Integrated assessment of organization's knowledge potential/ Integruotas organizacijos ziniu potencialo vertinimas.

Bivainis, Juozas ; Morkvenas, Renatas

1. Introduction

States and organizations invest large sums of money into the creation of mind power platforms. While these processes carry on, the society has stepped into a new stage of development where networks of complicate structures and different depths of knowledge form (Adekola et al. 2008; Tvaronaviciene, Kalasinskaite 2010). In this society there is a need to conceptualize the knowledge potential of human that was acknowledged by scientists in the 20th century as the most important resource that conditions both personal and organizational success, effectiveness of investments, economy expansion as well as the power of states. Employees, organizations and even states are compared in the aspect of knowledge (Brauers, Ginevicius 2009; Ginevicius, Gineviciene 2009).

It is important to stress that purposeful and well-grounded management of knowledge potential relies on knowing how to measure, assess or calculate it (Kaklauskas et al. 2009). Although there are quite a lot of scientific studies as well as more popular publications on various aspects of knowledge management, but professional and scientific material on organization's knowledge potential assessment is very scarce. While suitable instrumentalities' which let to assess knowledge potential of organization is not created, the managing of this resource can't be effective. This situation encouraged us to carry out a research on knowledge potential assessment by summarizing other scientists' research results on this topic and preparing a quantitative model for integrated assessing the potential of knowledge in organization.

2. Building a new concept model for organization's knowledge potential assessment

The exact quantitative adaptation of models for assessment of organization's knowledge potential has not been developed. According to D. Bell (1973), A. Toffler (1980), J. Bivainis (1991), P. Drucker (1993), I. Nonaka and H. Takeuchi (1995), W. C. Kim and R. Mauborgne (1999), A. Armstrong and P. Foley (2003), N. Paliulis and J. Raudeli?nien? (2006) the need for such investigations is caused by changing social structure. The analysis of scientific papers identifies numerous works which assess the competency and knowledge of organizations and employees, as well as analyze the knowledge management and application by organizations. The following works can be considered as more distinct in the area of knowledge management: Wissepsmanagement Forum Organization's knowledge management process assessment guide (2003); assessment methods of jobs and office positions by A. Sileika et al. (2004); "Knowledge measurement and interviewer bias" by K. Fink (2005); "Organizational competency management" by T. Ley (2006); organization's knowledge culture creation and development model by O. Stan and K. R. Kandadi (2006); organization's knowledge assessment model by E. Jonhson (2007); and organization's knowledge management model created by The Knowledge Company, Inc. (2009). Comparison of models analyzed in Table 1 summarizes models used to assess knowledge in the organization.

After examining the results of model comparison (Table 1) it becomes clear that models analysed do not meet modern requirements and must be improved in many ways. Only two models provide the assessment result in quantitative expression, only one model is entirely orientated towards an individual, none of the models analyse synergy in the context of knowledge, and assessment factors in all models provoke doubt on the expedience of application when knowledge contents are concerned, and application of all models is complicated.

Therefore, assessing knowledge potential becomes vital in modern managing of an organization. The outcome of our multiyear research is a model (Fig. 1) essentially based on an original concept, and consisting of the following parts: 1) employee's knowledge potential assessment; 2) knowledge potential synergy assessment; 3) organization's external medium assessment.

[FIGURE 1 OMITTED]

Firstly, it is aimed at creating a collective medium where all employees are able to find the gaps that might be filled with their knowledge potential. Secondly, the synergy is created when employees interplay in the organization medium.

Synergy arises not only when two complementary persons with different skills cooperate. Synergy arises when different types of knowledge are combined and we call it the synergy component of knowledge potential. Thirdly, the more effective external relations the organization can maintain, the more knowledge it is able to absorb into itself and disseminate this knowledge within the organization via the internal relations.

3. Assessment of employee's knowledge potential

In assessing the knowledge potential of an employee as a member of an organization, it is necessary to evaluate his actions in a certain complicated organization's internal medium, which is common to all the employees. In our opinion, the main factor that reveals an employee's knowledge potential is the complexity of the work that the employee does. The more complex is the work, the greater knowledge potential is necessary to accomplish it.

