Chapter V. ANALYSIS OF OWN RESEARCH IN THE SCOPE OF KNOWLEDGE
1. Results of the pilot study
The results of the pilot study of the two companies, acquiring one – Company 1 (F1) and acquired one – Company 2 (F2), allowed to examine 31 variables (features) broken down by general characteristics and knowledge of the examined enterprises.
Table 34 shows the results of the pilot study stage a, and Table 35 shows the results of stage b.
Table 34. General variables (characteristics) of the studied enterprises – pilot studies stage a results
No. Indicators Company 1 (acquiring) Company 2 (acquired)
1. Company assets 135.9 (EUR million) 67,1 (mln euro)
2. Average pay 3,313 (PLN) 4 020 (zł)
3. Total number of employees 51 459
4. Percentage of employees with higher
education (%) 5% 10%
5. Departments (production, electromechanical,
technical-implementation) 6 3
6. Revenues from sale 0–100 (PLN million) 101-500 (PLN million)
7.
General assessment of company financial condition (1 – the lowest grade, 4 – the
8. Whether transition team was established in the company?
YES YES
NO NO
9. Whether representatives of the acquired company take part in works of the team?
YES YES
No. Indicators Company 1 (acquiring) Company 2 (acquired))
12. Applied wage system
piecework piecework
incentive wage system incentive wage system
daily pay daily pay
daily-task daily-task
other – daily with bonus other – daily with bonus
13.
Cultural differences in relation to
consolidated company (0 – lack, 1 – small, 2 – average, 3 – biggest)
Number of employees having access to a computer compared to the total number of employees (in %)
31% 22%
15.
Number of employees having access to data base compared to the total number of employees (in %)
11% 19%
Source: own study.
Table 35. Knowledge variables (characteristics) of the studied enterprises – pilot studies stage b results
No. Type of knowledge taken over Acquiring
company Acquired company 1.
x1 – knowledge that is an individual motive for acquisition (patents, inventions, important technologies etc.)
YES NO YES NO
2.
x2 – knowledge, including tacit knowledge that is relevant to the acquiring entity (e.g. particular competences of management, unique skills of contractors, etc.)
YES NO YES NO
3. x3 – knowledge, including explicit knowledge, of
relevance (relations, experience, etc.) YES NO YES NO
4.
x4 – organisational knowledge characteristic of certain enterprises (pay system rules, reports, important legal documents, etc.)
x1 – knowledge that is an individual motive for acquisition (patents, inventions, important technologies etc.)
x2 – knowledge, including tacit knowledge that is relevant to the acquiring entity (e.g. particular competences of management, unique skills of contractors, etc.)
4 (months)
1 (months)
7. x3 – knowledge, including explicit knowledge, of relevance (relations, experience, etc.)
x4 – organisational knowledge characteristic of certain enterprises (pay system rules, reports, important legal documents, etc.)
2 (months)
3 (months)
Type of knowledge taken over
Significance (weight) of knowledge Acquiring
company Acquired company 9.
x1 – knowledge that is an individual motive for acquisition (patents, inventions, important technologies etc.)
0 6
10.
x2 – knowledge, including tacit knowledge that is relevant to the acquiring entity (e.g. particular competences of management, unique skills of contractors, etc.)
4 5
11. x3 – knowledge, including explicit knowledge, of
relevance (relations, experience, etc.) 2 2
12.
x4 – organisational knowledge characteristic of certain enterprises (pay system rules, reports, important legal documents, etc.)
x1 – knowledge that is an individual motive for acquisition (patents, inventions, important technologies etc.)
0% 90%
14.
x2 – knowledge, including tacit knowledge that is relevant to the acquiring entity (e.g. particular competences of management unique skills of contractors, etc.)
30% 60%
15. x3 – knowledge, including explicit knowledge, of
relevance (relations, experience, etc.) 20% 40%
16.
x4 – organisational knowledge characteristic of certain enterprises (pay system rules, reports, important legal documents, etc.)
80% 90%
Source: own study.
Companies vary considerably in value of assets, sales revenues, and level of employment. Company 2 was the initiator of the consolidation (merger by absorption).
Company 1 in the year preceding the consolidation has shown a net revenue of PLN 320.1 million, while the Company 2 generated PLN – 228.8 million. In turn the assets of the two companies amounted to PLN 62.1 and PLN 135.9 million, respectively.
