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The Future is Here: How AI and ML are Revolutionizing Project Portfolio Management

Strategic portfolio management (SPM) is the process of making decisions about the selection and allocation of resources to achieve an organization’s strategies.  This involves balancing the organization’s investments to maximize their potential benefits, while considering cost, capacity and risk limitations.

In SPM, decisions have to take into account the organization’s immediate, medium and long-term goals. Achieving this requires a complete understanding of the organization’s demand to realize value aligned to strategic priorities, as well as production capabilities such as costs, time and risks associated with each project.

Now, Artificial Intelligence (AI) and Machine Learning (ML) are transforming the way organizations approach SPM.  AI and ML can bring capabilities and perspectives to decision making that go beyond traditional methods. Here are some of the things that AI and ML can do in decision making that are unique:

  1. Predictive Analytics: AI and ML can analyze large amounts of demand and production data, including project information and historical performance data, to make predictions about expected benefits, timelines, budgets, resource consumption.
  2. Prescriptive Analytics: Going beyond predictions, AI and ML driven prescriptive analysis can make recommendations for courses of action.  AI and ML can evaluate the infinite possibilities and prioritize projects while optimizing production capabilities.
  3. Performance Evaluation: AI and ML algorithms can also be used to evaluate project performance.  They can provide levels of transparency that have never before been possible, helping to understand not just what is happening, but also the causes.  Additionally, the ability for AI and ML to analyze large amounts of data helps ensure that the best information possible is feeding decisions, providing the most complete, accurate and timely information possible.
  4. Recognize decision making biases: AI and ML can help detect and reduce biases by monitoring decision makers behavior in real-time.  Biases, often unconscious, impact portfolio management, leading to suboptimal decisions.  AI and ML can detect biases around everything from anchoring bias, overconfidence and sunk cost to mental accounting.
  5. Automated decision making: AI and ML algorithms can be programmed to make decisions automatically based on pre-defined criteria.  This can help organizations automate routine decision-making processes.  This can allow organizations to use AI and ML to organize the project creation and selection processes, resource allocation, and management of phase activities.

In conclusion, AI and ML can bring unique capabilities to strategic portfolio processes and decision-making, analyzing huge amounts of data, reducing the impact of cognitive biases, improving decision accuracy, and enhancing the efficiency of the decision-making process.

Mike Gruia, Co-founder

Mike is a visionary leader in Portfolio Management, known for his deep knowledge and unique thinking. He grounds his approach in five fundamental pillars: economics principles, applied mathematics, business architecture concepts, system dynamics, and behavioral aspects. Recognized by industry experts, including Gartner, Mike is considered a pioneer in Portfolio Management. He has co-founded three companies specializing in Portfolio Management solutions, including UMT Consulting, a leader in the field before being sold to EY in 2015, and UMT360, sold to Teleo Capital in 2019. With degrees in Industrial & Systems Engineering and Operations Research from Columbia University and the Technion Israeli Institute of Technology, Mike has played an active role in shaping the evolution of Portfolio Management, challenging current practices, and anticipating future trends.