According to the International Labor Organization Geneva Scheme (1950), the complexity of the work is determined by evaluating the requirements for the specific job position, i.e., employee's education, professional experience, and level of position. They as important factors determining employee's knowledge potential are analyzed by J. Bivainis (1991), P. Drucker (1993), V. Dubinas (1995), I. Nonaka, H. Takeuchi (1995), A. Sileika et al. (2004), O. Stan and K. R. Kandadi (2006), Knowledge Company, Inc. (2009), World Bank (2008). All these factors are detailed using quantitative methods in our earlier investigations (Bivainis, Morkv?nas 2010).

Assessment of education component of knowledge potential. Employee's knowledge potential determined by the employee's level of education can be calculated as follows:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (1)

where: B--score for employee's highest acquired education; [p.sub.c]--score for employee's additionally acquired education in the level c; [l.sub.c]--score for employee's acquired education that enabled him/her to acquire additional education in the level c; [h.sub.c]--number of additionally acquired educations in the level c; t--number of educational levels.

The basis of these calculations is the cumulative vector (Table 2), based on the score distribution according to our ca[l.sub.c]ulations of educational levels (Bivainis, Morkv?nas 2010). Under different conditions, the cumulative vector can be recalculated using our proposed methodology.

Assessment of occupational experience component of knowledge potential. Employee's knowledge potential, determined by employee's occupational experience, can be calculated as follows:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (2)

where: [d.sub.s]--employee's work experience in the sector; [d.sub.b]--employee's overall work experience; [psi]--relative importance of the overall work experience compared to the work experience in the sector.

Assessment of occupation level component of knowledge potential. Employee's knowledge potential, assessed from the employee's position level, can be determined as follows:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (3)

where: [[phi].sub.a]--evaluation of the employee's position a in score; [[kappa].sub.a]--quantity of hours worked in the employee's position a; [sigma]--number of positions held by employee in the organization.

Assessment of employee's salary as indicator of the employee's ability to use his/her acquired knowledge potential. The salary also allows to quantitatively compare the knowledge potential of employees from different organizations. In Formula 4, the employee's knowledge potential is multiplied by the employee's salary coefficient ([[eta].sub.i]) see Formula 5), and the knowledge potential (Podi) of all the employees of organization l is determined according to Formula 6.

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (4)

[eta] = [u.sub.0]/[u.sub.v], (5)

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (6)

where: [[lambda].sub.j]--importance of factor j; [V.sub.ij]--score of factor j considering employee i; [u.sub.v]--average salary (brutto) in the labor market; [u.sub.0]--employee's salary (brutto) in an organization; n--number of employees of an organization.

In order to ascertain the importance of factors determining the knowledge potential of an employee, we conducted a research. The importance was evaluated applying the AHP (Analytic Hierarchy Process) (Saaty 1980). The evaluation characteristics of factors by their importance, as determined by experts, are provided in Table 3.

4. Assessment of knowledge potential synergy in organization

In order to evaluate the synergy of knowledge potential of an organization, it is first necessary to determine the amount of knowledge disseminated among the employees. The determination of the amount of knowledge disseminated among the employees in the model is calculated from the average knowledge potential of an employee ([k.sub.v]) per one relation: p

[k.sub.v] = [P.sub.odl]/[r.sub.t], (7) rt

where: [r.sub.t]--maximum amount of relations among the employees within an organization. Knowing what the average knowledge potential of an employee is per one relation, the second step is to determine the number of effective relations ([r.sub.e]) that form among the employees of an organization. We suggested two different methodological variants for performing this step.

Method based on theoretical norms accepted in a theory of management. For theoretical calculations, the norm of effective relations [r.sub.n] = 5. Then:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (8)

where: [r.sub.a]--number of random relations.

The number of random relations among employees within an organization is calculated as follows:

[r.sub.a] = 1 - 1/n) (n - 6). (9)

Method based on the detailed analysis of an organization's management structure, which determines the existing relations between the employees within a division, as well as relations between the employees from different divisions.

Because the multiplicator law applies to knowledge, the amount of disseminated knowledge is multiplied by the knowledge multiplicator. To determine the knowledge multiplicator (m), the following parameters are used: 1) norm of effective relations; 2) compat ibility of organizational structure; 3) informational technology employment coefficient; 4) size of an organization.

