Journal of Information, Law and Technology

A Stages of Growth Model for Knowledge Management Technology in Law Firms

Petter Gottschalk
Norwegian School of Management BI
Norway
petter.gottschalk@bi.no

This is a refereed article published on: 16 August  2002 

Citation: Gottschalk P, ‘A Stages of Growth Model for Knowledge Management Technology in Law Firms’, The Journal of Information, Law and Technology (JILT) 2002 (2). <http://elj.warwick.ac.uk/jilt/02-2/gottschalk.html>

Abstract
A law firm can be understood as a social community specialising in the speed and efficiency in the creation and transfer of legal knowledge. Knowledge management was introduced to law firms to help them to create, share, and use knowledge more effectively. Information technology can play an important role in successful knowledge management initiatives. In this paper, information technology support for knowledge management is linked to stages of growth. A Stages of Growth model is proposed consisting of four stages. The first stage is end user tools that are made available to knowledge workers, the second stage is information about who knows, the third stage is information from knowledge workers, and the final stage is information systems solving knowledge problems.

Keywords: IS maturity, growth stages, knowledge categories, knowledge levels, knowledge work.

1. Introduction
Knowledge management has long been considered an important approach for law firms in gaining competitive advantage. The role of information technology in knowledge management is increasing, and law firms are applying different kinds of technology to support knowledge management. This article proposes a Stages of Growth model for knowledge management technology in law firms. The model is useful to understand the current stage in a specific law firm, and it is useful to develop strategies for future use of information technology in a law firm.

This article is organised as follows. First, law firms are defined in terms of knowledge organizations.  Next, knowledge management is presented in terms of the knowledge-based view of the firm. In the third section, knowledge categories in law firms are discussed. The role of IT is then discussed, before the Stages of Growth model is presented. Application of the Stages of Growth model to the Knowledge Management Matrix is illustrated as well as links between the Legal Grid and the Stages of Growth model.

2. Law Firms
A law firm can be understood as a social community specialising in speed and efficiency in the creation and transfer of legal knowledge (Nahapiet and Ghoshal 1998). Many law firms represent large corporate enterprises, organisations, or entrepreneurs with a need for continuous and specialised legal services that can only be supplied by a team of lawyers. The client is a customer of the firm, rather than a particular lawyer. According to Galanter and Palay (1991), relationships with clients tend to be enduring. Such repeat clients are able to gain benefits from the continuity and economies of scale and scope enjoyed by the firm.

Lawyers can be defined as knowledge workers. They are professionals who have gained knowledge through formal education (explicit) and through learning on the job (tacit). Often, there is some variation in the quality of their education and learning. The value of professionals’ education tends to hold throughout their careers. For example, lawyers in Norway are asked whether they got the good grade of ‘laud’ (now A), even thirty years after graduation. Professionals’ prestige (which is based partly on the institutions from which they obtained their education) is a valuable organisational resource because of the elite social network that provides access to valuable external resources for the firm (Hitt et al. 2001).

After completing their advanced educational requirements, most law students enter their careers as associates in law. In this role, they continue to learn and thus they gain significant tacit knowledge through learning by doing. Therefore, they bring explicit knowledge derived from formal education into their firms and build tacit knowledge through experience (Hitt et al. 2001).

Most professional service firms use a partnership form of organisation. In such a framework, those who are highly effective in using and applying knowledge are eventually rewarded with partner status, and thus own stakes in a firm. On their road to partnership, these professionals acquire considerable knowledge, much of which is tacit. Thus, by the time professionals achieve partnership, they have built up human capital in the form of individual skills (Hitt et al. 2001).

Lawyers work in law firms, and law firms belong to the legal industry. According to Becker et al. (2001), the legal industry will change rapidly because of three important trends. First, global companies increasingly seek out law firms that can provide consistent support at all business locations and integrated cross-border assistance for significant mergers and acquisitions as well as capital-market transactions. Second, client loyalty is decreasing as companies increasingly base purchases of legal services on a more objective assessment of their value, defined as benefits net of price. Finally, new competitors have entered the market, such as accounting firms and Internet-based legal services firms.

Montana (2000) is not convinced that law firms will change, arguing that law stands out as an anachronism in the age of knowledge management. Law is entirely man-made; there are no hidden physical principles. A person researching some question of law ought to be able to quickly and easily derive an answer with certainty. According to Montana (2000), nothing is further from the truth.

The entire body of law is an accumulated historical knowledge without organisation. Law is a conservative calling steeped in its own traditions. Montana (2000) predicts that little will happen because of the obstacles posed by expectations, cost, training and vested interests.

Both Becker et al. (2001) and Mountain (2001) believe that law firms will have to change. Mountain (2001) has addressed the question why law firms ought to invest in online legal services when studies to date show that there is no correlation between law firm technology and profitability. He argues that legal web advisors are a disruptive technology that law firm competitors, such as accounting firms, dot-coms, and corporate clients, are beginning to harness to erode law firm margins.

All authors seem to agree that the competitive strength of a law firm comes from knowledge. Knowledge is a renewable, reusable and accumulating resource of value to the firm when applied in the production of legal services. Furthermore, all authors seem to agree that knowledge management can be improved in law firms, and that information technology can be an enabler of knowledge management improvement in law firms.
3. Knowledge Management
A new perspective on knowledge in organisations is being created. Organisations are viewed as bodies of knowledge, and knowledge management is considered an increasingly important source of competitive advantage for organisations. This article applies the knowledge-based view of the firm that has established itself as an important perspective in strategic management. This perspective builds on the resource-based theory of the firm. According to this theory, performance differences across firms can be attributed to the variance in the firms’ resources and capabilities.

The knowledge-based view argues that the products and services produced by tangible resources depend on how they are combined and applied, which is a function of the firm’s know how. This knowledge is embedded in and carried through individual employees as well as entities such as organisation culture and identity, routines, policies, systems and documents. The knowledge-based view of the firm posits that these knowledge assets may produce long-term sustainable competitive advantage for the firm because knowledge-based resources are socially complex to understand and difficult to imitate by other firms (Alavi and Leidner 2001).

Knowledge cannot be stored in computers; it can only be stored in the human brain. According to Fahey and Prusak (1998), knowledge is what a knower knows; there is no knowledge without someone knowing it. Knowledge is information combined with experience, context, interpretation, reflection, intuition and creativity. Information, which can be stored in computers, becomes knowledge once it is processed in the mind of an individual. This knowledge then becomes information again once it is articulated or communicated to others in the form of text, computer output, spoken words, or written words or other means. Six characteristics of knowledge distinguish it from information: knowledge is a human act, knowledge is the residue of thinking, knowledge is created in the present moment, knowledge belongs to communities, knowledge circulates through communities in many ways, and new knowledge is created at the boundaries of old.

