"It can be hard to measure R&D progress or understand when to kill a project in order to free up resources for more promising items in the R&D portfolio. As a result, zombie projects with unclear status and milestones tend to linger, burning money, inflating total R&D costs, increasing time-to-market for worthwhile projects, and causing frustration all around. AI-based methodologies can improve R&D project prioritization and increase performance within individual projects, thus liberating budgets and raising overall efficiency. Failure rates of R&D projects to improve F1 car performance approach 90 percent."
"QuantumBlack, a firm specializing in advanced analytics, has successfully employed AI to streamline the R&D process and identify the most promising R&D projects early on. In part, it does this by pulling data from a wide variety of integrated sources and then using AI and machine learning to forecast factors that might detract from performance. Team dynamics are a key performance lever. Projects with a high level of interconnectedness should have high-intensity communications. By analyzing communications and discovering patterns, QuantumBlack can warn managers early on if a project seems to be off-track."
"AI and machine learning to forecast factors that might detract from performance".
"data from a wide variety of integrated sources"
Potential impact: QuantumBlack’s AI-based approach typically generates R&D productivity gains of 10 to 15 percent and accelerates time to market by 10 to 40 percent.