1. First of all, it is important to note that when there is a large number of employees, knowledge is not exchanged between each of the employees. When knowledge dissemination takes place among employees, the knowledge multiplicator depends on the number of effective relations maintained per one employee. The management theory indicates that the number of relations that can be maintained effectively by an employee, is limited because upon expansion of the number of those relations part of them become ineffective. Therefore, knowledge can be multiplied as many times as is physically possible. Scientific literature indicates that an employee can effectively maintain 4 to 6 relations, and this number is considered the norm. The amount of disseminated knowledge ([r.sub.e] [k.sub.v]) within an organization can be multiplied [r.sub.n] times.

2. Concerted structure of an organization enables the employees to effectively receive, disseminate, and create knowledge. Whether an organization's structure is concerted or not is revealed by a very important characteristic of an organizational structure--subordination. The norm of subordination has been determined by V. A. Graiciunas (1937)--a rational number of employees, subordinate to the manager is 4 to 6. L. F. Urwick (1943) score out that a manager cannot directly control the activities of more than 5 to 7 employees. In our opinion, there exists another characteristic, more precisely determining the compatibility of an organization, i.e., the average number of effective relations per one employee ([r.sub.v]), as the effective work of employees is no less important than that of managers. Determined norms (the model uses the results of the work of V. A. Graiciunas (1937)) apply to both managers and employees, i.e., the norm of effective relations ([r.sub.n]) is equal to 4-6 relations. The average number of effective relations per one employee is calculated by dividing the number of effective relations by n/2 (because 2 employees participate in one relation):

[r.sub.v] = [r.sub.e]: n/2 = [2r.sub.e]/n. (10) 2 n

To evaluate the compatibility of the organizational structure, the compatibility coefficient ([m.sub.s]) of organizational structure has been calculated:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (11)

3. Another factor stimulating the synergy of knowledge potential is the ability of the employees to apply information technologies. The coefficient ([m.sub.t]) of the employees' ability to use information technologies is calculated as follows:

[m.sub.t] = 1/100 [beta], (12)

where: [beta]--the percentage of the organization's employees able to use the Internet.

4. In order to evaluate the impact of the organization's size on knowledge multiplication, logarithmic function can be applied (its application is based on our research). The base of the logarithm is the size of the organization ([greater than or equal to] 250 employees), according to the classification of enterprises.

Therefore, the impact of the organization's size on knowledge multiplication is evaluated by a coefficient ([m.sub.n]):

[m.sub.n] = [log.sub.250](n). (13)

To sum up, the knowledge multiplicator and the synergy of the knowledge potential of the organization's employees is calculated in following way:

m = [r.sub.n] [m.sub.s] [m.sub.t] [m.sub.n], (14)

[P.sub.osl] = [mr.sub.e][k.sub.v], (15)

[P.sub.osl] = [r.sub.n] [m.sub.s] [m.sub.t] [m.sub.n] [r.sub.e] [k.sub.v]. (16)

After adding the knowledge potential of the organization l and the organization's knowledge potential arising from synergy, the result can be obtained as follows:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (17)

5. Assessment of organization environment

In assessing the organization's knowledge potential it is important to investigate the influence of the environment on the organization. The more knowledge the environment contains, the more effective external relations the organization can maintain within that environment. The more effective external relations the organization maintains, the more knowledge the organization can absorb into itself, and disseminate that knowledge via internal relations within the organization. The knowledge potential of each organization has to be corrected by a coefficient ([[mu].sub.z]), the value of which depends on the knowledge economy index of the country in which the organization operates:

[[mu].sub.z] = [KEI.sub.z]/[KEI.sub.v], (18)

where: [KEI.sub.z]--knowledge economy index of country z; [KEI.sub.v]--the average of the indices of the countries' knowledge economy.

With respect to the level of the knowledge economy of the country in which the organization operates, the knowledge potential is corrected in the following way:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (19)

6. Verification of the model for assessing organization's knowledge potential

When carrying out theoretical simulation of knowledge potential components in organization, low, average and maximum meanings of informational technology employment and organizational structure compatibility coefficients were chosen. In order the simulation to be more simple other parameters used in model were set as constants (e.g. knowledge potential of organization ([P.sub.di]) equals 150 score), some of them change according to the number of employees. Results of simulation are given below (Figs. 2-6).