Our concern with distinctions between information and knowledge is based on real differences as well as technology implications. Real differences between information and knowledge do exist, although for most practical purposes these differences are of no interest at all. Information technology implications are concerned with the argument that computers can only manipulate electronic information, not electronic knowledge. Business systems are loaded with information, but without knowledge.

Knowledge management was introduced to the business world to help companies create, share, and use knowledge more effectively. Knowledge management (KM) can be defined as a method to simplify and improve the process of sharing, distributing, creating, capturing and understanding knowledge in the company. KM is description, organisation, sharing and development of knowledge in the firm. KM is managing knowledge-intensive activities in the firm. KM is a discipline focused on systematic and innovative methods, practices, and tools.

Distinctions can be made between core, advanced and innovative knowledge. These knowledge categories indicate different levels of knowledge sophistication. Core knowledge is that minimum scope and level of knowledge for daily operations, while advanced knowledge enables a firm to be competitively viable, and innovative knowledge is the knowledge that enables the firm to lead its industry and competitors (Tiwana 2000):

•	Core knowledge is the basic knowledge required to stay in business. This is the type of knowledge that can create efficiency barriers for entry of new companies, as new competitors are not up to speed in basic business processes. Since core knowledge is present in all existing competitors, the firm must have this knowledge even though it will provide the firm with no advantage that distinguishes it from its competitors. In a law firm, examples of core knowledge include knowledge of the law, knowledge of the courts, knowledge of clients and knowledge of procedures.

•	Advanced knowledge is what makes the firm competitively visible and active. Such knowledge allows the firm to differentiate its products and services from that of a competitor through the application of superior knowledge in certain areas. Such knowledge allows the firm to compete head on with its competitors in the same market and for the same set of customers. In a law firm, examples of advanced knowledge include knowledge of law applications, knowledge of important court rulings and knowledge of successful procedural case handling.

•	Innovative knowledge allows a firm to lead its entire industry to an extent that clearly differentiates it from competition. Such knowledge allows a firm to change the rules of the game by introducing new business practices. Such knowledge enables a firm to expand its market share by winning new customers and by increasing service levels to existing customers. In a law firm, examples of innovative knowledge include knowledge of standardised repetitive legal cases, knowledge of successful settlements and knowledge of modern information technology to track and store vast amounts of information from various sources.

4. Law Firm Knowledge
Classification of knowledge into categories and dimensions may depend on industry. For example, there are likely to be different knowledge categories in a bank compared to a law firm. At the same time, there will be certain generic knowledge categories such as market intelligence and technology understanding in most companies independent of industry. When classifying knowledge in a firm, it is important to do the analysis without the organization chart. If you classify knowledge into technology knowledge, production knowledge, marketing knowledge and financial knowledge, it may be because the firm according to the organization chart consists of a development department, production department, marketing department and financial department. It might be more useful to introduce new knowledge categories such as product knowledge, which includes knowledge of development, production, marketing and finance. By identifying cross-sectional knowledge categories and dimensions, solutions for improved knowledge flows in the organization will emerge.

A law firm is a good example. A law firm is organized according to legal disciplines. Some lawyers work in the tax department, while others work in the mergers and acquisitions department. The types of knowledge involved in the practice of law can be categorized as administrative, declarative, procedural and analytical (Edwards and Mahling 1997):

•	Administrative knowledge, which includes all the nuts and bolts information about firm operations, such as hourly billing rates for lawyers, client names and matters, staff payroll data, and client invoice data.

•	Declarative knowledge, which is knowledge of the law, the legal principles contained in statutes, court opinions and other sources of primary legal authority; law students spend most of their law school time acquiring this kind of knowledge.

•	Procedural knowledge, which involves knowledge of the mechanisms of complying with the law’s requirements in a particular situation: how documents are used to transfer an asset from Company A to Company B, or how forms must be filed where to create a new corporation. Declarative knowledge is sometimes labelled know-that and know-what, while procedural knowledge is labelled know-how.

•	Analytical knowledge that pertains to the conclusions reached about the course of action a particular client should follow in a particular situation. Analytical knowledge results, in essence, from analysing declarative knowledge (i.e., substantive law principles) as it applies to a particular fact setting.

Classification of knowledge into categories and dimensions has important limitations. For example, the classification into explicit and tacit knowledge may create static views of knowledge. However, knowledge development and sharing are dynamic processes, and these dynamic processes cause tacit knowledge to become explicit, and explicit knowledge to become tacit over time. Tacit and explicit knowledge depend on each other, and they influence each other. In this perspective, Alavi and Leidner (2001) argue that whether tacit or explicit knowledge is the more valuable may indeed miss the point. The two knowledge categories are not dichotomous states of knowledge, but mutually dependent and reinforcing qualities of knowledge: tacit knowledge forms the background necessary for assigning the structure to develop and interpret explicit knowledge.

According to Alavi and Leidner (2001), the linkage of tacit and explicit knowledge suggests that only individuals with a requisite level of shared knowledge are able to exchange knowledge. They suggest the existence of a shared knowledge space that is required in order for individual A to understand individual B’s knowledge. The knowledge space is the underlying overlap in knowledge base of A and B. This overlap is typically tacit knowledge. It may be argued that the greater the shared knowledge space, the less the context required for individuals to share knowledge within the group and, hence, the higher the value of explicit knowledge. For example in a law firm, lawyers in the maritime law department may have a large knowledge space so that even a very limited piece of explicit knowledge can be of great value to the lawyers.

5. Information Technology
Information technology can play an important role in successful knowledge management initiatives. However, the concept of coding and transmitting knowledge in organizations is not new: training and employee development programs, organizational policies, routines, procedures, reports, and manuals have served this function for many years. What is new and exciting in the knowledge management area is the potential for using modern information technology (e.g., the Internet, intranets, extranets, browsers, data warehouses, data filters, software agents, expert systems) to support knowledge creation, sharing and exchange in an organization and between organizations. Modern information technology can collect, systematize, structure, store, combine, distribute and present information of value to knowledge workers (Nahapiet and Ghoshal, 1998).

According to Davenport and Prusak (2000), more and more companies have instituted knowledge repositories, supporting such diverse types of knowledge as best practices, lessons learned, product development knowledge, customer knowledge, human resource management knowledge, and methods-based knowledge. Groupware and intranet-based technologies have become standard knowledge infrastructures. A new set of professional job titles – the knowledge manager, the knowledge coordinator, and the knowledge-network facilitator – affirms the widespread legitimacy that knowledge management has earned in the corporate world.

The low cost of computers and networks has created a potential infrastructure for knowledge sharing and has opened up important knowledge management opportunities. Computational power as such has little relevance to knowledge work, but the communication and storage capabilities of networked computers make it an important enabler of effective knowledge work. Through email, groupware, the Internet, and intranets, computers and networks can point to people with knowledge and connect people who need to share knowledge independent of time and place (Gottschalk 2002).

