the knowledge. Unfortunately it is difficult to link knowledge to decisions. And even if we are aware of all that is going on in the decision maker’s head, politics may become a problem. Senior managers, in particular, might balk at the idea of examining their decisions in detail to understand what knowledge they applied and how the decision turned out.

The most common pitfalls firms encounter in the knowledge management business include:

• If we build it ... they won’t come. You can buy as many Notes or Netscape licenses as you want – but it doesn’t mean anyone will use or get value out of your investments.
• Let’s put the personnel manual on-line. Simply putting your yawn-inducing paper document tomes on-line will weaken your terminological currency, and should you later decide to put some real knowledge into this repository, no one will notice.
• None dare call it knowledge. The inability to use the word “knowledge” suggests that the senior management doesn’t buy into the big idea behind knowledge management – that what people know and can learn is more valuable than any other business resource.
• Every man a knowledge manager. “So since it’s also everybody’s job to monitor costs and enhance revenues, you’ve also eliminated the finance and accounting organisations?”
• Justification by faith. Faith can get you a long way, but concrete evidence of the worth of what you do saves you when the crunch eventually comes.
• Restricted access. Better access does increase the likelihood that knowledge sources will be consulted, but it does not necessarily mean attention or appetite or affiliation.
• Bottoms Up! For thousands of years knowledge has been strongly associated with hierarchy, and we see no evidence that things are any different today. Knowledge management is a highly political undertaking. You’ll have to tread lightly in giving access to knowledge to those who formerly lacked it, or you will run afoul of someone powerful to whom your KM acitivities are threatening.

(c) Copyright Jyrki J.J. Kasvi
www.knowledge.hut.fi/projects/itss/itssref.html

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