By Their Words Ye Shall Know Them:

Knowledge management terms 1

Knowledge Management Terms and Common Business Language

William L. Tullar Department of Business Administration Bryan School of Business and Economics University of North Carolina at Greensboro Greensboro, NC 27401

Tony R. Wingler Department of Accounting and Finance Bryan School of Business and Economics University of North Carolina at Greensboro Greensboro, NC 27401

Abstract This exploratory research examines the penetration of knowledge management vocabulary words into general business parlance. The authors constructed counts of the relative frequency of knowledge management words in 10k reports of 40 randomly chosen publicly traded U. S. companies. Results indicated that many of the vital knowledge management concept words were never used at all in more than 665,000 words. Those words that did have significant frequency were those that had more general meaning than just KM. Using 32 words that did have a significant frequency of occurrence, the sample was split into two halves: 20 high knowledge management companies and 20 low knowledge management companies. Results indicate that 14 KM words did occur significantly more often in high knowledge management companies. Knowledge Management Terms 2

Introduction

As to moving ideas around diverse businesses that don’t have a lot in common, General Electric does this because it has to. If it doesn’t, then it is just a holding company . . . A breakthrough in GE’s Medical Systems business, with relatively little modification, led to a method by which an aircraft engine can transmit continuous information about blade speed, engine heat and other relevant data about its in-flight performance well in advance of any possible safety situation. This innovation, in turn, catalyzed an important new development with respect to a self-monitoring system for use with heart pacemakers. I could cite any number of other examples having to do with sharing methods of selling, sourcing techniques, procedures for improved storage and security of data and so on. (Steve Kerr, VP of Corporate Leadership Development and chief learning officer, General Electric Corporation as quoted in Miller, Fern, & Cardinal (2007).)

Knowledge may well be the most important intangible asset that a firm controls (Liebeskind, 1996). Indeed, there is some evidence that knowledge management (KM) practices have an effect on overall firm performance (Marqués & Simón, 2006) and the application of inventions to technological development (Miller, Fern, & Cardinal, 2007). Those who have been stressing the importance of intangible assets for sustained competitive advantage recognize that knowledge management is crucial to firm success.

The importance of knowledge management has been enhanced by reduced product life cycles, high mobility rates of educated knowledge workers, and the increased merger and acquisition activities around the globe. Knowledge Management (KM) is a young management theory which emerged in the 1990’s and focuses on how the creation, transfer, retention, and utilization of knowledge can be managed within organizations and applied to business processes in order to gain a competitive advantage. Initiated by the globalization, labor-intensive manufacturing has moved from the developed countries to low-cost labor countries around the world: While in the 1960’s almost 50% of all workers in industrialized countries were employed in manufacturing-related jobs, in the new millennium this proportion is down to about 20% (Drucker, 1994). A recent OECD study highlights the service sector (perhaps the most dedicated users of KM) to be the quantitatively most important sector in almost all OECD countries, contributing 70% of all economic value added (Wölfl, 2005).

Textbooks on knowledge management point out how companies have built knowledge repositories that support customer knowledge, product development knowledge, customer service knowledge, and human resource management knowledge (e.g. Awad & Ghaziri, 2004). Search any major business program in the United States or Europe, and you will get at least a dozen hits for the term Knowledge Management. Knowledge management Knowledge Management Terms 3 topics appear in the popular and business press, attendance at KM conferences and seminars is increasing, specialized KM journals provide forums for the dissemination of new knowledge, and the proliferation of KM courses at the post-secondary level signals awareness of the importance of the area to society. Some organizations have even begun using job titles like: knowledge developer, knowledge facilitator, and chief knowledge officer. These trends are both reflective of the value of KM and indicative of its future potential for enhancing many areas of society.

The importance of language in knowledge management

Language is the principle medium of thought. When people do not have the requisite terms and concepts, it is difficult to think or talk precisely about a topic. In order to think precisely about knowledge management (KM), we argue that it is necessary to use the terms that have developed in the field. This paper examines the extent to which those terms appear in 10 Ks, the most concise and thoughtful of corporate self descriptions.