6. A Stages of Growth Model
To understand how information technology can support knowledge management, a Stages of Growth model is proposed. The purpose of this model is both to be able to understand the current situation in a firm in terms of a specific stage as well as to be able to develop strategies to move to a higher stage in the future.

The first stage is general IT support for knowledge workers. This includes word processing, spreadsheets, and email. The second stage is information about knowledge sources. An information system stores information on who knows what in the firm and outside the firm. The system does not store what they actually know. A typical example is the company intranet. The third stage is information representing knowledge. The system stores what knowledge workers know in terms of information. A typical example is databases such as Lotus Notes. The final stage is information processing. An information system uses information to simulate expert opinions. A typical example is expert systems such as Knowledger. The contingent approach implies that Stage I may be right for one firm, while Stage IV may be right for another firm. Some firms will evolve over time from Stage I to higher stages. A law firm moving from Stage II to Stage III is illustrated in Figure 1.

Figure 1   The Stages of Growth Model for Knowledge Management Technology

Stages of IT support in knowledge management are useful to identify the current situation as well as to plan for future applications in the firm. Let us look more closely at each stage in Figure 1:

I.	End-user tools are made available to knowledge workers. At the simplest stage, this means a capable networked PC on every desk or in every briefcase, with standardized personal productivity tools (word processing, presentation software) so that documents can be exchanged easily throughout a company. More complex and functional desktop infrastructures can also be the basis for the same types of knowledge support. Stage I is recognized by widespread dissemination and use of end-user tools among knowledge workers in the company. For example, lawyers in a law firm will at this stage use word processing, spreadsheet, legal databases, presentation software, and scheduling programs.

II.	Information about who knows what is made available to all people in the firm and to selected outside partners. Search engines should enable work with a thesaurus, since the terminology in which expertise is sought may not always match the terms the expert uses to classify that expertise.

Here we find the cartographic school of knowledge management (Earl 2001), which is concerned with mapping organizational knowledge. It aims to record and disclose who in the organization knows what by building knowledge directories. Often called 'yellow pages,'-, the principal idea is to make sure knowledgeable people in the organization are accessible to others for advice, consultation, or knowledge exchange. Knowledge-oriented directories are not so much repositories of knowledge-based information as gateways to knowledge, and the knowledge is as likely to be tacit as explicit.

One starting approach at Stage II is to store curriculum vitae (CV) for each knowledge worker in the firm. Areas of expertise, projects completed and clients helped may over time expand the CV. For example, a lawyer in a law firm works on cases for clients using different information sources that can be registered on yellow pages in terms of an intranet.  

III.	Information from knowledge workers is stored and made available to all people in the firm and to selected outside partners. Here data mining techniques can be applied to find relevant information and combine information in data warehouses. On a broader basis, search engines are web browsers and server software that work with a thesaurus, since the terminology in which expertise is sought may not always match the terms the expert uses to classify that expertise.

One starting approach at Stage III is to store project reports, notes, recommendations and letters from each knowledge worker in the firm. Over time, this material will grow fast, making it necessary for a librarian or a chief knowledge officer (CKO) to organize it. In a law firm, all client cases will be classified and stored in databases using software such as Lotus Notes.

IV.	Information systems solving knowledge problems are made available to knowledge workers and solution seekers. Artificial intelligence is applied in these systems. For example, neural networks are statistically oriented tools that excel at using data to classify cases into one category or another. Another example is expert systems that can enable the knowledge of one or a few experts to be used by a much broader group of workers who need the knowledge. 

Expert system is an example of knowledge management technology at Stage IV. According to Curtis and Cobham (2002), the short answer is that an expert system is a computerized system that performs the role of an expert or carries out a task that requires expertise. In order to understand what an expert system is, then, it is worth paying attention to the role of an expert and the nature of expertise. It is then important to ascertain what types of expert and expertise there are in business and what benefits will accrue to an organization when it develops an expert system.

For example, a doctor having a knowledge of diseases comes to a diagnosis of an illness by reasoning from information given by the patient’s symptoms and then prescribes medication on the basis of known characteristics of available drugs together with the patient’s history. The lawyer advises the client on the likely outcome of litigation based on the facts of the particular case, an expert understanding of the law and a knowledge of the way the courts work and interpret this law in practice. The accountant looks at various characteristics of a company’s performance and makes a judgement as to the likely state of health of that company (Curtis and Cobham, 2002).

All of these tasks involve some of the features for which computers traditionally have been noted – performing text and numeric processing quickly and efficiently – but they also involve one more ability: reasoning. Reasoning is the movement from details of a particular case and knowledge of the general subject area surrounding that case to the derivation of conclusions. Expert systems incorporate this reasoning by applying general rules in an information base to aspects of a particular case under consideration (Curtis and Cobham, 2002).

When companies want to use knowledge in real-time, mission-critical applications, they have to structure the information base for rapid, precise access. A web search yielding hundreds of documents will not suffice when a customer is waiting on the phone for an answer. Representing and structuring knowledge is a requirement that has long been addressed by artificial intelligence researchers in the form of expert systems and other applications. Now their technologies are being applied in the context of knowledge management. Rule-based systems and case-based systems are used to capture and provide access to customer service problem resolution, legal knowledge, new product development knowledge, and many other types. Although it can be difficult and labour-intensive to author a structured knowledge base, the effort can pay off in terms of faster responses to customers, lower cost per knowledge transaction, and lessened requirements for experienced, expert personnel (Grover and Davenport, 2001).

Expert systems are at stage IV. Stewart (1997) argues for stage II by stating that knowledge grows so fast that any attempt to codify it all is ridiculous; but the identities of in-house experts change slowly. Corporate yellow pages should be easy to construct, but it's remarkable how few companies have done it. A simple system that connects inquirers to experts save time, reduces error and guesswork, and prevents the reinvention of countless wheels.

What could be stored at Stage III, according to Stewart (1997), are lessons learned and competitor intelligence. A key way to improve knowledge management is to bank lessons learned - in effect, checklists of what went right and wrong, together with guidelines for others undertaking similar projects. In the area of competitor intelligence, companies need to organize knowledge about their suppliers, customers, and competitors.

7. Application of the Stages of Growth Model
Information technology can be applied at four different levels to support knowledge management in an organization. At the first level, end user tools are made available to knowledge workers. At the second level, information on who knows what is made available electronically. At the third level, some information representing knowledge is stored and made available electronically. At the fourth level, information systems capable of simulating human thinking are applied in the organization. These four levels are illustrated in Table 1, where they are combined with knowledge management tasks. The entries in the figure only serve as examples of current systems.

