Section 12.2: Full Text
Structured Knowledge Systems
Semistructured Knowledge Systems
Knowledge Network Systems
Window on Management
Supporting Technologies: Portals, Collaboration Tools, and Learning Management Systems

ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS

Figure 12-4 provides an overview of the technologies and capabilities found in enterprisewide knowledge management systems. They include capabilities for storing both structured and unstructured data; tools for locating employee expertise within the firm; and capabilities for obtaining data and information from key transaction systems, such as enterprise applications and from Web sites. They also include supporting technologies such as portals, search engines, and collaboraton tools (including e-mail, instant messaging, and groupware) to help employees search the corporate knowledge base, communicate and collaborate with others inside and outside the firm, and apply the stored knowledge to new situations. Systems for managing employee learning are emerging as another supporting technology for enterprise-wide knowledge management.


FIGURE 12-4 Enterprise-wide knowledge management systems

Enterprise-wide knowledge management systems use an array of technologies for storing structured and unstructured documents, locating employee expertise, searching for information, disseminating knowledge, and using data from enterprise applications and other key corporate systems.


           Managers and firms must deal with many different kinds of knowledge and knowledge issues. There are three major categories of enterprise-wide knowledge management systems for dealing with these different kinds of knowledge. Some knowledge exists already somewhere in the firm in the form of structured text documents and reports or presentations, and the central problem is organizing this existing structured knowledge into a library and making it accessible throughout the firm. We will call this type of knowledge structured knowledge, and we can refer to these types of systems as structured knowledge systems.

           The first knowledge management systems that appeared in the late 1980s and 1990s focused on this type of knowledge. Managers may also need information that may exist somewhere inside the firm in the form of less-structured documents, such as e-mail, voice mail, chat room exchanges, videos, digital pictures, brochures, or bulletin boards. We can call this knowledge semistructured knowledge, and we can refer to the systems that focus on this type of knowledge as semistructured knowledge systems (the industry name is digital asset management systems).

           Systems for structured and semistructured knowledge function as knowledge repositories. A knowledge repository is a collection of internal and external knowledge in a single location for more efficient management and utilization by the organization. Knowledge repositories provide access through enterprise portals and search engine technology and may include tools for accessing information from corporate databases.

           In still other cases there are no formal or digital documents of any kind, and the knowledge resides in the heads of experienced employees somewhere in the company. Much of this knowledge is tacit knowledge and is rarely written down. Here, the problem faced by managers is building a network that connects knowledge demand with knowledge supply. Knowledge network systems, also known as expertise location and management systems, attempt to perform this function. Knowledge network systems provide an online directory of corporate experts in well-defined knowledge domains and use communication technologies to make it easy for employees to find the appropriate expert in a company. Some knowledge network systems go further by systematizing the solutions being developed by experts and then storing the solutions in a knowledge database as a best practices or frequently asked questions (FAQ) repository.

           Table 12-2 compares the major categories of enterprise-wide knowledge management systems.

TABLE 12-2 Categories of Enterprise-Wide Knowledge Management Systems

 

Structured Knowledge Systems

Structured knowledge is explicit knowledge that exists in formal documents, as well as in formal rules that organizations derive by observing experts and their decision-making behaviors. The essential problems of structured knowledge are the creation of an appropriate database schema that can collect and organize the information into meaningful categories and the creation of a database that can be easily accessed by employees in a variety of situations. Once the schema is created, each document needs to be “tagged,” or coded, so that it can be retrieved by search engines. Structured knowledge systems perform the function of implementing the coding schema, interfacing with corporate databases where the documents are stored, and creating an enterprise portal environment for employees to use when searching for corporate knowledge.

           All the major accounting and consulting firms have developed structured document and engagement-based (case-based) repositories of reports from consultants who are working with particular clients. The reports typically are created after the consulting engagement is completed and include detailed descriptions of the consulting objective, participants, and the practices used to achieve the client’s objectives. These reports are placed in a massive database to be used later for training new consultants in the company’s best practices and for preparing new consultants joining an existing on-site consulting team. Accounting firms, for instance, have created large tax law accounting databases that store information on tax policy, the application of that policy to specific client companies, and the advice of in-house tax experts on how local laws work.

           Perhaps one of the largest private-sector structured knowledge repositories is KPMG’s KWorld. KPMG International is an international tax and accounting firm with 95,000 professionals serving clients through 1,100 offices in 820 cities and 150 countries (KPMG, 2003a). With such a large global base of employees and clients, KPMG faced a number of problems in sharing knowledge, preventing the loss of knowledge as consultants retired or left the firm, disseminating best practices, and coping with information overload of individual consultants.

