English
Received 22.09.2023, Revised 10.01.2024, Accepted 28.02.2024
In the modern IT industry Scrum methodology is increasingly popular, necessitating the development and use of effective metrics for evaluating team stability and productivity. Among these, the volatility metric stands out as critical for enhancing work efficiency analysis and timely problem identification. It involves quantitative methods, encompassing data collection on performance and subsequent statistical analysis. Factors like the sprint risk coefficient significantly impact sprint volatility, yet the scale and measurement methods of this impact, crucial in team performance data analysis, remain unclear. This involves calculating average performance values, and standard deviation, and employing Pearson’s correlation coefficient. The aim is to precisely establish the relationship between sprint riskiness and team performance variability, enhancing understanding of risk factors impact on team efficiency in a dynamic project environment. Quantitative analysis methods, including the collection of performance data, determining the average performance value, and calculating the standard deviation and Pearson correlation coefficient are used to assess the relationship between iteration riskiness and volatility. The study revealed a statistically significant positive correlation between the riskiness of iterations and team volatility, with correlation coefficients ranging from 0.47 to 0.86. This indicates a significant impact of risks on team stability. The research proposes methods to investigate the relationship between the sprint risk coefficient and project teamwork volatility. It confirms that increased iteration riskiness correlates with higher Scrum teamwork volatility. Further research is recommended on external factors affecting this interaction to develop more effective risk management methods
scrum methodology; sprint risk coefficient; team volatility in Scrum; risk management in agile projects; risk management methods
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