LEVELS

TASKS	I
END USER TOOLS	II
WHO KNOWS WHAT	III
WHAT THEY KNOW	IV
WHAT THEY THINK	
Distribute
knowledge	Word Processing
Desktop Publishing
Web Publishing
Electronic Calendars
Presentations	Word Processing
Desktop Publishing
Web Publishing
Electronic Calendars
Presentations	Word Processing
Desktop Publishing
Web Publishing
Electronic Calendars
Presentations	Word Processing
Desktop Publishing
Web Publishing
Electronic Calendars
Presentations	
Share
knowledge		Groupware
Intranets
Networks
E-mail	Groupware
Intranets
Networks
E-mail	Groupware
Intranets
Networks
E-mail	
Capture
knowledge			Databases
Data Warehouses	Databases
Data Warehouses	
Apply
knowledge				Expert systems
Neural networks
Intelligent agents	

Table 1:  Examples of IS/IT at different Knowledge Management Stages

When the Stages of Growth model is applied to the two classifications of knowledge presented earlier, we get the Table 2 below. For example, a law firm can have procedural knowledge at the core, advanced and innovative levels. Also, a law firm can have administrative knowledge not only at the core level, although 'nuts and bolts' knowledge appears to be very much like core knowledge. For example, a law firm can be extremely creative in exploring client relationships using an extranet.

Levels
Categories	Core
Knowledge	Advanced
Knowledge	Innovative
Knowledge	
Administrative
Knowledge				
Declarative
Knowledge				
Procedural
Knowledge				
Analytical
Knowledge				

Table 2:   Knowledge Management Matrix

The knowledge management matrix can first be used to identify the current IS/IT that support knowledge management in the firm as illustrated in Table 3. 

Levels
Categories	Core
Knowledge	Advanced
Knowledge	Innovative
Knowledge	
Administrative
Knowledge	Accounting system
Hours billing
Clients database
E-mail
Word processing
Spreadsheet
Salary system	Competence database
Client firm information
Internet
Intranet	Lawyer statistics	
Declarative
Knowledge	Library system
Electronic law-book
Electronic legal sources	Law database		
Procedural
Knowledge	Case collection
Document standards
Procedural standards
Document examples	Internal databases
Intranet
Public databases		
Analytical
Knowledge	Law interpretations	Groupware		

Table 3:  Knowledge Management Matrix for the Current IS/IT Situation

The placement of items within the various categories may appear at times to be inconsistent. For example, why is the Internet considered to be advanced knowledge? Some may argue that it is core knowledge as Internet access doesn't differentiate a law firm from its competitors any more than does e-mail. The reason for the Internet categorisation is the fact that the Internet provides access to advanced knowledge rather than core knowledge. Each categorisation expresses knowledge access rather than technology sophistication.

Now the knowledge management matrix can be applied to identify future IS/IT as illustrated in Table 4. The systems not only serve as examples; they also illustrate that it is possible to find systems than can support all combinations of knowledge categories and knowledge levels. This figure illustrates both current and future applications of information systems and information technology, enabling a diagnosis of both current and future stage of growth for knowledge management technology in a law firm.  Future applications are in italics.

Levels
Categories	Core
Knowledge	Advanced
Knowledge	Innovative
Knowledge	
Administrative
Knowledge	Accounting system
Hours billing
Clients database
E-mail
Word processing
Spreadsheet
Salary system
Electronic diary 
Electronic reception
Office automation
Message system	Competence database
Client firm information
Internet
Intranet
Videophone
Video conference
Quality system
Financial services
Net agent
Electronic meetings	Lawyer statistics 
Client statistics
Recruiting system
Scanning
Quality assurance
Benchmarking
Customer relationships
Net-based services
Mobile office
Executive information	
Declarative
Knowledge	Library system
Electronic law-book
Electronic legal sources
Document management
Legal databases
Commercial databases	Law database
Electronic library
Extranet
International legal sources	Law change base
Precedents base
Conference system
Intelligent agents
Portals
Work flow systems	
Procedural
Knowledge	Case collection
Document standards
Procedural standards
Document examples
Planning system
Standards archive
Publishing system	Internal databases
Intranet
Public databases
Experience database
Image processing
Document generation
International law base
Public web access	Video registration
Case system
Online services	
Analytical
Knowledge	Law interpretations
Voice recognition
Case interpretations	Groupware
Intelligent agents
Client monitoring
Extranet
Discussion groups
Video conference	Expert register
Expert system
Research reports
Subject database
Data warehouse	

Table 4:  Knowledge Management Matrix for Desired IS/IT Situation

Let us look at one system in a most demanding location, innovative-analytical knowledge. There we find expert system. According to Susskind (2000, p.163), six kinds of expert systems can play an important role in law firms in the future:

•	Diagnostic systems. Those systems offer specific solutions to problems presented to them. From the facts of any particular case, as elicited by such a system, it will analyse the details and draw conclusions, usually after some kind of interactive consultation.
 
•	Planning systems. In a sense, planning systems reason in reverse. For these systems are instructed as to a desired solution or outcome and their purpose is to identify scenarios, involving both factual and legal premises, which justify the preferred conclusion. 

•	Procedural guides. Many complex tasks facing legal professionals require extensive expertise and knowledge that is in fact procedural in nature. Expert systems as procedural guides take their users through such complex and extended procedures, ensuring that all matters are attended to and done within any prescribed time periods. 

•	The intelligent checklist. This category of system has most often been used to assist in auditing or reviewing compliance with legal regulations. Compliance reviews must be undertaken with relentless attention to detail and extensive reference to large bodies of regulations. Intelligent checklists provide a technique for performing such reviews. They formalize the process. 

•	Document modelling systems. These systems – also referred to as document assembly systems – store templates set up by legal experts. These templates contain fixed portions of text together with precise indications as to the conditions under which given extracts should be used. 

•	Argument generation systems. It is envisaged that these systems are able to generate sets of competing legal arguments, in situations when legal resources do not provide definitive guidance. Rather than seeking to provide legal solutions (as diagnostic systems strive to do), argument generation systems will present sound lines of reasoning, backed both by legal authority and by propositions of principle and policy. 

Software and systems suitable for knowledge management in a law firm can now be identified using the knowledge management matrix. In Table 5, examples of software to support systems in Table 4 are listed.