Firestone (2001, p. 3) defines knowledge as “validated linguistic formulations about the world, the beautiful and the right.” Building on the importance of language, we explore how the words used by business firms to describe themselves is reflective of their value system . . . what they view as important to their success and how they view themselves as distinct. This study is an exploratory study of the KM words used by business organizations in describing themselves and their activities as a means of marking the development of KM as a business activity.

Method Sample of Firms We created a stratified random sample of forty publicly-traded American corporations where the sample strata are developed to capture the extremes of reliance on, and use of knowledge management. The two strata are defined as firms that allocate a substantial proportion of their revenues to research and development activities and those that expend very little of their resources on such activities. Spending on research and development signifies that corporate resources have been allocated to activities which are expected to provide future benefits, although the realization, timing, and duration of the expected benefits is characterized by considerable uncertainty. The term research and development connotes the marshalling of various firm resources and the extension of its understanding to advance the firm’s abilities and understanding in some fashion. The stratification of our sample is thus designed to identify firms which should place different levels of emphasis on the management of knowledge. Those that focus heavily on research and development must necessarily focus on knowledge management; those that focus only slightly on research and development are likely to be less concerned with knowledge management. Knowledge Management Terms 4 Therefore, from here on, we shall identify high R & D expenditure firms as High KM Firms and low R & D expenditure firms as Low KM Firms. We performed a computerized search of the Morningstar financial data base to identify high and low KM firms. Criterion for inclusion in the High KM firms’ stratum was that they had expended thirty percent or more of their annual revenues on research and development over the most recent three-year history. We judged the thirty percent level as identifying firms that devote a considerable portion of firm resources to the development of knowledge assets. Companies that were included in the Low KM sample were those that expended five percent or less of their total revenues over the most recent three years history on research and development activities. Selection of the threshold levels (five and thirty percent) was based on examination of the criterion measure for a large number of firms and the determination that the selected levels appeared to distinguish the more extreme points of the research and development spending continuum. The Morningstar screens produced a large number of firms satisfying the low KM screen and a much smaller number of firms satisfying the high KM screen. The high-low KM groups were further analyzed by randomly selecting from each group for purposes of our analysis. Given that the high KM group is somewhat smaller than the low KM group, our stratified sample oversamples the high KM group. A listing of firms randomly selected from the high-low KM groups is shown in appendix A. A close reading of that appendix reveals some surprising firms in each of the samples. For instance, it is surprising to find Dell in the Low KM sample. Our screening procedure examined the latest three years of financial data. If this time period places a firm at a down cycle in its business activities, it is possible that business conditions have dictated a scaling back of research and development activities from that which would be more typical. It is quite common for firms experiencing moderating growth trends to reduce spending on research and development in an effort to bolster earnings. This possibility is ameliorated in our sample in that the time period was generally one of good business conditions with most firms reporting improving and even record earnings (See for instance, .”Bullish toast,” 2004; “Profits are stronger,” 2004; “Stronger sales,” 2004). Under American Generally Accepted Accounting Principles (GAAP), expenditures on research and development must be charged as an expense to revenues in the period the activity takes place. Although R&D spending is an investment which is expected to provide benefits over future years, for accounting purposes, it is not treated in this fashion. A theoretically proper accounting treatment of the benefits and cost associated with R&D activities would entail a portion of the R&D costs incurred today be matched as an expense against the future revenues generated by the R&D activity. For practical reasons, accounting guidelines specify that proper identification of the future revenue benefits derived from today’s R&D spending is so problematic as to preclude this conceptually desirable matching of revenues and costs. Instead, accounting guidelines require that the costs associated with developing the long Knowledge Management Terms 5 term knowledge asset (research and development) be fully expensed against current revenues. This accounting artifact means that firms in which KM is integral to their success are in way penalized in their current reported income by having to expense activities which clearly have long-term benefits. This accounting artifact is the primary reason firms curtail R&D spending in a given year in an effort to avoid further pressures on their accounting earnings if they are experiencing a cycle of weakening business activity (Penman, 2007). In order to see how extensively the KM vocabulary has penetrated the general business lexicon, we examine the wording of what is widely viewed to be the most definitive self-description of business firms--their 10K reports filed yearly with the United States’ Securities and Exchange Commission. These 10K reports resulted in a total sample of over 655,000 words on 1588 pages of text.

