Assessment of Data-Driven Project Management Practices with a Particular Focus on Project Maturity Models: The Case of Ethiopian Red Cross Society
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Date
2022-07
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Addis Ababa University
Abstract
The objective of this study is assessing data-driven project management practice with particular focus on project maturity models, the case of Ethiopian Red Cross Society. To accomplish its
objectives, the researcher has employed a descriptive research design and used both primary and secondary data. For the primary data the researcher has conducted an online survey questionnaire and for the secondary data the researcher has used document reviews associated with ERCS and other partner national societies that have delegation offices in Ethiopia, within the ERCS premises or compound. According to this study, the project management practice in the organization mainly depends on gut or instinct and partially on data that is inconsistent and unstructured. The study has discovered that there are some limitations in data-driven project management practice in the organization which the researcher believes is a contributing factor for the project delay, cost overrun and quality issues. In relation to this limitations, it’s been found out that there is limitation to the project data culture, project data management, and data-driven decision making in the organization. Based on the findings the researcher has noted a gap in data-driven project management between the data use culture in the existing project management practice and what ought to be. The results of the findings are presented using tables, charts, percentages, and also discussed using project maturity models. Based on the findings the researcher makes recommendation in order to improve the data-driven project management practice in the organization. According to the researcher, ERCS needs to make all the efforts required to improve
or bridge the gap in its data-driven project management practices and basis all of its projects decisions mainly on data so as to gain the competitive advantage data would bring about.
Keywords: Data, Project, Project data, Data-driven culture, Project management, Data-driven project management, Data-driven decision making