           In 1995, KPMG began developing a Web-based knowledge environment known as “Knowledge Web,” or KWeb. KWeb contained databases organized around internal and external knowledge domains of interest to its consultants and partners. In 1999, KPMG rolled out an extension of KWeb called KWorld, which features an integrated set of knowledge content and collaboration tools that can be used worldwide. Figure 12-5 provides an abstract overview of the complex nature of knowledge stored by KWorld.

FIGURE 12-5 KWorld’s knowledge domains
KPMG’s KWorld is organized into nine levels of content that are further classified by product, market segment, and geographic area.


           KWorld is an online environment for gathering, sharing, and managing knowledge. Although it is primarily a document repository, KWorld also provides online collaboration capabilities for the firm’s consultants and an internal reporting system. KWorld stores white papers, presentations, best practice proposals, articles, presentations, internal discussions, marketing materials, engagement histories, news feeds, external industry research, and other intellectual capital. The content is organized into nine levels by KPMG products and market segments. Within each of these domains are many subcategories of knowledge. For instance, the client knowledge domain includes entries on financials, industry dynamics, change dynamics, client organization, client products and customers, and KPMG’s history of engagements (KPMG, 2003). Consultants use KWorld to coordinate their work as a team with a client, and the client is allowed access to the collaboration environment as well. Figure 12-6 illustrates the system processes used by KPMG to capture and organize content for this system.


FIGURE 12-6 KPMG knowledge system processes

KPMG systems classify, filter, and organize content from both internal and external sources for use internally in KWorld and externally on the company Web site.


           KPMG has invested heavily in organizational and management capital required to make use of the millions of documents stored in KWorld. KPMG has created a division of knowledge management, headed by a chief knowledge officer. An extensive staff of analysts and librarians assesses the quality of incoming information, ensures its proper categorization, assesses its value, and provides some analysis of its importance.

           Another example of a structured knowledge system is Roche Labs’ Global Healthcare Intelligence Platform, which integrates documents from multiple sources to provide its professional services group with up-to-date information and expertise relating to new Hoffman-La Roche pharmaceutical products. The system gathers relevant information from global news sources, specialty publishers, health care Web sites, government sources, and the firm’s proprietary internal information systems, indexing, organizing, linking, and updating the information as it moves through the system. Users can search multiple sources and drill down through layers of detail to see relationships among pieces of data.
 

Semistructured Knowledge Systems

Semistructured information is all the digital information in a firm that does not exist in a formal document or a formal report that was written by a designated author. It has been estimated that at least 80 percent of an organization’s business content is unstructured—information in folders, messages, memos, proposals, e-mails, graphics, electronic slide presentations, and even videos created in different formats and stored in many locations. In many cases firms have no idea what semistructured content has been created, where is stored, or who is responsible for it.

           It might be convenient or cost effective not to know this information, but increasingly this is not legal or effective under the influence of laws such as the Sarbanes-Oxley Act of 2002, which requires financial services firms to keep records on the origins of all material corporate documents, including e-mails, brochures, and presentations, and strict internal controls governing their storage. The health care industry in the United States has been similarly impacted by the Health Insurance Portability and Accountability Act (HIPAA) of 1996, which requires health care providers and insurers to track the flow of personal health information meticulously.

           Firms such as Coca-Cola need to keep track of all the images of the Coca-Cola brand that have been created in the past at all their worldwide offices both to avoid duplicating efforts and to avoid variation from a standard brand image. Without the appropriate tools, a firm may have thousands of content centers located in offices around the world where employees often know only about the materials they create themselves. Searching across departments and offices—from corporate legal to technical engineering to customer correspondence to records, or from New York to London to Tokyo—can be a daunting, if not impossible, task. As a result, semistructured documents are continually reproduced and re-created, knowledge is forever lost, and costs climb ever higher.

           The essential problem faced by managers is building a database and technical infrastructure that can collect such semistructured information and organize it in a coherent fashion. A number of vendors have responded to this need with systems that can track, store, and organize semistructured documents as well as more structured traditional documents.

           One of the largest players in this marketplace is Hummingbird, a Canadian software company specializing in “integrated knowledge management systems” (see Figure 12-7). In addition to providing document management in the form of centralized repositories, Hummingbird’s Business Intelligence module pulls data from the firm’s enterprise systems and makes it available firmwide through a portal. A more recent addition to the product line is a rules-based e-mail management program that automatically profiles incoming and outgoing mail messages using rules developed by line managers.