Sample of KM Words

We identified a set of knowledge management words by using KM textbooks and KM encyclopedias. We do not claim that our list is exhaustive; it is simply a convenience sample drawn from well known sources. We endeavored to identify as many words as possible that are commonly used in KM applications. Textbooks from Knowledge Management courses were used to identify words that KM authors emphasized in the vocabulary sections of their texts. The references used were Awad & Ghaziri (2004) Knowledge Management, Gottschalk (2005) Strategic Knowledge Management Technology, Hislop (2005) Knowledge Management in Organizations: a critical introduction, and Schwarz (2006) Encyclopedia of Knowledge Management. While this list certainly is not exhaustive of possibilities, it does provide a representative sample of KM terms. After identifying a long list of words from our sources, we eliminated all the duplicates on our list. The resulting 171 words are found in Table 1. In addition to not being exhaustive, the identified words/phrases in Table 1 are not exclusive to KM. A cursory examination of the words indicates that many of these terms are in general usage. However, they are words that a number of authors have indicated as necessary to understand the concepts of knowledge management.

Results

Fifty-seven percent of the KM terms listed in Table 1 were not cited even one time in the 655,000 words in our sample. Considering that such a large percentage of the KM words in Table 1 are unused in almost 1600 pages of business text describing 40 publicly traded companies, we are led to conclude that there is little evidence to suggest that the general KM vocabulary in Table 1 has been incorporated into general business parlance. It is interesting to note that some of the words that had zero frequency are not at all esoteric: data mining, expert system, groupware, and knowledge creation are just some of the terms whose absence is troubling to those interested in promoting the value of KM. Knowledge Management Terms 6 The argument that 10K reports are financial reports and therefore could not be expected to use the KM words in Table 1 misses an important point. The 10K reports are the primary forum used by firms to convey information of their activities to external constituents. As such, and also owing to information disclosures required by the SEC, the 10K report is widely viewed as the most credible and forthcoming information which firms provide about themselves. ------Insert Table 1 about here ------Even more interesting is the set of terms that are mentioned. Table 2 shows that of the 73 terms in Table 1 that are mentioned, only 44 or 26% are mentioned 10 or more times. Only 19 terms are mentioned 100 or more times and only three terms are mentioned 1000 or more times. Looking at those terms mentioned 100 or more times, we find that most of them, while having knowledge management and information technology uses, are words that have a variety of more general meanings. Words such as case, data, intellect, intellectual property, research, resources, rights, study, user, and validation are not specific to knowledge management or information technology but have a variety of business uses. The words that occur more than 1000 times, asset, patent, and technology are clearly words that extend across many common business topics. ------Insert Table 2 about here ------The main inference we draw from our findings shown in Tables 1 and 2 is that terms more specific to knowledge management occur infrequently if at all. From knowledge base to knowledge source only one mention was found. Tacit knowledge, a critical concept knowledge management, has a zero frequency. It is particularly disappointing that words such as data mining, data warehouse, and knowledge map have frequencies of zero. These are concepts that constitute much of the value added of KM. Even “information technology” has a mere 24 mentions. What our results generally show is that most of the listings in Table 1 occur very infrequently, if at all, in the most comprehensive and most studied self-description provided by business firms. If knowledge management is a source of value and a competitive advantage, then we should expect to see more mentions of these terms as a reflection of its perceived value. In recent years, even accountants have sought ways to account for “intangible assets” such as knowledge. However, the language necessary to describe “intangible assets” is not common. Finance, accounting, marketing, and operations management terms abound in our sample 10Ks. Terms such as market segmentation (27 mentions), target market (21 mentions), liabilities (558 mentions), liquidity (123 mentions), testing (223 mentions), training (179 mentions), and manufacturing (1542) have fairly high frequencies. These functional areas of business are older and have had a longer period of time to infuse their central concepts into common business language. Knowledge Management Terms 7 We hold that the infusion of knowledge management vocabulary into general business parlance is an evolving process which currently can be characterized as a slow evolution. However, we also believe that it is important that American businesses and the people who think and write about them should begin to use the terms that will enable them to describe the merits of knowledge management processes that create value. In order for the value of knowledge management to be more widely appreciated, knowledge management terms will have to gain wider use. ------Insert Table 2 about here ------Table 3 shows the contrast in frequency between high KM firms. As can be seen in the table, the multivariate test of the difference between the two groups is significant at the 1% level. Of the 32 words listed in the table, 14 of them show differences in favor of the High KM firms significant at the 5% level or better. Two of the differences that are significant at the 5% level show significantly higher relative frequencies for Low KM firms. Those words are ‘Assets’ and ‘Web.’ Given the relative greater emphasis on tangibles in the Low KM firms, the result for the word ‘asset(s)’ is not surprising. The word ‘Web’ may seem somewhat more surprising, but the web has become a venue for so many different activities. High KM firms may use it less to protect the confidentiality of the knowledge they are depending on. In the rest of the table, there are only four more non-significant negative t’s. The table thus has 26 t’s that are positive. That is, for those 26 words, the High KM sample shows a higher relative frequency than the Low KM sample. The words that have significantly higher frequencies in high knowledge management organizations are words that we would expect: case, file, know- how, model, patent, protocol, range, research, resources, rights, science, study, technology, and uncertainty. So while it is true that few words from the KM vocabulary have substantial frequencies in the 10K’s of our sample, it is also true that the words that do have some level of usage differentiate between High KM and Low KM organizations. Discussion