When the number of employees in the organization or its subdivisions is rational (6 employees) and when meanings of coefficients that are used to calculate synergy are maximum, the simulated ratio of knowledge potential synergy and employees' knowledge potential equals 1.62, when the coefficients are average the ratio equals 0.79, and when the coefficients are low it equals 0.28. When the number of employees in the organization increases, knowledge potential synergy and employees' knowledge potential ratio decreases.

[FIGURE 2 OMITTED]

[FIGURE 3 OMITTED]

[FIGURE 4 OMITTED]

[FIGURE 5 OMITTED]

[FIGURE 6 OMITTED]

To verify the practical applicability of model of knowledge potential assessment in organization by carrying out an empirical research three different organization were chosen: 1) Department of Cultural Heritage under the Ministry of Culture of the Republic of Lithuania (further mentioned as Department); 2) wood processing company "Inkilas" (further mentioned as Wood Processing Company); 3) consulting company "VEPROC Research and Consulting, Ltd." (further mentioned as VEPROC).

After analyzing the results of research (Table 4) it was determined that knowledge potential level in VEPROC is high (total 5805 score, 387 score per employee), in the Department it is average (total 21192 score, 202 score per employee), in the Wood Processing Company it is low (total 4787 score, 84 score per employee). The results in a quantitative expression as well as transformed in a relative measure are reliable and easy to compare. In the organizations chosen for the research the knowledge potential synergy and employees' knowledge potential ratio is from 0.08 to 0.87.

This way of demonstrating research results allows one to group organizations according to their knowledge potential, compare them in different aspects, determine the need to increase knowledge potential and sources needed, and find the highest value of organizational knowledge potential and work results.

According to prepared given assessment methodic, the model is easily applied in various organizations. The usage of model is useful because: 1) by putting the model into practice it is possible to assess knowledge potential in organization quantitatively; to determine the level of knowledge potential and its changes in organization; to make the best decisions that stimulate the spread of knowledge potential in organization by following results of model application; 2) the model can be successively applied when carrying out various research in order to determine knowledge potential in employees and organization. This model can also be applied when carrying out complex research in order to assess knowledge potential in organization group, sector, state and organizations in different countries; 3) state's knowledge potential assessment database can be created based on this model.

7. Conclusions

The model to assess knowledge potential is orientated towards an individual and involves all components of knowledge: explicit, tacit and synergy. The content of model was structured using factors that till now were poorly analyzed in the context of knowledge but are very important; the factors and their connections' qualitative characteristics were reduced to quantitative expression.

Such conclusions were drawn after theoretically simulating components of knowledge potential in the organization and carrying out an empirical research applying the created model to assess knowledge potential in different organizations:

--Organization must use means to stimulate synergy, otherwise the knowledge potential synergy dies away rapidly (after simulating the ratio between employees' knowledge potential and knowledge potential synergy, it was from 0 to 1.62, in comparison with results given by empirical research--from 0.08 to 0.87). It was determined that knowledge potential synergy in organization grows slower when the number of employees grows, and the largest amount of knowledge potential synergy per employee is reached when there are 6 employees in the organization.

--Model parameters are easily applied in the organizations assessed. Organization's accounting and statistical data are enough to make the calculations. The results received after assessing the knowledge potential of organizations were transformed into a relative quantity (knowledge potential of organization per employee that shows the level of knowledge potential in organization) and are easy to compare.

Presumptions made after applying the model: to enlarge permanent organization's competitiveness by identifying unused sources of knowledge potential and by developing management of human resources; to bind salary system with employees' knowledge; to make objective decisions on employee change; to observe changes in organization's result and knowledge potential dependence; to form databases that support knowledge management decisions. The model can be easily put into practice by various organizations, and assessment results form different states can also be compared.