Levels
Categories	Core
Knowledge	Advanced
Knowledge	Innovative
Knowledge	
Administrative
Knowledge	Microsoft Word
Microsoft Excel
Microsoft Outlook
SuperOffice
Timex
Concorde XAL
DBMS
SuperOffice
Microsoft Office
Oracle
Agresso
Powermarkt
Uni økonomi
Datalex
Justice Data Systems
GroupWise
Alta Law Office
ESI Law	Microsoft Access
Lotus Approach
Corel Paradox
Infotorg
IFS
Rubicon
Concorde
K-link
Akelius dokument
Windows NT
Explorer
CheckPoint Firewall
RealMedia
Advisor klient
Completo Advokat
Visma Business Advokat	Intranet
Internet
Extranet
WAP
PDA/Palm
KnowledgeShare
IFS Business performance
Mikromarc 2 statistikk
IFS Front Office
Psion
Nomade
Netscape Netcaster	
Declarative
Knowledge	NorLex
CarNov
RightOn
Lovdata
NORSOK	Lovdata
Celex
BibJure
Shyster
Finder
Prjus
BookWhere	Hieros Gamos
Eudor
Abacus Law
Lawgic
Netmeeting
Lov chat
LegalSeeker
KG Agent
Lotus K-station
Domino Workflow	
Procedural
Knowledge	Jasper
Karnov
Mikas
Aladdin ePaper
Action Request System
DocuShare
CyberWorks Training
Learning Space	Lotus Domino
Domino.Doc
DOCS Open
HotDocs
EUR-Lex
ODIN
eCabinet
Amicus Attorney	Justice
Autonomy
LegalSeeker
Expert Legal Systems
Hieros Gamos
Real Media
	
Analytical
Knowledge	PDA/Palm
Lotus LearningSpace
Lotus Quickplace
Lotus Sametime
IBM Content Manager
IBM Enterprise Portal
Voice Express
Collaborative Virtual Work
Search Sugar
Vchip	Lotus Notes
iNotes
Lotus K-Station
Jasper
Novell GroupWise
Microsoft Exchange
Netscape Communicator
JSF Litigator’s Notebook
Empolis K42
Legal Files	Summation
Knowledger
Lotus Raven
Shyster
XpertRule Miner
Expert Choice
Dragon Dictate	

Table 5:   Knowledge Management Matrix for Software Supporting Desired IS/IT Situation

Let us look at one example in Table 5. Knowledger is listed as a potential software in the innovative-analytical knowledge location. This is an ambitious location for a software product that has yet to demonstrate its real capabilities in knowledge firms. According to the vendor Knowledge Associates, Knowledger 3.0 is a complete knowledge management software that can be integrated with other systems in the firm. Knowledger is web-based and supports the firm in categorizing internal and external information, as well as linking incoming information to existing information.

Let us look at one more application in a most demanding location, innovative-analytical knowledge. There we find Summation. Summation is a system for document handling for use in large court cases. In the large Norwegian Balder court case of 2001, the Thommessen Krefting Greve Lund (TKGL) law firm used Summation. The Balder case is a dispute between Exxon and Smedvig about the rebuilding of an offshore vessel costing 3 billion Norwegian kroner. TKGL had more than 2500 binders when the court case started in the city of Stavanger. All these documents were scanned into a database for use by Summation. When lawyers from TKGL present material in court, they submit it from their laptops. When new information emerges in court, it is registered in Summation. When TKGL lawyers are to trace technical and financial developments for Balder, they make a search in the Summation database.

Another law firm is also using Summation. The law firm Bugge Arentz-Hansen Rasmussen (BA-HR) has the task of locating money left by the late ship owner Jahre. The money is expected to be found in banks in tax havens. The hunt for Jahre funds has been going on for almost a decade, and BA-HR has developed a large Summation database enabling BA-HR lawyers to present important information in the court in the city of Drammen.

A third example of Summation use can be found in the US. The Justice Department used Summation in its legal struggle with Microsoft. According to Summation Legal Technologies, Summation helped the Justice's lead prosecutor, David Boies, piece together the most damaging information against Microsoft. In presenting its defence, which ended on February 26, Microsoft relied more than Justice did on a low-tech overhead projector.

Summation and Knowledger are interesting examples of software for knowledge management in law firms because they are applications at Stage IV of the Stages of Growth model. 

The Stages of Growth model can be applied to the knowledge management matrix as illustrated in Table 6.

  Levels
Categories	Core
Knowledge	Advanced
Knowledge	Innovative
Knowledge	
Administrative
Knowledge	I	I	II	
Declarative
Knowledge	I	I	II	
Procedural
Knowledge	III	III	IV	
Analytical
Knowledge	I	III	IV	

               Table 6:Knowledge Management Matrix applied to Stages of Growth.

IT for administrative core and advanced knowledge as well as IT for declarative core and advanced knowledge is mainly end-user tools at Stage I. IT for administrative and declarative innovative knowledge is mainly for who knows what at Stage II. IT for advanced analytical knowledge is mainly for what they know at Stage III, while IT for innovative analytical knowledge is mainly for what they think at Stage IV.

The classification of each of the twelve matrix elements in Figure 2 can be challenged. The main framework, however, should be agreeable. The main idea says that when a law firm moves from the upper-left corner in the knowledge management matrix to the lower-right corner in the matrix, then the firm evolves through stages of growth in the use of knowledge management technology.

8. Legal Grid and Stages of Growth Model
From an IT-perspective, Susskind (2000) has illustrated how law firm focus can vary as illustrated in Figure 2. He defines a horizontal axis from technology focus to knowledge focus, and a vertical axis from firm focus to client focus. He calls it the legal grid. In each quadrant, IT applications can be identified. Office support systems are technology-oriented applications internal to the firm. Knowledge management systems are knowledge-oriented applications internal to the firm. Legal web advice is knowledge-oriented applications focusing on clients, while customer relationship management is technology-oriented applications focusing on clients.

                     Figure 2:  The Legal Grid for Applications of IT in Law Firms

Susskind (2000) has illustrated how the focus has shifted in law firms as illustrated in Figure 3. Until 1995, law firms were concentrating on office support systems such as accounting and other administrative systems. In 1995, knowledge management became the focus of attention. Soon customer relationship management will emerge, and so will legal web advice. An interesting aspect of this illustration is the link between different parts. One important link is the need for KMS to enable both CRM and LWA. 

Figure 3:  Changing focus over time for Applications of IT in Law Firms

The Stages of Growth model as proposed in this article, is mainly concentrating in the bottom-left quadrant of knowledge management. End-user tools is the starting point for knowledge management, before advancing into information about who knows what. Knowledge management becomes even more advanced in the legal grid quadrant when information from knowledge workers is stored in computer systems. The most advanced stage is occurring when knowledge management in the bottom-left quadrant is at Stage IV by a law firm having information systems solving knowledge problems.

As illustrated in Figure 3, the knowledge management quadrant is very much the attention of this decade. Attention will expand into client-related systems in a few years. This is interesting in the Stages of Growth model perspective, as LWA will be dependent on KMS to be successful.

Dependence of LWA on KMS is visible in anecdotal evidence from current online legal service providers. In Norway, legal web advisors such as Legaliz.no, AdvokatOnline.no, Jusstorget.no and Internettadvokaten.no all struggle to survive. These actors have neither a backbone system in terms of internal knowledge management systems nor backbone staff in terms of a minimum number of lawyers on which web services can be updated and renewed. 

