Some business leaders think that knowledge management is too ephemeral. Far from it, says this author, who has a four-stage plan for realizing and measuring the benefits.

While most business leaders appreciate the strategic value of knowledge and the need to manage their knowledge assets, many of them seem unable to derive real benefits from their efforts. There are several reasons for this, including their persistence in viewing knowledge management (KM) as a supply-side issue, namely their belief that the acquisition of the right knowledge automatically produces benefits. Other reasons that benefits don’t materialize include a lack of focus on KM initiatives; a staggering over reliance on technology to provide both the solution and the benefit; structures that are inappropriate for capitalizing on an organization’s knowledge assets; and lastly, a lack of proper ownership.

Using market-tested examples and ongoing research at the Cranfield School of Management, in Bedfordshire, England, this article aims to place the issues in a practical framework that will show how organizations can practise worthwhile KM. Specifically, it proposes the following four-step program to deliver tangible benefits from KM initiatives:

STEP 1: Make KM a demand-led activity keyed to business results.
STEP 2: Focus on those result areas where KM investments will yield the best return.
STEP 3: Ensure that KM initiatives are always constructed and run as benefit-delivery programs, with their success measured as beneficial outcomes.
STEP 4: Manage KM teams.


In a survey carried out by Cranfield School of Management (in conjunction with Xerox and published with the Economist Group in 1998), a majority of senior executives agreed with the sentiment expressed by Lew Platt, the former CEO of Hewlett-Packard: “If only HP knew what HP knows, it could be three times more productive.” While this statement may be true, it cannot be proved until the hidden knowledge is located and used. Nevertheless, this belief has persuaded many senior executives that the acquisition of knowledge is a supply-side task, and that knowledge will enable the organization to perform better almost as a matter of course. The IT industry has vigorously reinforced this perspective with its various “knowledge technology” offerings.

Nearly all KM practitioners have nevertheless asserted that KM must begin at the top of the organization, and that knowledge-sharing begins with a CEO who “walks the talk.” But senior executives are busy people, and if they have, say, appointed a chief knowledge officer and sanctioned a new global intranet, they may conclude, “Why have a dog and bark yourself?” This is especially true if KM is believed to be a supply-side phenomenon.

I suggest that the supply-side approach to knowledge management places too much reliance on hope, or may simply be a cover for laziness. KM is an enabler that can only produce results when managers intervene to capitalize on what it has to offer. Without managerial direction, enablers—especially technological ones—are unlikely to be aligned with the business drivers. There is, for example, substantial anecdotal evidence that organizations are now using intranets just because they can, not because they should (departmental newsletters are a case in point). Another problem, inherent in all supply-side initiatives, is the difficulty of measuring success, since meaningful returns occur on the output side, for example, an increase in customers or market share.

The first step, then, is to focus KM activity on beneficial business results. Figure 1, the DIKAR model, illustrates the required paradigm by tracking the relationship between data, information, knowledge, actions and results.

Figure 1 The DIKAR model (after Venkatraman, 1996).

The conventional way of interpreting the model is to view it from left to right, as a supply-side value spectrum, i.e., to begin with basic data and progress through the stages, each one progressively yielding more value, and culminating in worthwhile business results. The linkages between each of the stages are also important, since they represent activities that increase value (procedures, competencies, etc.). The closer to the data end, the more procedures and technology can operate. Towards the results end, the emphasis is increasingly on people—as individuals, as groups, and as directed by management.

Using the DIKAR model in the left-to-right mode is useful in understanding how business is actually conducted. However, when the organization steps outside “business-as-usual” and sets new targets such as breaking into a new market, the left-to-right reading cannot explain how to achieve that goal. This is because the appropriate DIKAR chain doesn’t exist, although the model can still be helpful if used right to left. In this RAKID direction, a series of knowledge questions are posed: Given our desired results, what actions are needed to achieve them? Given that set of actions, what do we need to know to perform the actions? What knowledge enablers and other resources are needed to plan and execute actions?

Globalization, liberalization, and deregulation have increased the number of companies, products and services competing for customers’ attention, which has in turn made the marketplace a more difficult arena in which to operate. The appropriate response cannot always be to “turn up the wick” on the existing, traditional resources and their deployment, i.e., faster, better DIKAR. Instead, companies have to create new capabilities that will distinguish them from existing or potential competitors, and find ways of making the marketplace aware of them. These capabilities will achieve their intended goals only if management knows how to integrate organizational resources in new value-adding ways (RAKID).

The role of KM is to marshal knowledge and experience in the necessary disciplines, as well as to combine them to form new capabilities valued by the market. The marketplace and the organization’s capabilities therefore become the major factors shaping the KM activity.

