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Why Knowledge Management is a Dirty Word

Why Knowledge Management is a Dirty Word

Why Knowledge Management is a Dirty Word

If ever there was a misunderstood technology, it’s knowledge management (KM). The statistics tell the story and the contradiction of KM.

By Donna Fluss
Customer Interface Magazine

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If ever there was a misunderstood technology, it’s knowledge management (KM). The statistics tell the story and the contradiction of KM. More than 80 percent of KM initiatives fail. This is higher than the dismal 60 percent failure rate of customer relationship management (CRM) projects in general. That KM is still around and keeps being reincarnated shows its durability in theory, if not its practical value. Given the dramatically high failure rates, what is so compelling about KM that visionaries are willing to risk their careers for the potential benefits? The answer is simple. Successful KM initiatives, like Novell’s (see Customer Interface’s December 2001 article, “In the Know.”) can save companies millions of dollars and improve quality.

KM has been around in different forms for more than 20 years, starting with its introduction as a form of Artificial Intelligence (AI). KM technology attempts to emulate cognitive processing and collaboration of knowledge by providing a framework for authoring, collecting, harvesting and sharing information. In its 20 years of existence, KM has been a technology in search of an application, with vendors as yet unable to fully exploit KM’s capabilities in a viable and marketable software product.

In 1998, when Internet-based customer service became a “hot” component of the CRM revolution, the KM vendors thought they had finally found the perfect application for their technology. Web self-help software that identifies and delivers structured data in response to structured questions has emerged as a winning application of KM. Consider this “FAQ on steroids:” a structured search facility takes customers through a series of self-defining questions that ultimately brings up one or more answers.

Unfortunately, the same challenge that has doomed KM initiatives to failure over the past 20 years, the need to collect and maintain the information that is going to be shared, continues to frustrate Web self-help providers. The KM technology and applications available from Web self- help providers are good, but the flaw remains that the answers provided to internal users or external customers are only as good as the information collected and entered into the system. Until someone develops an easy and quick process for accurately anticipating the questions the KM or Web self-help systems will be asked and entering in the correct answers, these systems will continue to disappoint their users and limit the proliferation of KM technology in the market.

KM’s Value Proposition and ROI

Service organizations claim to use Web self-help applications to improve quality by providing an alternative service channel and delivering service when live agents are not available. In reality, the primary objective of Web self-help is to reduce servicing costs by shifting inquiries away from expensive service delivery vehicles involving live assistance. Web self-help applications have, in fact, reduced the cost of service in environments where the questions are predictable and customers are willing to use the Web to find answers. Where Web-self help has been successful the payback has been as quick as three months but is more likely to take up to a year. In all cases, success is dependent on an enterprise’s willingness and ability to identify the questions customers ask most and to keep the answers accurate and up-to-date.

Web self-help does not work well in environments where customer questions are not predictable or conducive to structured searches. Natural language search capabilities, which allow customers to ask free-form questions using conversational English, still elude the market place, in spite of vendors’ claims to the contrary. Industry analysts estimate that it will take three to five years before there are significant breakthroughs in natural language search.

Cultural and Procedural Changes Required

The good news is KM technologies are continually improving. The bad news is technology is not the most important factor in a successful KM implementation. According to Peter Dorfman, founder of Knowledge Farm, a KM consulting company based in Lebanon, NJ, “KM is only marginally about tools. It’s about people, process and content ?? in other words, best practices. You can succeed even if you chose bad tools and fail even if you chose good tools. The real question is have you got the processes right and are the people you depend on to make KM work buying it?”

To succeed with KM initiatives, enterprises must be willing to undergo a cultural and business transformation. Before investing in a KM tool, enterprises must perform a rigorous organizational self-assessment to determine if they are positioned to make the necessary changes. For a typical customer service organization, the implications of moving from traditional servicing to KM-oriented servicing are huge.

The vast majority of customer service organizations reward representatives based on productivity first and quality second. They are motivated to handle as many calls as possible, as quickly as possible. Representatives give a verbal answer to a customer inquiry and move on to the next call. In a KM-empowered world, representatives are required first to look up a question and find the documented answer. If no answer is found, they must determine a resolution and document it by authoring a new KM solution. This increases the average handled time of calls by 100 to 300 percent and increases the cost of servicing. But it also reduces the number of wrong answers and call backs, thereby increasing customer satisfaction. Implementing KM will absolutely improve quality in the long term, but if the short-term cost is greater than the benefits, enterprises are unlikely to invest in it.

The KM Market Place

There are many KM and Web self-help vendors in the market place today, but the majority of these vendors will either be acquired or out of business by the end of 2003. KM and Web self-help applications can contribute significantly to an enterprise’s bottom line by improving productivity, efficiency and quality, but do not add enough perceived value to warrant a stand-alone market. The value of KM and Web self-help increases when these applications are bundled with more complete and functionally rich products, such as customer service and support suites (CSS) or CRM suites. It is expensive to integrate stand-alone KM technology into an existing CRM or CSS suite and therefore vendors who offer suites with integrated KM and Web self-help functionality, will be the winners.

There are three main categories of KM providers:

  • CRM and CSS suite vendors who include Web self-help as a component of the suite. These products are perceived as less mature than the stand-alone providers and not yet functionally competitive but are expected to improve over the next three years. These vendors are: Chordiant, Oracle, PeopleSoft and Siebel.
  • Traditional KM vendors like Primus and ServiceWare who offer feature-rich and mature KM offerings with advanced work flow, authoring, editing and publishing capabilities but whose products are often perceived as expensive, difficult and time-consuming to implement.
  • Web self-help vendors whose products are increasing in popularity because the applications are less expensive and easier to implement and use even though they are less feature-rich than those of the traditional KM providers. These vendors include: Ask Jeeves, Banter, eGain, eShare, Firepond, Island Data Corp., Kana, NativeMinds, RightNow Technologies and Talisma.


Since its inception, the failure of KM implementations has been blamed on the lack of corporate, cultural and procedural change and expertise. In an ideal world and work environment, requiring a business transformation to support new technology would be fine. But reality tells a different story. For KM to become widely adopted, the technology needs to be easy to deploy and use and employees need to see its benefit to them. KM will remain a “dirty” word and continue to fail frequently until the technology becomes so easy to use that it is almost intuitive, rendering cultural change unnecessary.

Web self-help, the most successful application of KM technologies, is maturing at a rapid rate. The reason for its broader acceptance and use is that service and call center employees don’t need to buy into the process for Web self-help applications to be successful (although it does help if they do). Expect to see continuous investments and improvements in these applications and technologies during the next five years.

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