How Data-Driven Decision-Making is Utilized and Seen at the Manager Level of the Case Company
Kuittinen, Teemu (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024121837289
https://urn.fi/URN:NBN:fi:amk-2024121837289
Tiivistelmä
The amount of data created and harnessed is increasing year over year. The need for data-driven decision-making is constantly growing and this calls for organizations to start utilizing their data at every level. In this thesis, the focus group is the manager level of the case company. The goal is to understand how data-driven decision-making is utilized and seen at the manager level.
Data-driven decision-making consists of many different aspects. It involves the data itself, data quality, data culture, data literacy, data analysis, and decision-making. All these aspects can provide organizations with a more thorough decision-making process and the possibility for better preparedness toward the result.
Data-driven decision-making is a relatively new concept in business as the amounts of data have only evolved greatly in recent years in the 21st century. To access it fully, an organization needs to have a more thorough data culture than just static visualizations, reports, and dashboards. It requires a robust data culture in which data is shared and accessible throughout the organization. It requires data that is timely, relevant, and trustworthy. It requires data literacy to enable the employees and managers the possibility to utilize the available data. Finally, it requires the managers to have a thorough understanding of data and data analytics and to showcase data-driven decision-making for the employees.
The material was gathered by conducting semi-structured interviews with the participants. The interviews consisted of seven sections, which were related to data, data analysis, data quality, data-driven decision-making, and result tracking.
The results provided an outlook of how the manager level of the case company utilizes and sees data-driven decision-making. The results showcased a thorough and confident experience in data-driven decision-making. It was seen as a major aspect of business and decision-making, and it was better to have at least some data than to have zero data in decision-making. With the use of data, decisions had the backing from facts, and it provided the possibility for preparedness for certain outcomes as well as a way of risk management.
Data-driven decision-making was seen as a crucially important part of organizations and the future, with the expanding of technologies such as Big Data and AI. Possible challenges could be seen within data quality, and human mindset toward data-driven decision-making.
Data-driven decision-making consists of many different aspects. It involves the data itself, data quality, data culture, data literacy, data analysis, and decision-making. All these aspects can provide organizations with a more thorough decision-making process and the possibility for better preparedness toward the result.
Data-driven decision-making is a relatively new concept in business as the amounts of data have only evolved greatly in recent years in the 21st century. To access it fully, an organization needs to have a more thorough data culture than just static visualizations, reports, and dashboards. It requires a robust data culture in which data is shared and accessible throughout the organization. It requires data that is timely, relevant, and trustworthy. It requires data literacy to enable the employees and managers the possibility to utilize the available data. Finally, it requires the managers to have a thorough understanding of data and data analytics and to showcase data-driven decision-making for the employees.
The material was gathered by conducting semi-structured interviews with the participants. The interviews consisted of seven sections, which were related to data, data analysis, data quality, data-driven decision-making, and result tracking.
The results provided an outlook of how the manager level of the case company utilizes and sees data-driven decision-making. The results showcased a thorough and confident experience in data-driven decision-making. It was seen as a major aspect of business and decision-making, and it was better to have at least some data than to have zero data in decision-making. With the use of data, decisions had the backing from facts, and it provided the possibility for preparedness for certain outcomes as well as a way of risk management.
Data-driven decision-making was seen as a crucially important part of organizations and the future, with the expanding of technologies such as Big Data and AI. Possible challenges could be seen within data quality, and human mindset toward data-driven decision-making.