Applying the model in the future should be taken into account the importance of factors. In our research the importance of factors are established leading classical understanding of knowledge organization. However in the different phases of economical development the importance of factors could change and must be recounted permanently using suggested methods.

doi: 10.3846/16111699.2011.620152

Received 25 February 2011; accepted 30 May 2011

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Juozas Bivainis [1], Renatas Morkvenas [2]

Department of Social Economics and Management, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania

E-mails: [1] vvfsevk@vgtu.lt (corresponding author); [2] r.morkvenas@vgtu.lt

Juozas BIVAINIS. Professor, Doctor Habil, Head of Department of Social Economics and Management, Vilnius Gediminas Technical University. He is the author of over 200 scientific works. Research interests: intensification of economic development, business management theory, economic legislation.

Renatas MORKVENAS. Doctor of social science. Department of Social Economics and Management, Vilnius Gediminas Technical University. Research interests: creating methodologies for knowledge management, business management. Table 1. Comparison of the models assessing an organizations' knowledge potential Authors of models Criteria of O. Stan, comparison K. Fink E. Johnson K. R. Kandadi R. Smith Presentation of 0 1 0 2 result in quantitative expression Orientation towards 1 1 1 1 an individual Identification of 0 0 0 1 knowledge synergy Suitability of 1 1 1 1 assessment factors Applicability 1 1 1 2 Versatility 0 0 0 2 Acceptability of 0 0 1 2 expenditure Objectiveness of 1 1 1 0 results Authors of models Criteria of "Wisseps- comparison T. Ley management Forum" "Workitect, Inc" Presentation of 2 1 0 result in quantitative expression Orientation towards 1 1 2 an individual Identification of 0 0 0 knowledge synergy Suitability of 1 1 1 assessment factors Applicability 0 1 1 Versatility 0 1 1 Acceptability of 0 2 1 expenditure Objectiveness of 1 1 1 results Authors of models Criteria of The Knowledge comparison Company, Inc." Presentation of 0 result in quantitative expression Orientation towards 1 an individual Identification of 0 knowledge synergy Suitability of 1 assessment factors Applicability 1 Versatility 1 Acceptability of 1 expenditure Objectiveness of 1 results Notes: Model estimates according to criteria: 0 -non satisfactory; 1 - partly satisfactory; 2 -com-pletely satisfactory Table 2. Cumulative vector of the knowledge potential distribution according to the level of education Education Score 1. No education 0 2. Elementary education 12.18 3. Basic education (10 grades) 22.97 4. Secondary education 31.30 5. Professional education 36.95 6. Bachelor's degree 48.71 (obtained not from a University) 7. Bachelor's degree 67.7 (obtained from a University) 8. Masters degree 73.51 9. Doctors's degree 100.00 Table 3. Synthesized evaluation characteristics of factors by their importance Factors [V.sub.1] [V.sub.2] [V.sub.3] [[lambda].sub.j] [V.sub.1] 1.00 0.52 3.14 0.34113 [V.sub.2] 2.14 1.00 4.29 0.54303 [V.sub.3] 0.34 0.25 1.00 0.11584 Table 4. Summary of the results of an empirical study Parameter Department Wood Processing VEPROC Company Employee's knowledge 12013 score 2969 score 2077 score potential ([P.sub.dl]) Synergy of knowledge 2210 score 244 score 1819 score potential ([P.sub.sl]) Number of direct 191 79 26 relations among employees in different subdivisions ([r.sub.s]) Number of effective 219 127 15 relations in subdivision ([r.sub.p]) Total number of 410 206 44 effective relations among employees ([r.sub.e]) Average employees' 2.2 score 1.86 score 19.78 score knowledge potential per relation ([p.sub.v]) Average number of 7.8 7.2 5.86 relations per employee ([r.sub.v]) Management structure 0.461 0.6944 0.8532 compatibility coefficient ([m.sub.s]) Informational 0.91 0.251 1 technology employment coefficient ([m.sub.t]) Organization S size 0.84 0.73 0.49 coefficient (mj 2.45 0.636 2.1 Knowledge multiplicator (m) Environment 1.49 1.49 1.49 knowledge potential level coefficient ([[mu].sub.z]) Knowledge potential 21192 score 4787 score 5805 score ([P.sub.j]) Knowledge potential 202 score 84 score 387 score per employee ([P.sub.dv])