Benchmarking in multinational companies to support investment decision making
Salina, Anna (2022)
Salina, Anna
2022
Master's Programme in Industrial Engineering and Management
Johtamisen ja talouden tiedekunta - Faculty of Management and Business
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Hyväksymispäivämäärä
2022-11-04
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202211028136
https://urn.fi/URN:NBN:fi:tuni-202211028136
Tiivistelmä
Modern competitive business environment forces companies into a non-stop development and adaptation of its external and internal functions along with changing conditions. To stay competitive production companies mainly focus on more efficient ways of manufacturing. One of the most promising methods to discover development opportunities is to compare company’s performance towards similar actors. In that sense multinational companies have a significant advantage of comparing with its own subsidiaries, where cultural and geographical diversity brings along wider knowledge scale and more experience.
The motivation of the study was to validate the effectiveness of the production methods in the case company and to explain productivity difference in the production units of the same company. The need of benchmarking was identified to tackle the challenge and to map areas of improvement and find solutions. The aim was to gain realistic vision of current state of the manufacturing activities in the company. The benchmarking results then are taken as a solid knowledge background for making an investment decision.
The objective of the thesis consists of two parts. The first part questions whether the benchmarking has a potential inside the multinational company with various product portfolios in their subsidiaries. The second part attempts to analyse the coherence between company’s machine fleet and its product portfolio. The thesis is based on the case study conducted in a multinational company producing the hydraulic fittings with its subsidiaries producing hydraulic hose assemblies.
To answer the research question, a study was performed on a base of combination of existing material in a form of interventionist research. Primary and secondary data was utilized. The researcher was a part of the company, while conducting the study. The empirical part of the study was executed based on historical data retrieved from two hydraulic hose assembly manufacturing units of the same company.
To execute the benchmarking procedure, it was necessary to identify benchmarking candidates from product portfolios of both units. The candidates were identified after a thorough analysis of data retrieved from company’s software. Differences in manufacturing processes in two subsidiaries were taken into account. The benchmarking process initiated another research question about fleet coherence and product portfolio of the case company which was studied based on historical manufacturing data and experience of another unit in the same organization.
The results of the study showed that one of the biggest challenges in benchmarking is to definite candidate products for comparison. Even though two legit benchmarking candidates were identified, however, with the limited available data there was no clear explanation in the productivity difference of two production units. Additionally, the incoherence between factory’s machine fleet and its product portfolio was identified. The recommendation for adjusting the company’s fleet was presented. The further analysis of manufacturing data from other production units of the same company could provide clearance to the productivity difference and deviations of cycle times.
The motivation of the study was to validate the effectiveness of the production methods in the case company and to explain productivity difference in the production units of the same company. The need of benchmarking was identified to tackle the challenge and to map areas of improvement and find solutions. The aim was to gain realistic vision of current state of the manufacturing activities in the company. The benchmarking results then are taken as a solid knowledge background for making an investment decision.
The objective of the thesis consists of two parts. The first part questions whether the benchmarking has a potential inside the multinational company with various product portfolios in their subsidiaries. The second part attempts to analyse the coherence between company’s machine fleet and its product portfolio. The thesis is based on the case study conducted in a multinational company producing the hydraulic fittings with its subsidiaries producing hydraulic hose assemblies.
To answer the research question, a study was performed on a base of combination of existing material in a form of interventionist research. Primary and secondary data was utilized. The researcher was a part of the company, while conducting the study. The empirical part of the study was executed based on historical data retrieved from two hydraulic hose assembly manufacturing units of the same company.
To execute the benchmarking procedure, it was necessary to identify benchmarking candidates from product portfolios of both units. The candidates were identified after a thorough analysis of data retrieved from company’s software. Differences in manufacturing processes in two subsidiaries were taken into account. The benchmarking process initiated another research question about fleet coherence and product portfolio of the case company which was studied based on historical manufacturing data and experience of another unit in the same organization.
The results of the study showed that one of the biggest challenges in benchmarking is to definite candidate products for comparison. Even though two legit benchmarking candidates were identified, however, with the limited available data there was no clear explanation in the productivity difference of two production units. Additionally, the incoherence between factory’s machine fleet and its product portfolio was identified. The recommendation for adjusting the company’s fleet was presented. The further analysis of manufacturing data from other production units of the same company could provide clearance to the productivity difference and deviations of cycle times.