The acquisition of professional staff employed directly in production is a condition of mastering technology by the acquiring enterprise. A reflection of importance of the staff employed directly in production in Company 1 is significantly higher average wages in this company.
Table 36 summarizes these indicators and their differences.
Firstly, the differences between activity status indicators and knowledge transferable of both companies were examined.
Table 36. Summary of activity status indicators and knowledge and their differences for pilot
1. Company assets PLN million 135.9 67.1 -68.8 68.8
2. Average pay PLN 3.313 4.020 +707 707
3. Number of employees people 51 459 +408 408
4. Percentage of employees with higher
education % 5 10 +5 5
5. Amount of revenues PLN million 19.2 241.5 +222.3 222.3
6. Number of departments pc. 6 3 -3 3
7. General assessment of company financial
condition (1, 2, 3, 4) 1-6 3 3 0 0
8. Knowledge learning time (×1) months 0 1 +1 1
9. (×2) months 4 1 -3 3
10. (×3) months 5 6 +1 1
11. (×4) months 2 3 +1 1
12. Significance (weight) of knowledge ×1 6–4 0 6 +6 6
13. ×2 4–2 4 5 +1 1
14. ×3 2–-1 2 2 0 0
15. ×4 1–0,5 1 0,5 0 0
16. Explicit knowledge share ×1 % 0 90 +90 90
17. ×2 % 30 60 +30 30
18. ×3 % 20 40 +20 20
19. ×4 % 80 90 +10 10
20.
Number of employees having access to a computer compared to the total number of employees
% 31 22 -9 9
21.
Number of employees having access to data base compared to the total number of employees
% 11 19 +8 8
Source: own study.
Examining the differences between the values concerning both companies, especially in terms of knowledge transfer, is important. Knowledge transfer is best suited to companies with large potential differences, both in terms of size and importance of knowledge. On the other hand, when the consolidation is motivated by other goals, only useful knowledge is mentioned. This distinction has a specific meaning. In the case of searching a way to shorten the time to acquire the necessary knowledge, this can be done at the expense of prolonging the time to master useful knowledge. In this situation, the greater the differences in such knowledge are, the more companies are susceptible to be consolidated. By successively analysing values in table 38, an attempt was made to interpret them.
Assets of the two companies, listed on the first position, are very different.
This means that the acquisition will be relatively straightforward both in formal and substantial terms, as decision disputes will be avoided in case of possible divestment.
However, it will not be easy in terms of knowledge acquisition. The smaller of the companies have improved furnace operating technology and experienced staff with high competences. This requires a serious effort related to conveying the tacit knowledge associated with technology, skills and experience.
The same applies to the number of employees, as among them are highly qualified professionals. This is also evidenced by the average wage level that is higher in the acquired company. The difference in the number of departments relative to employment is rather apparent. In the first company the number of furnaces in the department is significantly lower than in the acquiring entity.
There is no difference in the overall financial condition.
Unlike indexes that determine the level of acquired knowledge, a significant difference, expressed in the time of learning, is not great. Exception is the difference in the acquired knowledge with respect to x2 knowledge, which indicates the time of learning it by the acquired company, mainly concerning knowledge related to the experience and skills of executives.
However, given the importance of knowledge, the amount of difference refers to knowledge x1. This concerns mastering the new improved technology.
The differences in the share of explicit knowledge are very high only in relation to the technology acquired, as it was part of the knowledge that the first company was most interested in.
In addition to the aforementioned differences, calculated were these in accessing the computer and database. They are a bit bigger in the first company. The arithmetic means and absolute deviations from this value, calculated for individual indicators, show very large variations both in size of the company (assets) and its human potential. However, in terms of knowledge, the situation is different in its individual types, which in turn increases the scope of its possible bilateral transfer.
More information can be provided by an analysis of the structure, which is only possible in the problem of knowledge acquisition due to the presence of homogeneous quantities.
Table 37 contains two types of data. Firstly, the top rows of the table contain data on location of knowledge acquired from Company 2 by Company 1, secondly is the same amount expressed in percent.