Wider Assimilation of KM Words The phrase tipping point is a sociological phrase that describes a dramatic moment when something unusual or unique becomes commonplace. Malcolm Gladwell's 2000 bestselling book, The Tipping Point: How Little Things Can Make a Big Difference, popularized the idea and applied it to daily life. While the phrase is often misused, it seems perfectly applicable here. What we have seen is that much of the important vocabulary of KM has not reached the tipping point - - it has not become commonplace in business language. We have also seen that in a small random sample of High KM and Low KM firms, some of the KM vocabulary discriminates significantly between the two groups. While the results are not uniform, they do seem to indicate that 14 of the 32 KM vocabulary words that occurred more often than 30 times in the 655,000 Knowledge Management Terms 8 words of this sample do discriminate between High and Low KM firms. We see this as evidence for the validity of the idea that KM is driven by vocabulary - - firms that make a living on knowledge are more likely to use certain words to describe themselves and their activities. We recognize that the words that do discriminate between the two groups are words that are fairly general and not specific to KM. We would expect that as KM becomes more widely practiced that some of the more esoteric KM words would discriminate between these two groups. It is true that there are many specialized business and trade journals that are focused on knowledge management . Any internet search of journals could turn up dozens that either have knowledge management in their titles or feature articles about knowledge management. The Harvard Business Review has had 53 articles since 1995 that focused in whole or in part on knowledge management. A search of business school offerings shows that all of the top 50 U. S. business schools (most recent Business Week rankings) have coursework that deals wholly or in part with knowledge management. All that should indicate that knowledge management should be well on its way to being a recognizable functional area in business. These data seem to indicate otherwise. We are not sure when the tipping point will come, but it needs to come soon. Managing knowledge assets necessitates a certain vocabulary. We suspect that 10Ks of High KM firms written ten or fifteen years from now will include a lot more KM terms and more esoteric KM terms at that. We also speculate that the gap in KM vocabulary will grow wider between High KM firms and Low KM firms. As more businesspeople are trained in KM concepts, the KM terms that are now somewhat esoteric will become more commonplace. If knowledge is the intangible asset that allows a firm to gain a sustainable competitive advantage, then knowledge management and the vocabulary to implement it must become more commonplace in business language. Knowledge Management Terms 9

Table 1 Knowledge Management Words Tried Out (40 organizations, 665,000 words on 1588 pages)