FIGURE 12-7 Hummingbird’s integrated knowledge management system.

Hummingbird’s enterprise solution combines document management, knowledge management, business intelligence, and portal technologies and can be used for managing semistructured as well as structured knowledge.


           One user of Hummingbird’s enterprise knowledge management system is Hennigan, Bennett and Dorman LLP, a Los Angeles-based law firm. The firm handles many big-name, multiparticipant lawsuits, such as government bankruptcies or institutional shareholder fraud cases. New requests for electronic discovery require a legal team to sift through thousands of electronic messages to search for potential evidence. The firm was inundated with backup tapes of hundreds of thousands of e-mail messages and needed a way to filter that information into something its attorneys could use more easily. The firm implemented Hummingbird’s Enterprise document management system, which automates the capture, manipulation, and distribution of document-based knowledge embedded in e-mail. Instead of sifting through piles of printed copies of e-mails, attorneys can run powerful electronic searches, locating only the e-mails they need for a case and marking them up electronically. The system can also re-create all of the threads of an entire e-mail discussion for attorneys to follow and scan e-mail attachments. Using this system has cut the time to process e-mail in half (Hummingbird, 2003a).

           Another Hummingbird user is Cuatrecasas, a leading Spanish law firm described in the Window on Management. Cuatrecasas implemented Hummingbird Enterprise to provide a standard platform for organizing and managing both structured and semistructured information. Cuatrecasas maintains many offices in many different locations, each previously with its own information systems. The only way information could be shared among offices was by e-mail, and that was also difficult to manage because of version control problems. These problems were solved by adopting a single platform for enterprisewide knowledge management.

ORGANIZING KNOWLEDGE: TAXONOMIES AND TAGGING

One of the first challenges that firms face when building knowledge repositories of any kind is the problem of identifying the correct categories to use when classifying documents. It is, of course, possible simply to “dump” millions of documents into a large database and rely on search engine technology to produce results for users. However, a brute search engine approach produces far too many results for the user to cope with and evaluate.

           Firms are increasingly using a combination of internally developed taxonomies and search engine techniques. A taxonomy is a scheme for classifying information and knowledge in such a way that it can be easily accessed. A taxonomy is like a table of contents in a book or like the Library of Congress system for classifying books and periodicals according to subject matter and author. A business firm can access information much more easily if it devises its own taxonomy for classifying information into logical categories. The more precise the taxonomy, the more relevant are the search results produced by search engines. Once a knowledge taxonomy is produced, documents are all tagged with the proper classification. Generally, Extensible Markup Language (XML) tags are used for this purpose so the documents can be easily retrieved in a Web-based system.

           Products such as ActiveKnowledge (Autonomy Corporation) and Taxonomy (Semio Corporation) attempt to reduce the burden on users by categorizing documents using an existing corporate taxonomy. Such products consider the user’s prior searches, the context of the search term in the document (the relationships between words in a document), related concepts the user may not have entered, as well as keyword frequency and the popularity of the document. The purpose of these newer tools is to increase the probability that the correct response will be in the first 10 results.

           Several tools perform auto tagging and reduce the need for managers to develop their own unique taxonomies. Semio’s Tagger software is a categorization and indexing engine that identifies key phrases in documents, assigns relevance factors to these phrases, and organizes the documents into categories, creating XML-based document tags using rules that users can see and modify. Tagger can access more than 200 different document types stored in legacy, enterprise, or other intranet databases. Users can integrate existing taxonomy categories and add, delete, or merge categories after examining how the system responds. Semio claims that its semiautomatic system can achieve 95 percent of the accuracy obtained by manually reviewing and tagging documents in a fraction of the time required for manual efforts (www.semio.com).

           One user of Semio’s auto-tagging tools is Stanford University’s HighWire Press, which publishes 298 online journals containing more than 12 million articles. When the company expanded its collection in 2001 from 1 million to 12 million articles, it needed a way to automate and expand its indexing process. It also needed to provide researchers with better browsing and searching capabilities to support the discovery of unexpected relationships, to link articles from a variety of disciplines, to identify concepts in articles, and to link these concepts in logical categories. Currently, the system has developed 22,000 categories and more than 300,000 concepts. The system supports 84 million hits each week with a database of 6 terabytes (Semio, 2003). The system requires some active management. HighWire Press reviews its classification scheme every month and makes changes based on user feedback and management insight.
 

