Data Management Plan for the SGTS Nordic & Baltic PC Factory
Kanerva, Hans (2021)
Kanerva, Hans
2021
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2021120223147
https://urn.fi/URN:NBN:fi:amk-2021120223147
Tiivistelmä
The purpose of this study was to create a data management plan, which would address issues related to data management at the PC Factory activity within the Saint-Gobain Technology Services Nordic & Baltic (SGTS NB) organization. SGTS NB is an internal IT-service organization within the global enterprise Saint-Gobain, which deliver infrastructure services for the local Saint-Gobain companies in the Nordic & Baltic region and the PC Factory is a dedicated SGTS NB team, focused on delivering premium PC life-cycle services. The need for data management was identified before the study, but the necessary means and tools were missing. It was decided that the study was needed to find a solution for the issues faced and hence was the study commissioned by SGTS NB.
The current state of the PC Factory data management was investigated by using both qualitative and quantitative methods. The qualitative research consisted of six in-depth interviews with relevant stakeholders while the quantitative research consisted of a customer survey, which was addressed to a total of forty-six recipients. Issues were found in four areas of the current data management process, and the issues were related to missing skills, policies, reports, and current heavy manual processes. Best practices were found from available knowledge which identified the means and tools for solving the issues identified during the current state analysis phase.
The outcome of this thesis is a data management plan, based on the best practice, which address the data management issues within the PC Factory. The data management plan is targeted for a specific business problem, but it is written in a way which makes it possible to replicate, with modifications, to other parts of the organization. The data management plan addresses the six activities discovered during the analysis of the best practices, in addition to the data maturity assessment, which as a whole cover all aspects of the activities needed for working data management. A detailed action plan is prepared, as an appendix to the data management plan, to ensure a successful implementation of the data management plan.
It is agreed within SGTS NB that the data management plan will be facilitated within the PC Factory, as the benefits for the organization are clear and beneficial. The work will start in Q1-2022 and is estimated to be completed by the end of year 2022. By implementing the data management plan the PC Factory will be in control of data, will be able to utilize data better, and will be able to continue the development of data analytics to support the organization digital transformation in the future by continuing to build upon the data maturity presented in this thesis.
The current state of the PC Factory data management was investigated by using both qualitative and quantitative methods. The qualitative research consisted of six in-depth interviews with relevant stakeholders while the quantitative research consisted of a customer survey, which was addressed to a total of forty-six recipients. Issues were found in four areas of the current data management process, and the issues were related to missing skills, policies, reports, and current heavy manual processes. Best practices were found from available knowledge which identified the means and tools for solving the issues identified during the current state analysis phase.
The outcome of this thesis is a data management plan, based on the best practice, which address the data management issues within the PC Factory. The data management plan is targeted for a specific business problem, but it is written in a way which makes it possible to replicate, with modifications, to other parts of the organization. The data management plan addresses the six activities discovered during the analysis of the best practices, in addition to the data maturity assessment, which as a whole cover all aspects of the activities needed for working data management. A detailed action plan is prepared, as an appendix to the data management plan, to ensure a successful implementation of the data management plan.
It is agreed within SGTS NB that the data management plan will be facilitated within the PC Factory, as the benefits for the organization are clear and beneficial. The work will start in Q1-2022 and is estimated to be completed by the end of year 2022. By implementing the data management plan the PC Factory will be in control of data, will be able to utilize data better, and will be able to continue the development of data analytics to support the organization digital transformation in the future by continuing to build upon the data maturity presented in this thesis.