An existing law firm in Norway with typically 50-150 lawyers will have both the knowledge and the resources for knowledge management to develop an internal knowledge management system that can be the foundation for legal web advice. Figure 4 illustrates how the Stages of Growth model can be linked to the Legal Grid.

            

Figure 4: Stages of Growth linking Knowledge Management and Legal Web Advice
9. Validation of the Stages of Growth model
The next stage in this research will be to validate the model. Empirical validation of the Stages of Growth model can be carried out though a survey using a questionnaire as listed in the Appendix. 

In the first part of the survey instrument in the Appendix, there are four research constructs defined, one for each stage. Each construct is measured through a multiple-item scale. Each scale has five items, where the fifth item is a summary item. For each responding law firm, the average value for each level can be calculated. For the whole sample, statistical difference tests such as the t-test can be applied to evaluate whether responding law firms report significant differences between stages. Empirical validation of the Stages of Growth model will be successful if responding law firms have significantly lower scores at higher levels.

In the second part of the survey instrument in the Appendix, the four stages of growth are described in terms of benchmark variables. Benchmark variables indicate the theoretical characteristics at each stage of growth (King and Teo, 1997). For example, firms at Stage I can theoretically be expected to conform to values of benchmark variables listed under Stage I. However, this does not mean that it is not possible for firms at Stage I to have values of benchmark variables applicable to other stages. Rather, it means that the values of benchmark variables indicate the most likely theoretical characteristics applicable at each stage of integration as indicated in Table 7.

No.	Benchmark Variable	Stage I
END USER TOOLS	Stage II
WHO KNOWS WHAT	Stage III
WHAT THEY THINK	Stage IV
HOW THEY THINK	
1	Trigger of IT for KM	Individual lawyer's needs	Organization needs	Organization's goals	Automate lawyers' work	
2	Top management's participation	Seldom	Infrequent	Frequent	Almost always	
3	User participation	Seldom	Infrequent	Frequent	Almost always	
4	Principal contribution	Efficiency of lawyer	Effectiveness of lawyer	Effectiveness of firm	Competitiveness of firm	
5	Technology assessment	Seldom	Infrequent	Frequent	Almost always	
6	Focus	Availability	Reorganization	Culture	Replacement	
7	Dominating statement	Distribute knowledge	Collect information	Produce documentation	Concentrate on work	
8	Critical success factor	PCs and networks	Culture and incentives	Quality and quantity	Artificial intelligence	
9	Philosophy	Independence	Community	Client satisfaction	Client independence	
10	Strategy	Tool strategy	Stock strategy	Flow strategy	Growth strategy	
11	Main task	Distributing	Sharing	Capturing	Applying	
12	Main purpose	Administrative work	Access to information	Sharing information	Automating work	
13	Contribution of IT function	Supplier of PCs	Technical infrastructure	Resource of information	Supplier of systems	
14	Role of IT manager	Technology expert	Functional administrator	Resource manager	Knowledge management expert	
15	Performance of IT function	Operational efficiency	Strategy implementation	Knowledge implementation	Long-term impact	
16	IT manager's participation	Seldom	Infrequent	Frequent	Almost always	
17	Business level	Efficiency-driven	Availability-driven	Effectiveness-driven	Expert-driven	
18	Main effect	Reduced dependence	Effective application	New knowledge	Client performance	
19	Priority in business	Fourth	Third	Second	First	
20	Management agenda	Year	Month	Week	Day	
21	Priority in marketing	Fourth	Third	Second	First	

         Table 7: Typology of Evolutionary Stages of Knowledge Management Technology

There are a total of twenty-one benchmark variables in Table 7. Twelve benchmark variables are concerned with IT in KM, the next four benchmark variables (no. 13-16) are concerned with IT management, while the remaining five (no. 17-21) are concerned with knowledge management in general.

Benchmark variables in Table 7 indicate the theoretical characteristics at each stage of growth. The problem with this approach is that all indicators of a stage may not be present in an organisation, which makes it difficult to place the organisation in any specific stage. Unfortunately, IT factors do not lend themselves to precise Guttman scaling techniques. Guttman scaling is also sometimes known as cumulative scaling or scalogram analysis. The purpose of Guttman scaling is to establish a one-dimensional continuum for a concept to measure. We would like a set of items or statements so that a respondent who agrees with any specific question in the list will also agree with all previous questions. This is the ideal for a stage model - or for any progression. By that we mean that it is useful when one progresses from one state to another state in a manner so that if one is in the later/higher stage, it also indicates that one has all the features of the earlier stage (Trochim, 2002).

In the third part of the survey instrument in the Appendix, the four stages of growth are extensively described, enabling respondents to make an overall judgement of knowledge management technology stage in the firm.

In the fourth part of the survey instrument, a validation check of the paths of evolution is conducted. Respondents are asked to indicate the duration spent at each stage of growth. This is to ensure that respondents do think about paths of evolution (King and Teo, 1997). The duration (number of years) spent at each stage is also measured in the questionnaire.

In the fifth part of the survey instrument, knowledge-sharing perceptions and reward perceptions are measured as defined by Hunter and Beaumont (2002). This is done to evaluate a theoretical proposition that higher stages of growth will have higher knowledge-sharing perceptions and higher reward perceptions.

In the sixth and final part of the survey instrument, strategy and responsibility questions are applied to identify intentions and focus based on content analysis of responses. This is done to evaluate a theoretical proposition that higher stages of growth will be associated with more IT and KM focused strategy statements as well as more IT and KM executives (Hunter and Beaumont, 2002). 

The desired informant for this proposed survey instrument is the chief executive officer (CEO) who can be the managing partner or the managing director in a law firm.

10. Conclusion
A Stages of Growth model is proposed to understand the stage at which at law firm is found concerning applications of information technology in knowledge management. Four stages are defined, and a law firm can use the model to develop a strategy for implementing technology at higher stages in the model.
References
Alavi, M and Leidner, D E (2001), “Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues”, MIS Quarterly, 25 (1), pp.107-136.

Becker, W M; Herman, M F; Samuelson, P A and Webb, A P (2001), “Lawyers get down to business”, The McKinsey Quarterly, 2001 (2), pp.45-55.

Curtis, G and Cobham, D (2002), Business Information Systems: Analysis, Design and Practice, UK: Prentice Hall.

Davenport, T H and Prusak, L (2000), Working Knowledge, USA: Harvard Business School Press.

Earl, M J (2001), "Knowledge Management Strategies: Toward a Taxonomy", Journal of Management Information Systems, 18 (1), pp.215-233.

Edwards, D L and Mahling, D E  (1997), “Toward Knowledge Management Systems in the Legal Domain”, Proceedings of the International ACM SIGGROUP Conference on Supporting Group Work Group ’97, USA: The Association of Computing Machinery ACM, pp.158-166.