Knowledge Network Systems

Knowledge network systems address the problem that arises when the appropriate knowledge is not in the form of a digital document but instead resides in the memory of expert individuals in the firm. According to a survey by KPMG, 63 percent of employees in Fortune 500 firms complain of the difficulty in accessing undocumented knowledge as a major problem. Because the knowledge cannot be conveniently found, employees expend significant resources rediscovering knowledge. An International Data Corporation (IDC) study estimated that the average cost of redundant effort in Fortune 500 companies exceeds $60 million per year per firm (AskMe, 2003a). Figure 12-8 illustrates the problem of “collective ignorance,” a situation in which someone in a firm knows the answer, but that knowledge is not collectively shared.


FIGURE 12-8 The problem of distributed knowledge

In many organizations, essential knowledge is not available even though someone in the firm may have the information. The problem is finding the right person or group.


           Knowledge network systems seek to turn tacit, unstructured, and undocumented knowledge into explicit knowledge that can be stored in a database. Solutions that are developed by experts and others in the firm are added to the knowledge database. This new knowledge can be stored as recommended best business practices or as an answer in a database of frequently asked questions. Table 12-3 lists some of the key features of enterprise knowledge network systems.

TABLE 12-3 Key Features of Enterprise Knowledge Network Systems

           AskMe, Inc., produces a widely adopted enterprise knowledge network system. Its users include Procter & Gamble and Intec Engineering Partnership, a project management company with more than 500 employees worldwide serving the global oil and gas industry. The software, AskMe Enterprise, enables firms to develop a database of employee expertise and know-how, documents, best practices, and FAQs, and then to share that information across the firm using whichever portal technology the firm has adopted.

           Figure 12-9 illustrates how AskMe Enterprise works. An Intec engineer with a question, for instance, could access relevant documents, Web links, and answers to previous related questions by initiating a keyword search. If the answer could not be found, that person could post a general question on a Web page for categories such as Pipeline or Subsea for other engineers accessing that page to answer. Alternatively, the person could review the profiles of all company engineers with relevant expertise and send a detailed e-mail query to experts who might have the answer. All questions and answers are automatically incorporated into the knowledge database.


FIGURE 12-9 AskMe Enterprise knowledge network system

A knowledge network maintains a database of firm experts, as well as accepted solutions to known problems, and then facilitates the communication between employees looking for knowledge and experts who have that knowledge. Solutions created in this communication are then added to a database of solutions in the form of FAQs, best practices, or other documents.

 


AN ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEM PAYS OFF FOR CUATRECASAS

Cuatrecasas is one of Spain’s largest independent law firms, specializing in all areas of business law, including corporate and finance, litigation, tax, and labor. The firm was founded in 1917 and now has 600 attorneys and 17 offices in the principal cities of Spain and Portugal, New York City, Brussels, and Sao Paulo. Many Cuatrecasas clients are the largest businesses in Spain, and the firm is especially active in foreign investments in Spain and in counseling Spanish companies expanding abroad.

           Cuatrecasas desperately needed to improve collaboration, information exchange, and reuse of knowledge assets among its far-flung employees. Each office had its own file system, so lawyers and other employees had no common medium other than e-mail for searching, accessing, or sharing the firm’s collective knowledge assets. Even information in e-mail could not be used efficiently because of problems with version control. Very few internal announcements documents and other content were published on the firm’s homegrown intranet because the available tools were too difficult to use. The existing infrastructure prevented Cuatrecasas from effectively creating online communities where attorneys could obtain information about best practices.

           In May 2002, Cuatrecasas chose Hummingbird Enterprise portal and knowledge management solutions. Hummingbird provided a broad range of capabilities, could be implemented in a relatively short period of time, and allowed for ongoing customization. Cuatrecasas started with two pilot projects with a select group of end users in March 2002. The firm’s information systems team spent the period from April through June defining user profiles and standardizing taxonomies for classifying information. By mid-January 2003, nearly 1,000 Cuatrecasas employees in 10 global offices had been trained to use the system.

           Cuatrecasas used Hummingbird to create a standardized platform for centralized document management, collaboration, and information sharing using a single Web-based desktop interface. Employees across all global office locations—but especially attorneys and administrative assistants—can easily and rapidly locate and share information and reuse best practices, regardless of where they work. The new system helped Cuatrecasas reduce the time formerly spent on document management by 10 percent.

           The firm can publish nearly three times as much content as in the past and it can publish this volume of content three to four times more rapidly than before. Publishing the same volume and quality of content with the same speed would have required one full-time dedicated information systems employee, so Cuatrecasas saved $50,000 annually with its new publishing capability.

