Project portfolio management (PPM) is a strategic approach to managing a collection of projects, programs, and operations to achieve strategic objectives. It can be a powerful tool to reduce the risks associated with using numerical models to select projects. Here’s how:

1. Define Clear Objectives and Criteria:

• Align with Strategy: Ensure that the numerical model’s criteria are aligned with the organization’s overall strategic goals.
• Weighting: Assign appropriate weights to different criteria based on their importance to achieve strategic objectives.

2. Identify and Assess Risks:

• Model Limitations: Recognize the limitations of numerical models, such as assumptions, data quality, and potential biases.
• Scenario Analysis: Consider different scenarios and their potential impacts on project outcomes.
• Sensitivity Analysis: Test the model’s sensitivity to changes in input variables.

3. Develop a Robust Portfolio:

• Diversification: Create a diversified portfolio that balances risk and return, considering factors like project type, industry, and geographic location.
• Resource Allocation: Allocate resources effectively to projects based on their strategic importance and risk profile.

4. Monitor and Control:

• Performance Metrics: Establish key performance indicators (KPIs) to track project progress and identify potential risks.
• Regular Reviews: Conduct regular reviews to assess the effectiveness of the numerical model and make necessary adjustments.
• Contingency Planning: Develop contingency plans to address potential risks and uncertainties.

5. Continuous Improvement:

• Learn from Experience: Analyze past project outcomes to identify lessons learned and improve the numerical model.
• Update Model: Regularly update the numerical model to reflect changes in the business environment and strategic priorities.

Specific Techniques to Reduce Risks:

• Sensitivity Analysis: Test the model’s sensitivity to changes in input variables to identify critical factors that could significantly impact project outcomes.
• Scenario Planning: Consider different scenarios (e.g., optimistic, pessimistic, most likely) to assess the potential range of outcomes.
• Risk Assessment Matrices: Use tools like risk assessment matrices to prioritize risks based on their likelihood and impact.
• Decision Trees: Visualize decision-making processes and potential outcomes to evaluate alternative options.
• Monte Carlo Simulation: Use statistical techniques to simulate different potential outcomes based on probability distributions of input variables.

By following these steps and incorporating specific techniques, organizations can significantly reduce the risks associated with using numerical models to select projects and make more informed decisions.