Doing new things that competitors find hard to imitate is an area in which KM can really count/make a difference. Conversely, applying KM to established core business processes is unlikely to yield much benefit for the following reasons:

A) Knowledge must already exist about an established process for it to be established. If the organization really doesn’t possess such fundamental knowledge (e.g., through excessive delayering), then it will probably not be long before it ceases to trade.
B) Unless knowledge about an industry core process can be protected in some way, it will soon be copied throughout/by others. The advantage, then, is only temporary.

The guideline, therefore, is to avoid KM initiatives on core processes because the return on investment will be small, zero or temporary. KM can, however, improve business performance by creating knowledge-based feeder processes that generate inputs for the core processes. (see Step 4).


If we accept the need to drive KM from a results perspective, we must then decide which results to aim for, and how we can ensure that KM programs remain focused on the correct set of results. The knowledge model recast in a RAKID form illustrates the steps needed.

Figure 2 The RAKID model – Demand side driven

The second step is to construct the Results -> Actions – > Knowledge trail for your organization. Executives’ judgment and experience play a large part in achieving this, especially in maintaining focus on results that matter. But there are techniques that help to make this step a structured and defensible one. Three useful, overlapping techniques are:

  • Driver Analysis
  • Balanced Scorecard
  • Critical Success Factors

Perhaps the best tactic is to combine these techniques, starting with Driver Analysis. This approach is a knowledge-sharing one itself. A “driver” is defined as, “a view held by senior management as to what is important to the business, in a given time scale, such that changes must occur. In a structured discussion, therefore, executives would agree what is causing the business to have to change: competition, government regulation or stock market opinion.

These causes need to be articulated along with a set of objectives that the executive has determined will address the drivers. For example: “In response to our declining market share (driver), we shall over the next three years (time scale) introduce two new products per year and take at least one major customer from the competition in each of four identified segments of the market (objectives).”

Drivers tend not to go away (e.g., competitor activity), but the objectives can vary because they represent senior management’s choice as to how the drivers might be addressed. For instance, management may choose to regain market share through a program of acquisitions.

If your organization uses the Balanced Score Card (BScC), the objectives derived from driver analysis can be termed “the goals” in the vocabulary of the scorecard. While the BScC articulates goals and measures of success, it does not require a formal statement of the actions needed to reach the goals. Inasmuch as this is a problem, it can be overcome by attaching a set of Critical Success Factors plus corresponding knowledge needs to each goal.

For example, consider a company that is faced with the drivers of losing business accompanied by declining profits, and that sets itself the following objective: “To improve retention of profitable customers and, within two years, avoid any loss of such customers.” The goal and success measures are clear, but in each of the four scorecard sections, actions can be added, such as identifying profitable customers and regularly reporting on business activity with them. These two actions need knowledge/information, that is, an analysis of the financial database (most organizations don’t know who their profitable customers are) and the implementation of an information extraction system for monitoring. Other actions might include assigning account managers to profitable customers and creating account plans for those customers. This could be backed up by a knowledge base on profitable customers and a knowledge-sharing system for the account teams.

Competitiveness: The optimum focus for knowledge management

In the KM survey referred to earlier, executives were asked to reply to the question, “How is KM going to be important for business?” by ranking 11 potential areas (derived from the survey pilot work). The consensus was that KM’s most important use would be in making an organization competitive and profitable. The other areas scored significantly lower, with “increasing revenue” ranked lowest. Subsequent interviews and field observations produced a plausible explanation: The combination of competitiveness and profitability suggests that businesses were looking for high-margin niche markets. To achieve and sustain these, companies must offer something special to customers, whether a product, service or mode of delivery. Developing that offering requires a knowledge of customers and market trends, and an understanding of the organization’s capabilities and how to capitalize on them.

So, knowledge can and should make a difference to competitiveness and profits. How, then, can we manage it to deliver those advantages? The first move is in some ways an easy one: Disregard all other proposals for KM applications until the competition/profit focus has been exhausted. Insist that knowledge teams focus on competitiveness and profitability. Above all, keep the focus demand-led, because this is the area where knowledge is scarce, where things change most, and where the structured leveraging of knowledge delivers most.


The IS Research Centre at the Cranfield School of Management has done extensive research into the benefits that can be realized from investing in information technology. More than 200 U.K. and international organizations have applied these results successfully. The findings are relevant and applicable to investments in KM.

One of the principles that the research uncovered is that, “Performance only improves when people do things differently.” The emphasis on people is deliberate because technology itself cannot deliver any benefits. Technology only enables people to work better, and it is new ways of working that deliver the benefits. Rephrasing the principle for KM, “Knowledge is only valuable when the recipient works in a new way that delivers benefits to the business.” The recipient may be an individual or an organizational unit, but the principle stands firm: It is the change in the way business is done that will deliver the benefits. Knowledge can only enable that change.

