Improving master data quality in data migration of ERP implementation project
Nyrhilä, Petteri (2015)
2015
Tietojohtamisen koulutusohjelma
Talouden ja rakentamisen tiedekunta - Faculty of Business and Built Environment
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Hyväksymispäivämäärä
2015-04-08
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201503231147
https://urn.fi/URN:NBN:fi:tty-201503231147
Tiivistelmä
ERP systems constitute the information system backbone of most organizations across all industries. An ERP implementation is a huge commitment for organizations and too often they are failed or ran over schedule and budget. Poor data is claimed to be the number-one reason for the high failure rate of new computer system implementations. The problem is that the data which is migrated from a legacy system to a target system has poor quality.
The aim of this thesis was to study how the master data quality can be improved in the data migration process of SAP ERP implementation. The research was conducted at a general level and specific cases or organizations were not examined. The objective was to compile a list of methods how to improve the master data quality in the data migration process. To achieve the goal the main barriers for the master data quality in the data migration process were also recognized.
The research was conducted in two parts: theoretical and empirical. The theoretical section was based on scientific literature about the research title and formed the foundation for the empirical part. The empirical research was conducted as a case study where the qualitative data was collected by interviewing nine SAP consultants. Furthermore, an additional questionnaire was conducted in order to point out the most intrinsic results.
The results show that the data migration process includes several data quality barriers which need to be taken into consideration. The barriers were divided into three groups: data, people, and process related barriers. The methods to improve the master data quality in the data migration process were derived from the data quality barriers and they were also divided into the same three groups: data, people, and process relater methods.
According to the results the most intrinsic methods to improve the master data quality in the data migration of SAP implementation are taking care of the good engagement with the client, defining and communicating the data related roles and responsibilities unambiguously, analyzing the status of the data in the legacy systems at starting point, arranging and executing the data cleansing carefully already in the legacy system, creating unambiguous data collection templates and carrying out walkthrough for them, and determining SAP rules for data to correspond to the business rules.
The aim of this thesis was to study how the master data quality can be improved in the data migration process of SAP ERP implementation. The research was conducted at a general level and specific cases or organizations were not examined. The objective was to compile a list of methods how to improve the master data quality in the data migration process. To achieve the goal the main barriers for the master data quality in the data migration process were also recognized.
The research was conducted in two parts: theoretical and empirical. The theoretical section was based on scientific literature about the research title and formed the foundation for the empirical part. The empirical research was conducted as a case study where the qualitative data was collected by interviewing nine SAP consultants. Furthermore, an additional questionnaire was conducted in order to point out the most intrinsic results.
The results show that the data migration process includes several data quality barriers which need to be taken into consideration. The barriers were divided into three groups: data, people, and process related barriers. The methods to improve the master data quality in the data migration process were derived from the data quality barriers and they were also divided into the same three groups: data, people, and process relater methods.
According to the results the most intrinsic methods to improve the master data quality in the data migration of SAP implementation are taking care of the good engagement with the client, defining and communicating the data related roles and responsibilities unambiguously, analyzing the status of the data in the legacy systems at starting point, arranging and executing the data cleansing carefully already in the legacy system, creating unambiguous data collection templates and carrying out walkthrough for them, and determining SAP rules for data to correspond to the business rules.