Table 37. Structural cross-section of knowledge acquired and transferred according to its types analysed in the study
Time of knowledge transfer in months Knowledge structure indexes in%
F1 F2 Σ F1 F2 Σ
x1 0 1 1 0 100 100
x2 4 1 5 80 20 100
x3 5 6 11 45 55 100
x4 2 3 5 40 60 100
22 Source: own study.
Company 1 acquired technological knowledge within a month and knowledge involving experience and performance skills within 6 months. The latter type of knowledge is tacit knowledge, the transfer of which is not simple, requires observation and imitation, and therefore takes a relatively long time, compared to the transfer of explicit knowledge, e.g. in the form of technological documentation.
In terms of knowledge x2 the situation was reversed. Company 1 transferred to Company 2 much more knowledge than it had acquired. These were managerial skills and other elements that were important to the acquiring entity, as Company 2 thus increased its productivity and lowered costs, which brought a significant benefit to the consolidated enterprises. Knowledge of the x3 type with a high proportion of tacit, poorly measurable elements was transferred in both directions; it was different knowledge, mutually needed. The same can be said about organizational knowledge x4.
The second section is the knowledge considered by the participation of companies in each of its categories, presented in Table 38.
Table 38. Structural cross-section of knowledge acquired by companies Absolute numbers (months) Structure indicators (%)
F1 F2 F1 F2
x1 0 1 0,0 9,0
x2 4 1 36,0 9,0
x3 5 6 45,0 54,5
x4 2 3 19,0 27,5
Σ 11 11 100 100
Source: own study.
Company 1 has acquired all kinds of knowledge. In certain cases this was a mutual exchange of knowledge, and acquisition took almost equal time in case of knowledge x3 and x4.
From a knowledge perspective, Company 2 (F2) gained a large amount of knowledge x2and x3, related to skills and experience.
Company F1 has gained experience in the use of furnace technology. Having data on the time of mastering knowledge and the scales that determine their importance, it is possible to calculate the overall time of knowledge transfer, taking into account its importance. For this purpose, a model of knowledge transfer was used (Figure 27).
As inputs, the values of knowledge and the coefficients from Table 36 were used, i.e. the general set of variables (features) for the pilot study, where actual data concerning the transfer time and the coefficients were placed, established on the basis of expert advice from each company separately. These coefficients differ from the established median values, estimated by experts for the entire group, and can be adjusted after analysis of the pilot study results. After placing the coefficients to the knowledge transfer model (Figure 27), considering the validity of the knowledge, based on the expert consultations of the two companies, the following equation was obtained:
Y1=6X1+5X2+2X3+ .0 5X4,
Y2 =4X2+2X3+X4, (6)
Y1+ → minY2 .
The following results were obtained when the knowledge values and calculation data were placed:
Y1= × + × + × +6 1 5 1 2 6 0 5 3. × ,
Y2 = × + × + ×4 4 2 5 1 2, (7) Y1+ =Y2 24 5 28. + =52 5. .
These results can be interpreted as follows: the overall time to master the knowledge transferred in both directions is 52.5 months, which is slightly more than four years. However, taking into account that with the appropriate human and material resources it could take place in parallel, this time could be reduced by a maximum of about half. However, this is not often the case. Choice has to be made, focusing on the knowledge most important in terms of business mergers effectiveness. Such manoeuvring is possible not only by simultaneous learning of knowledge, but also by total or temporary restraint of certain non-essential elements of transfer (e.g. adaptation of systems and regulations). In this situation, it is enough to skip or reduce the range of knowledge learnt that is of lesser importance in the model system, and to devote time and material resources to the transfer of knowledge of basic importance. In addition, the transfer manager may impose certain conditions
limiting the transfer time, e.g. in the pilot study described above, it is sufficient to impose in the second equation, a limit to x2 ≤ 8 and x3 ≤ 5 to shorten the overall transfer time by 13 months.
Verification of taxonomic grouping (by pilot study provided for in the substantial part) is not possible as the pilot group used cannot be split as the taxonomic distance of enterprise 1 from enterprise 2 is the same as 2 to 1. This would mean that both examined companies are not susceptible to transfer and that both are mutually compatible and belong to the same group. It must be stressed, however, that the purpose of the pilot study was not a detailed verification of the test methods applied in the base study, but merely direction of the research process.
The pilot study suggests that in the full group there should entities with differentiated character, representing different situations in the area of knowledge transfer. Then the conclusions of this study could be used to better understand the transfer process itself and be able to provide the opportunity to change the due-diligence analysis and methodology.