Thus, there is a two-step causal chain to be implemented. First, we must identify new ways of working that produce the benefits necessary to address the drivers and objectives. The knowledge required is then defined by asking, “What knowledge is needed in order to work in the new way?” Second, the required knowledge will be made available through a combination of technology and organizational enablers (the formation of a team or the formal agreement to share knowledge regularly).

A network can be constructed to link the drivers through the benefits to the knowledge enablers. The advantages are that all investments in technology, organizational change and knowledge management are linked to high-level business objectives. The dependencies of technology and knowledge on one another are also made clear. Ownership is clearer, and since each entry on the network is an improvement (new benefits, new ways of working, new enablers), two key questions can be put forward: “What measures will show that improvement has occurred?” and “Who is the person who will make the improvement happen?” This helps participants to understand the measures of success and establishes accountabilities.


Knowledge exists in three locations: as codified information sets; inside the heads of individuals; and within team groupings. Each location presents a different set of issues for any manager attempting to leverage that knowledge.

The location of knowledge and the consequent management issues

Teams can generate knowledge of a particular kind, that is, the integrated knowledge needed to create capabilities within an organization. Consider the example of Excel Logistics, the U.K.’s largest logistics company, which, while being pre-eminent in supply-chain work, had trouble winning large-scale international tenders. The KM approach used by Excel to redress the situation illustrates the benefits that occur when knowledgeable individuals stop working solely as individuals and work instead as a knowledgeable team.

Consider, then, a team of managers and specialists working together to formulate a bid for a major international contract. The bid is a complex one, involving not just product specialists and dealmakers but also experts in, say, contractual law, international taxation, exporting, global supply chains, complex sourcing and costing. The activities are iterative and complex, since a change in one expert’s input could cause another to revise his/her advice. A successful bid will require more than the sum of the parts; what is needed is the managerial know-how to integrate the expert inputs into a successful bid process. Excel created such a team, initially at some expense, since the expertise required was distributed around the world. Later, when the team had developed a new bid process, it deployed technology to maintain contact.

Organizations like Excel, that formally develop such capabilities, will win more business. Without institutionalizing such a capability, the organization is likely to respond to potential new business opportunities with a flurry of activity rather than with a coherent business process. In the bid-as-an-activity-set approach, knowledge resides in discrete packages within an expert’s domain, for example, tax law. In the bidding-as-business-process approach, formal attempts are made to retain the knowledge of how to integrate the contributions for a successful bid. Even if the bid is lost, learning will occur and subsequent bidding will improve. In a team, or similar virtual organizational unit, the management issues are ownership, process, roles, knowledge-sharing and trust. Until the people and process factors are addressed, the use of technology is a secondary consideration.


From the work done at Cranfield, a distinct pattern has emerged which has been termed Feeder Processes, structured activity sets that sustain the core business process. An analogy is the relationship between a river and its tributaries. As long as the tributaries supply fresh, oxygenated water, the river can continue to function as an ecosystem and a transport system.

Feeder processes conform to the RAKID approach. One pharmaceutical organization, faced with increasing demands on its R&D pipeline, has elevated “Licensing In” to a strategic position in its portfolio of development activities; it has accomplished this by setting up a proactive global feeder process. This contrasts with the previous case-by-case reactive process.

Characteristics of knowledge feeder processes are:

  • Unlike the core processes, feeder processes do not generate income; they create inputs to the core processes.
  • They involve the concurrent application of a range of knowledge and expertise, accompanied by iterative interaction with the outside world, usually in a compressed time scale.
  • The interaction of the expertise can be complicated; even language may be an issue, with each specialist using his or her own vocabulary.
  • Feeder processes work best when they are a team or community activity backed up by document management and workflow.
  • Typically, these feeder processes are not viewed by the organization as a process at all, but rather as a set of activities that people from several functions “just get on and do,” so ownership is not as clear as it should be.

The characteristics above indicate that some difficulties must be overcome, especially the last one: ownership. Any organization that solves these issues possesses a hard-to-copy capability.

This article has argued for a top-down approach to KM, treating it like any other serious investment program and applying proven business approaches and techniques. Above all, it demonstrates the need to locate KM to best effect: as a demand-led activity focused on improving competitiveness, which is the source of the best returns on investment. KM is unlikely to improve existing processes significantly. That is because KM already exists within these processes; it just hasn’t yet been identified explicitly as KM. Improvements in supply-side issues and administrative functions are best dealt with by more traditional methods.

This article has also stressed that KM initiatives can no longer be treated as acts of faith, but must be managed as a soundly argued, benefits-driven set of change programs. We have suggested some tools to achieve that goal. Finally, we have pointed out that at the very core of successful knowledge management one finds competent professionals managing smoothly running processes.