What can be a consequence of excessive data latency in operational processes?

The consequence of excessive data latency in operational processes primarily results in delayed insights leading to poor decision-making. When data experiences significant latency, the information that decision-makers rely on becomes outdated or irrelevant by the time it is available for analysis. This can hinder organizations' ability to respond to emerging trends, address operational inefficiencies, or capitalize on market opportunities effectively.

In environments where timely information is critical, such as finance, healthcare, or supply chain management, any delay can lead to missed opportunities or suboptimal responses to challenges. As a result, stakeholders may make decisions based on outdated information, adversely affecting the overall performance and strategic direction of the organization.

In contrast, factors like increased accuracy of predictive analytics, more streamlined data management, and improved user satisfaction are likely not direct consequences of excessive data latency. In fact, those outcomes are generally associated with well-timed and efficiently managed data systems.