Analogies 0 Enterprise application 7 Artificial intelligence 1 Enterprise information portal 0 Asset 1021 Enterprise knowledge Portal 0 Authentication 13 Episodic knowledge 0 Authority 39 Expert system 0 Bandwidth 12 Expertise 65 Believe 826 Explicit interteam transfer 0 Blackboard 0 Explicit knowledge 0 Blackboarding 0 Extensible markup language 1 Bounded rationality 0 External data 0 Brainstorming 0 Extranet 1 Case 225 Facet 39 Case-based Reasoning 0 Fault tolerance 0 Categorical data 0 Firewall 2 Certainty factor 15 Frame 5 Chunking 0 Groupware 0 Classification tree 0 Heuristic 0 Classification 30 Ideawriting 0 Cleaning data 0 Inductive reasoning 0 Closed question 0 Inference engine 0 Clustering 0 Inference 0 Collaborative 0 Inferencing 0 Collaborative intelligence 0 Information Technology 24 Collective sequential Transfer 0 Inheritance 0 Consensus decision 1 Instantiate 0 Content management System 0 Intellect 263 Copyright 44 Intellectual capital 1 Data 566 Intellectual Property 239 Data mining 0 Intelligence 27 Data warehouse 0 Intelligent agent 0 Decision tree 0 Internal data 0 Declarative Knowledge 0 Internet 129 Deductive reasoning 0 Interoperability 12 Delphi method 12 Intranet 5 Deployment 44 Justifier 0 Dichotomous question 0 Know-how 43 Document management system 0 Knowing-doing gap 0 Electronic collaboration 0 knowledge base 1 Electronic mailing List 0 Knowledge center 0 Empowerment 1 Knowledge Codification 0 Knowledge Management Terms 10 Knowledge creation 0 Research 893 Knowledge developer 0 Resources 307 Knowledge Management 0 Rights 596 Knowledge map 0 Role bias 0 Knowledge repository 0 Rule of inference 0 Knowledge sharing 0 Rule 89 Knowledge source 0 Sampling 64 Knowledge-related Driver 0 Satisficing 0 Learning by discovery 0 Scalability 12 Learning by Example 0 Science 44 Learning by Experience 0 Scribe 0 Learning organization 0 Search engine 4 Learning 0 Secondary question 0 Legacy application 1 Semantic knowledge 0 Logic 18 Sensitivity analysis 5 Management Science 0 Sequence discovery 0 Matching 4 Serviceability 2 Metadata 0 Shallow knowledge 0 Middleware 1 Shuttle process 0 Model accuracy 0 Slot 3 Model 193 Software 781 Modularity 0 Study 272 Multiple-choice 0 Systems analyst 0 Neural net 0 Tacit knowledge 0 Nominal Group Technique 0 Tacit knowledge Transfer 0 Open-ended question 0 Technical core 0 Outliers 0 Technology 1170 Patent 1448 Teleconferencing 0 Pattern 32 Test data 0 People core 0 Think-aloud 0 Personalization 1 Training data 0 Portability 5 Transformation 26 Portal 7 Transport layer 0 Premise 7 Uncertainty 56 Primary question 0 Usability 1 Procedural rule 0 User 185 Production rule 0 User interface 2 Profiling 3 Validation 144 Protocol analysis 64 Validity 41 Range 476 Verification 19 Ranking scale 1 Vertical portal 0 Rapid prototyping 0 Video mail 0 Reasoning 0 Voice portals 0 Reliability 2 Web 218 Repertory grid 0 Workflow 6 Repository 3 Knowledge Management Terms 11 Table 2 Frequency of Word Occurrence # of Terms % Total KM Terms # of Mentions 98 57% 0 73 43% >0 44 26% >10 19 11% >100 3 2% >1000