           Standardizing on a single knowledge management platform has reduced infrastructure costs. Current Cuatrecasas offices have been able to reuse file servers that were formerly required to support disparate file systems. Some of these file servers can be deployed in new offices that the firm expects to open over the next three years. Cuatrecasas can also save on its costs for information systems staff. Before Hummingbird was implemented, information systems personnel spent almost 10 percent of their time maintaining disparate file systems and infrastructures at individual offices. A standardized system reduced the time that information systems staff had to spend on all of Cuatrecasas’s disconnected systems.

           Cuatrecasas subsequently implemented a client extranet that permits its clients to access and retrieve documents related to their cases electronically without contacting their attorneys’ administrative staff. As use of this extranet expands, the firm anticipates lower administrative costs for client support.

           How much value did Cuatrecasas obtain from its new knowledge management system? Nucleus Research was assigned to find out. Nucleus quantified the benefits provided by the system and Cuatrecasas’s total investment in software, hardware, consulting, personnel, training, and other expenditures over a three-year period. Software costs for the initial Hummingbird licenses and annual license maintenance fees amounted to 42 percent of overall costs. Consulting costs in the first year made up over one-fifth of total costs. Time spent by Cuatrecasas information systems staff on the initial implementation of the system amounted to 15 percent of costs, while hardware costs were only 7 percent of total costs. The remaining costs were for training. Direct and indirect benefits far outweighed the costs of the system, producing a net cash flow after taxes of nearly $700,000 each year.

           Cuatrecasas was able to reduce infrastructure costs by deploying existing hardware and by using Hummingbird publishing capabilities to eliminate the need for a full-time information systems employee. Additional savings came from increased productivity of both users and information systems staff. Users did not need to spend as much time as in the past searching for and sharing documents. Information systems staff no longer had to maintain so many disparate systems. Nucleus did not put a price tag on the decreased administrative costs that the company expects to achieve in the future once its client extranet is widely adopted.

           Nucleus used various capital budgeting models (see Chapter 15) to analyze Cuatrecasas’s return on its Hummingbird knowledge system investment. It found that over a three-year period, the new system produced an annual rate of return on investment (ROI) of 84 percent and achieved a payback of the initial investment in only 1.2 years.

Sources: “A Law Firm’s Nucleus of Knowledge,” KM World, February 2004; and Nucleus Research, “ROI Case Study: Hummingbird Cuatrecasas,” www.hummingbird.com, accessed June 10, 2004.

To Think About: Why would a knowledge management system be especially useful for a law firm such as Cuatrecasas? What problems did the Hummingbird system solve for this firm? How did the Hummingbird system provide value for this company?


 

Supporting Technologies: Portals, Collaboration Tools, and Learning Management Systems

The major commercial knowledge management system vendors are integrating their content and document management capabilities with powerful portal and collaboration technologies. Enterprise knowledge portals provide access to external sources of information, such as news feeds and research, as well as to internal knowledge resources along with capabilities for e-mail, chat/instant messaging, discussion groups, and videoconferencing. Users can, for example, easily add a collection of documents obtained through a portal to a collaborative work space. The Gartner Group consulting firm uses the term Smart Enterprise Suites for this leading-edge knowledge management software.

LEARNING MANAGEMENT SYSTEMS

Companies need ways to keep track of and manage employee learning and to integrate it more fully into their knowledge management and other corporate systems. A learning management system (LMS) provides tools for the management, delivery, tracking, and assessment of various types of employee learning and training. A robust LMS integrates with systems from human resources, accounting, and sales so that the business impact of employee learning programs can be more easily identified and quantified.

           The first learning management systems primarily automated record keeping in instructor-led training. These systems have been enhanced to support multiple modes of learning, including CD-ROM, downloadable videos, Web-based classes, live instruction in classes or online, and group learning in online forums and chat sessions. The LMS consolidates mixed-media training, automates the selection and administration of courses, assembles and delivers learning content, and measures learning effectiveness. If a company had a customer relationship management (CRM) system that kept track of call-handling time, for instance, a sophisticated learning management system might be able to correlate performance data with training data to see whether training correlated with on-the-job performance. Recent versions of learning management systems with open architectures have capabilities for exporting their data to other systems.

           The Window on Organizations describes some of the benefits of learning management systems. Training for combat readiness and for job skills is an essential part of the U.S. Navy’s mission, and it must be conducted on a very large scale in many different settings and locations. Trainees have many different aptitudes, skills, and career paths to be managed. Trainees must be tested before and after they take courses. The Naval Education Training Command was able to implement a single learning management system that could handle all of these requirements.