An organization is undergoing a digital transformation. New behaviour patterns are encouraged among the teams. Many employees have adopted these…

The described employee attitude of avoiding experimentation and waiting for a single correct solution directly impacts two key behavior patterns. Firstly, it shows a failure to accept ambiguity and uncertainty, as the team members are uncomfortable acting without a guaranteed, pre-defined outcome. High-velocity environments are inherently complex and uncertain, requiring teams to proceed with incomplete information. Secondly, this attitude hinders the commitment to continual learning. Experimentation is a fundamental method for learning and discovery in complex systems. By avoiding it, employees are rejecting a primary mechanism for gaining new knowledge and improving their work, which is the essence of a learning culture.

A. 3 and 4: While this attitude may indirectly slow down customer value delivery (3) and could stem from a lack of trust (4), the described behaviors are most directly a failure to embrace uncertainty and learning.

B. 1 and 4: The core issue described is a resistance to uncertain processes (experimentation) and outcomes, which is more directly related to learning and ambiguity than interpersonal trust (4).

D. 2 and 3: The problem focuses on the team's internal approach to problem-solving (avoiding experiments) rather than their external focus on the customer's job (3), making continual learning (2) a more direct fit.

1. AXELOS, ITIL® 4 Specialist: High-velocity IT (2020), Section 3.2.5.1, Accept ambiguity and uncertainty: "In a complex environment, it is impossible to know everything up front... Waiting for a perfect solution is not an option... HVIT requires people to be comfortable with ambiguity and uncertainty." This directly contradicts the behavior of waiting for a "single correct solution."

2. AXELOS, ITIL® 4 Specialist: High-velocity IT (2020), Section 3.2.5.3, Commit to continual learning: "In a complex environment, it is often impossible to predict the outcome of an action. The only way to find out is to try it out. This is why experimentation is so important in HVIT." This directly addresses the problem of teams that "avoid experimentation."