Proceedings of the 12th European Conference on Knowledge ...

Harold Harlow
knowledge to create customer value as measured by innovation and economic outcomes. In order to
measure <strong>the</strong> innovation and economic outcomes <strong>of</strong> <strong>the</strong> firm, it is important to understand how and
why tacit KM is both crucial and necessary in today’s firms.
It is not sufficient to have knowledge assets, patents, or o<strong>the</strong>r marketable intellectual property. In a
knowledge creating company, managers have <strong>the</strong> responsibility to unleash that knowledge into valuecreating
actions aimed at customers and to generate and exploit that knowledge-ei<strong>the</strong>r public or
proprietary-more effectively than <strong>the</strong>ir competitors. In addition, managers are also responsible to
generate and exploit current firm knowledge better than <strong>the</strong>ir competitors and to use public knowledge
better than <strong>the</strong>ir rivals (Von Grogh Ichigo et al 2000). Von Krogh, Roos and Slocum (1994) suggest
that <strong>the</strong>re are essentially only two strategies used and that those are advancement and survival.
Ans<strong>of</strong>f (1990) also uses <strong>the</strong>se two distinctions as operational effectiveness strategy and developing
future pr<strong>of</strong>it potential strategies.
.
Miles and Snow (1978) identified three primary strategic types—defenders, prospectors, and
analyzers—and one lesser strategic type: reactors. Each <strong>of</strong> <strong>the</strong>se strategic types has different
performance characteristics based on environmental conditions such as stage in <strong>the</strong> product life
cycle, market growth, and industry product innovation. Each <strong>of</strong> <strong>the</strong>se strategies also has its own set
<strong>of</strong> unique knowledge competencies that enable <strong>the</strong> firm to compete. Strategic fit is an important
consideration as firms employ KM systems and determine whe<strong>the</strong>r to use systems that are tacit,
explicit, or a mix <strong>of</strong> both (Miles and Snow 1984). Porter also identified cost and differentiation as two
primary strategies <strong>of</strong> <strong>the</strong> firm (Porter 1980). While o<strong>the</strong>r strategies have been proposed as guiding <strong>the</strong>
operation <strong>of</strong> <strong>the</strong> firm, a manager who is interested in any <strong>of</strong> <strong>the</strong>se strategies has to choose a
knowledge strategy that fits <strong>the</strong>ir firm and that knowledge strategy is driven by <strong>the</strong> overall strategy <strong>of</strong>
<strong>the</strong> firm.
My earlier research has developed a tacit knowledge index used in this paper (Harlow 2008). My prior
research also included <strong>the</strong> effect <strong>of</strong> tacit knowledge and knowledge management methods both in <strong>the</strong>
aggregate and individually on firm performance. This research forms <strong>the</strong> background and structure for
this follow-on paper on knowledge strategy development and its relationship to <strong>the</strong> innovation and
learning perspective <strong>of</strong> <strong>the</strong> balanced scorecard.
This research uses analysis <strong>of</strong> <strong>the</strong> performance outcomes where <strong>the</strong> results <strong>of</strong> <strong>the</strong> firm, in both
innovation and financial outcomes, are equated to customer value. That value-creating capability
resides in <strong>the</strong> know-how or tacit knowledge <strong>of</strong> <strong>the</strong> engineers, managers and marketing staff and this
dynamic tacit knowledge capability creates sustainable competitive advantage (Teece, 1998). These
subject matter experts must be able to fit into an automated system that allows tacit knowledge
dispersal and tacit knowledge use by both <strong>the</strong> experts and <strong>the</strong> rest <strong>of</strong> <strong>the</strong> firm’s staff and depends to a
large degree on <strong>the</strong> KM systems that are employed (Maybury D’Amore and House, 2000). This is
needed for both <strong>the</strong> firm’s survival and advancement strategy (Von Grogh Ichigo et al, 2000).
3. Research Hypo<strong>the</strong>sis and Results
Dependent performance variables for innovation and financial were operationalized in <strong>the</strong> prior
research survey (Harlow 2008) based on <strong>the</strong> research performance variables from <strong>the</strong> Pr<strong>of</strong>it Impact <strong>of</strong>
Market Strategies (PIMS) database (Anderson and Paine 1978). Scores from <strong>the</strong> 1-5 Likert scale
factor questions were summed to create an overall innovation or financial score. Higher additive
scores indicated higher performance on each measure. Table 1 below indicates <strong>the</strong> factors used to
sum <strong>the</strong>se variables.
Table 1: Innovation and Financial Performance Variables
Innovation Financial
Product turns (as related to competitors) Return on sales
Number <strong>of</strong> new products (as related to competitors) Cost <strong>of</strong> goods sold
Patents (as related to competitors) Earnings per share
New products compared to <strong>the</strong> competition Share price over past 3 years
Market share compared to <strong>the</strong> competition Return on equity
Age <strong>of</strong> product lines Revenues
Marketing effectiveness Pr<strong>of</strong>its
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