Description
Data-driven process redesign leverages AI to analyze current workflows and suggest comprehensive changes that can enhance productivity and efficiency in R&D operations. By using data from multiple sources such as project logs, time tracking, and performance metrics, machine learning models identify inefficiencies and propose optimized workflows. This approach can help organizations pivot away from outdated practices and adopt streamlined processes that align with current technological and business needs.