Table 3 Means, Standard Deviations, and t’s for each Word that Made the Cut Hotellings λ = 0.055, p < .01 (20 high, 20 low) Word(s) Low Mean Low SD High Mean High SD t Asset(s) 1.77 1.04 1.21 1.02 -2.46** Authority 1.25 1.78 1.73 2.55 1.50 Belief, Believe 0.02 0.05 0.01 0.04 -1.39 Case* 0.57 0.38 0.27 0.29 2.72** Copyright 0.06 0.11 0.05 0.07 -0.74 Data 0.47 0.46 0.70 0.62 1.86 Example(s) 0.13 0.15 0.20 0.17 1.58 File(s)* 0.28 0.26 0.47 0.46 2.43** Force 0.35 0.28 0.35 0.32 0.63 Intellect 0.33 0.33 0.39 0.36 0.10 Intellectual Property 0.29 0.29 0.36 0.35 0.29 Internet 0.15 0.22 0.15 0.27 0.44 Know-how* 0.02 0.06 0.06 0.08 2.14* Model* 0.24 0.28 0.59 0.42 4.36** Patent* 0.95 1.15 1.84 1.78 3.29** Pattern 0.06 0.10 0.04 0.07 -0.76 Property 0.51 0.36 0.62 0.42 0.77 Protocol* 0.01 0.04 0.10 0.16 4.22** Range* 0.71 0.66 1.55 1.25 3.86** Research* 0.72 0.52 2.17 1.82 4.97** Resource(s) * 0.51 0.34 0.65 0.40 2.86** Rights* 0.50 0.47 1.03 0.71 4.08** Rule, rules 0.07 0.10 0.08 0.13 0.94 Sample(s,ing) 0.03 0.07 0.08 0.27 1.12 Science* 0.02 0.07 0.08 0.16 2.02* Software 0.76 1.97 0.53 1.09 -0.03 Stud(y,ies,ing)* 0.04 0.08 0.56 0.84 4.04** Technolog(y,ies, ical)* 1.72 1.43 3.22 2.51 3.56** Uncertainty* 0.08 0.10 0.19 0.22 2.99** User(s) 0.22 0.33 0.26 0.43 0.53 Valid(ity, ation) 0.04 0.06 0.06 0.10 1.20 Web 0.28 0.26 0.16 0.23 -2.33* Knowledge Management Terms 12

References

Awad, E. & Ghaziri, H. (2004) Knowledge Management. Pearson Prentice Hall: Upper Saddle River, NJ.

A bullish toast to 2005. (2004, December 13). Barrons, p. 26.

Drucker, P. (1994). Post-Capitalist Society, HarperCollins, New York

Firestone, J. (2001). Key issues in knowledge management. Journal of Knowledge and Innovation, 1, 3, 8-38.

Gladwell, M. (2000). The Tipping Point: How Little Things Can Make a Big Difference, Boston : Little, Brown

Gottschalk, P. (2005) Strategic Knowledge Management Technology, Idea Group Publications: Hershey, PA

Hislop, D. (2005) Knowledge Management in Organizations: a critical introduction, Oxford University Press: New York.

Liebeskind, J. (1996). Knowledge, strategy, and the theory of the firm. Strategy Management Journal, 21, 111-125.

Marqués, D. and Simón, F. (2006). The effect of knowledge management practices on firm performance. Journal of Knowledge Management, vol. 10, No 3, 143-156.

Miller, D., Fern, M., & Cardinal, L. (2007). The use of knowledge for technological innovation within diversified firms. Academy of Management Journal, 50, 2, 308-326.

Penman, S. (2007). Financial Statement Analysis and Security Valuation, McGraw-Hill Irwin: New York, NY

Profits are stronger than investors’ nerves. (2004, September 27). Business Week.

Schwarz, D. (2006) Encyclopedia of Knowledge Management, Idea Group Publications: Hershey, PA

Stronger sales power profits. (2004, July 26). Business Week. Knowledge Management Terms 13 Woelfl, A. (2005). The Service Economy in OECD Countries, OECD, Directorate for Science, Technology, and Industry (DSTI), http://ideas.repec.org/d/scoecfr.html

Appendix A

Firms above the 30% criterion Firms Below the 5% criterion Adolar Adam Golf Applied Microcircuit Albemarle Biogen Aptar Group Bitstream Bemis Corporation Brocade ComSys Cabot Capstone Ceradyne Celea Genomics Charles Colvard Ciena Dell Cubist Pharmaceuticals EOG Resources Diversa Firearms Training Systems Epiphany Harris Exactscience IMAX ICOS International Game Technology Imclone Systems Jabil Circuit Medarex K2 Myrid Genetics NETFLIX Phoenix Technologies Oakley Protein Design Labs Penford Redback Networks Pentair Sepacor Serologicals