Fahey, L and Prusak, L (1998), “The Eleven Deadliest Sins of Knowledge Management”, California Management Review, Spring, pp.9-21.

Galanter, M and Palay, T (1991), Tournament of Lawyers, The Transformation of the Big Law Firm, USA: The University of Chicago Press.

Gottschalk, P (2002), Knowledge Management through Information Technology, Bergen, Norway: Fagbokforlaget publishing, <http://www.fagbokforlaget.no>.

Grover, V and Davenport, T H (2001), “General Perspectives on Knowledge Management: Fostering a Research Agenda”, Journal of Management Information Systems (JMIS), 18 (1), pp.5-21.

Hitt, M A; Bierman, L; Shimizu, K and Kochhar, R (2001), “Direct and moderating effects of human capital on strategy and performance in professional service firms: a resource-based perspective”, Academy of Management Journal, 44 (1), pp.13-28.

Hunter, L and Beaumont, P (2002), "Knowledge management practice in Scottish law firms", Human Resource Management Journal, 12 (2), pp.4-21.

King, WR and Teo, TSH (1997), "Integration Between Business Planning and Information Systems Planning: Validating a Stage Hypothesis", Decision Sciences, 28 (2), pp.279-307.

Montana, J C (2000), “The Legal System and Knowledge Management”, The Information Management Journal, July, pp.54-57.

Mountain, D (2001), “Could New Technologies cause Great Law Firms to Fail?”, Journal of Information, Law & Technology (JILT), issue 1, 9 pages.
<http://elj.warwick.ac.uk/jilt/01-1/mountain.html>.

Nahapiet, J and Ghoshal, S (1998), “Social capital, intellectual capital, and the organizational advantage”, Academy of Management Review, 23 (2), pp.242-266.

Stewart, T A (1997), Intellectual Capital: The New Wealth of Organizations, UK: Nicholas Brealy Publishing.

Susskind, R (2000), Transforming the Law, UK: Oxford University Press.

Tiwana, A (2000), The Knowledge Management Toolkit – Practical Techniques for Building a Knowledge Management System, USA: Prentice Hall.

Trochim (2002),
<http://trochim.human.cornell.edu/kb/scalgutt.htm>.

Appendix
Knowledge Management Technology Survey

What is your job title? ____________________________________________________

How many years have you been with the firm? ______years

How many persons work in the firm?  ______persons

How many lawyers work in the firm?  ______persons

What is the total income budget for the firm this year? ______mill. NOK

What is the total IT budget for the firm this year?  ______mill. NOK

How many persons work in the IT function in the firm?  ______persons

END-USER-TOOL SYSTEMS

To what extent is the following information technology used by lawyers in the firm:	
To a little extent	
To a great extent	
Text processing (e.g., Word)	1    2    3    4    5    6	
Presentations (e.g., PowerPoint)	1    2    3    4    5    6	
Electronic mail (e.g., Notes mail)	1    2    3    4    5    6	
External legal databases (e.g., Lovdata)	1    2    3    4    5    6	
End user tools for lawyers	1    2    3    4    5    6	

WHO-KNOWS-WHAT SYSTEMS

To what extent is the following information technology used by lawyers in the firm:	
To a little extent	
To a great extent	
Groupware for cooperation (e.g., GroupWise, Lotus Notes)	1    2    3    4    5    6	
The firm's intranet	1    2    3    4    5    6	
The firm's own web pages on the Internet	1    2    3    4    5    6	
Internal standards database	1    2    3    4    5    6	
Systems providing information about lawyers' knowledge	1    2    3    4    5    6	

WHAT-THEY-KNOW SYSTEMS

To what extent is the following information technology used by lawyers in the firm:	
To a little extent	
To a great extent	
Groupware for knowledge (e.g., GroupWise, Lotus Notes)	1    2    3    4    5    6	
Database with client cases	1    2    3    4    5    6	
Database with best practices	1    2    3    4    5    6	
Document system (e.g., DocsOpen)	1    2    3    4    5    6	
Systems providing information based on lawyers' knowledge	1    2    3    4    5    6	

WHAT-THEY-THINK SYSTEMS

To what extent is the following information technology used by lawyers in the firm:	
To a little extent	
To a great extent	
Expert system (e.g., Knowledger)	1    2    3    4    5    6	
Neural network system	1    2    3    4    5    6	
Intelligent agent (e.g., Autonomy)	1    2    3    4    5    6	
Case-based reasoning system 	1    2    3    4    5    6	
Systems solving knowledge problems for lawyers	1    2    3    4    5    6	

For each of the following statements, please place one check mark () besides the description that most closely fits the firm. Please choose only one response for each numbered statement. (Even though more than one response may seem appropriate, please select the best statement for the firm). Please also note that none of the descriptions are inherently good or bad.

1. The implementation of information technology for knowledge management is primarily triggered by:
•	(  ) consideration of individual lawyer's needs
•	(  ) consideration of the organization's needs
•	(  ) consideration of the organization's goals
•	(  ) the need to automate lawyers' work

2. Please indicate the frequency of top management's participation in information technology planning for knowledge management:
•	(  ) almost always
•	(  ) frequent
•	(  ) infrequent
•	(  ) seldom

3. Please indicate the frequency of user participation in information technology planning for knowledge management:
•	(  ) almost always
•	(  ) frequent
•	(  ) infrequent
•	(  ) seldom

4. The principal contribution from information technology in knowledge management is:
•	(  ) improved efficiency of individual lawyer's work
•	(  ) improved effectiveness of individual lawyer's work
•	(  ) improved effectiveness of the firm
•	(  ) improved competitiveness of the firm

5. During information technology planning, how frequent is the impact of new knowledge management technologies assessed?
•	(  ) almost always
•	(  ) frequent
•	(  ) infrequent
•	(  ) seldom

6. In applying information technology to support knowledge management, we have the following main focus: 
•	(  ) making information technology available to lawyers
•	(  ) reorganizing the firm for knowledge sharing
•	(  ) creating a culture for knowledge development
•	(  ) replacing lawyers by information technology

7. Please indicate the most dominating statement about knowledge management technology: 
•	(  ) Information technology enables me to distribute information to my colleagues
•	(  ) Information technology enables me to collect information created by my colleagues
•	(  ) information technology enables me to produce comprehensive documentation
•	(  ) information technology enables me to concentrate on interesting work

8. The most critical success factor for information technology in knowledge management is:
•	(  ) availability of PCs and networks
•	(  ) culture and incentives to share knowledge
•	(  ) quality and quantity of available information in databases
•	(  ) availability of artificial intelligence, such as expert systems and intelligent agents

9. Please indicate the main 'philosophy' for knowledge management technology:
•	(  ) our lawyers enjoy independence in time and space, by working when they like (day or night) and where they like (office, home, summerhouse)
•	(  ) our firm is a knowledge community of people with a common interest, problem and experience, designed and maintained for a business purpose 
•	(  ) our clients are satisfied with our work, they have trust and confidence in our professional knowledge
•	(  ) we help our clients solve their problems themselves by making expert knowledge available

10. Please indicate the dominating strategy for knowledge management technology:
•	(  ) tool strategy of enabling lawyers to use PCs
•	(  ) stock strategy of storing whatever documents that are produced in the firm
•	(  ) flow strategy of only storing documents that will be used again in work processes
•	(  ) growth strategy of only storing documents that are related to legal work where we have little experience

11. Presently, the main task of information technology in knowledge management is:
•	(  ) distributing knowledge
•	(  ) sharing knowledge
•	(  ) capturing knowledge
•	(  ) applying knowledge

12. Presently, information technology in knowledge management mainly exists for the purpose of: 
•	(  ) facilitating administrative work processes
•	(  ) providing access to information more efficiently
•	(  ) sharing information more effectively
•	(  ) automating work done by lawyers

13. The information technology function is primarily viewed as:
•	(  ) supplier of PCs and end user tools
•	(  ) developer of technical infrastructure and applications
•	(  ) a resource making information available
•	(  ) supplier of systems that automate legal work

14. The primary role of the information technology manager is:
•	(  ) an information technology expert who knows PCs and IT tools
•	(  ) a functional administrator responsible for providing support
•	(  ) an information resources manager
•	(  ) a knowledge management systems expert

15. The performance criteria for the information technology function are its:
•	(  ) operational efficiency and cost minimization
•	(  ) contribution to business strategy implementation
•	(  ) contribution to knowledge strategy implementation
•	(  ) long-term impact on the organization

16. Please indicate the frequency of the information technology manager's participation in business strategy planning:
•	(  ) almost always
•	(  ) frequent 
•	(  ) infrequent
•	(  ) seldom

17. We are in the business of providing legal advice:
•	(  ) based on efficiency of our lawyers
•	(  ) based on availability of our lawyers
•	(  ) based on effectiveness of our lawyers
•	(  ) based on expert knowledge of our lawyers

18. Knowledge management has the following main effect:
•	(  ) reduced dependence on individual lawyer's knowledge
•	(  ) effective application of current knowledge
•	(  ) development of new knowledge
•	(  ) improved client performance

19. Knowledge management has the following priority in our business strategy:
•	(  ) first priority
•	(  ) second priority
•	(  ) third priority
•	(  ) fourth priority

20. Knowledge management is at the top management agenda:
•	(  ) every day
•	(  ) every week
•	(  ) every month
•	(  ) every year

21. Knowledge management has the following priority in our marketing strategy:
•	(  ) first priority
•	(  ) second priority
•	(  ) third priority
•	(  ) fourth priority

22. The information technology manager is ____level(s) below the managing director.

23. The information technology manager has been with the firm for ____years.

24. The knowledge manager is ____level(s) below the managing director.

25. The knowledge manager has been with the firm for ____years.

Please indicate with one check mark () the description that most closely fits your current projects for information technology to support knowledge management in the firm:

•	(  ) End-user tools will be made available to lawyers. This means a capable networked PC on every desk or in every briefcase, with standardized personal productivity tools (word processing, presentation software) so that documents can be exchanged easily throughout a company. A widespread dissemination and use of end-user tools among knowledge workers in the company is to take place.

•	(  ) Information about who knows what will be made available to lawyers. It aims to record and disclose who in the organization knows what by building knowledge directories. Often called 'yellow pages', the principal idea is to make sure knowledgeable people in the organization are accessible to others for advice, consultation, or knowledge exchange. Knowledge-oriented directories are not so much repositories of knowledge-based information as gateways to knowledge.

•	(  ) Information from lawyers will be stored and made available to colleagues. Here data mining techniques will be applied to find relevant information and combine information in data warehouses. One approach is to store project reports, notes, recommendations and letters from each lawyers in the firm. Over time, this material will grow fast, making it necessary for a librarian or a chief knowledge officer (CKO) to organize it.

•	(  ) Information systems solving knowledge problems will be made available to lawyers. Artificial intelligence will be applied in these systems. For example, neural networks are statistically oriented tools that excel at using data to classify cases into one category or another. Another example is expert systems that can enable the knowledge of one or a few experts to be used by a much broader group of lawyers who need the knowledge. 

As far back as you can recall, please indicate below the evolution of information technology projects for knowledge management in the firm in terms of the duration spent in each type of information technology projects, and the reasons for changing from the previous type of knowledge management technologies. Please use the terms 'not applicable' or 'NA' beside any type of information technology projects that the firm did not experience.

Information technology projects focused on:	Duration
(e.g., 1997-2001)	Reasons for changing from the previous project type to this type	
End-user tools for lawyers, both hardware and software			
Information about who knows what			
Information from lawyers stored and made available			
Information systems solving knowledge problems			

KNOWLEDGE-SHARING PERCEPTIONS

To what extent do you disagree or agree with the following statements about the firm:	
Strongly disagree	
Strongly agree	
Lawyers are encouraged to share with others what they have learned from their recent assignments	1    2    3    4    5	
Senior staff are too busy to reflect on their experiences and share them	1    2    3    4    5	
The firm has a well-organised system for sharing knowledge (e.g. about clients, managing projects, new approaches) within departments or practice areas	1    2    3    4    5	
The firm has a well-organised system for sharing knowledge (e.g. about clients, managing projects, new approaches) across departments or practice areas	1    2    3    4    5	
There is an expectation that lawyers or their teams will have to take a regular turn to provide a reflection on learning experiences	1    2    3    4    5	
Sharing knowledge systematically is part of the firm's culture	1    2    3    4    5	

REWARD ATTITUDES

To what extent do you disagree or agree with the following statements about the firm:	
Strongly disagree	
Strongly agree	
Lawyer salary increases in the firm are based on ability and how well he/she does his/her work	1    2    3    4    5	
Promotion of a lawyer in the firm is based on ability and how well he/she does his/her work	1    2    3    4    5	
Lawyers are fairly rewarded for the amount of effort they put in	1    2    3    4    5	
The interest of the work lawyers do compensates for long hours and a stressful workload	1    2    3    4    5	
The team as a whole is rewarded for good work	1    2    3    4    5	
Teamwork in this firm is fully recognised and rewarded	1    2    3    4    5	

Please describe the firm's business strategy in one sentence:____________________

_____________________________________________________________________

Please describe the firm's knowledge strategy in one sentence:___________________

_____________________________________________________________________

Please describe the firm's information technology strategy in one sentence:_________

_____________________________________________________________________

Please describe the firm's human resources strategy in one sentence:______________

_____________________________________________________________________

Which function in the firm is responsible for knowledge management?________function

Which function in the firm is responsible for IT management?________function