How to Measure Anything in Project Management series with

oxford global projects

A Collaborative Training Experience for More Reliable, Measurable, and Realistic Project Forecasting

This evidence-based training series integrates Oxford Global Projects’ forecasting expertise with Hubbard Decision Research’s quantitative measurement methods to improve the accuracy and decision value of project forecasts under uncertainty.

Participants will learn to apply quantitative measurement and probabilistic forecasting methods that outperform expert judgment, even in complex projects with limited data. Hubbard Decision Research builds foundational measurement capability and probabilistic models using Bayes, regression, and scenario analysis to quantify and update cost and schedule uncertainty. Oxford Global Projects reinforces these methods through Reference Class Forecasting, using large empirical datasets to reveal hidden risks, bias, and the true drivers of project performance. Together, HDR and OGP deliver an evidence-based path from improved measurement to defensible forecasts and stronger project decisions.

This training series includes 7, 2-hour live workshops and 3 asynchronous training courses (21 training hours). Live workshops will be held on Tuesdays at 8:00AM US CDT (13:00 UTC) from April 28 to June 9.

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10 Course Bundle

Including 7 Live Workshops Presented by Hubbard Decision Research and Oxford Global Projects

Course 1 (LIVE)

How to Measure Anything in Project Management

April 28, 2026 8:00AM US CDT (2-Hours)

Presented By: Hubbard Decision Research

Learning Objectives

  • Understand the limitations of common project-management measurement methods (e.g., risk matrices)
  • Develop stronger approaches to thinking about project measurements and project risk
  • Apply course concepts to build a probabilistic model for evaluating project benefits, risks, and schedule
  • Identify key updates from Doug Hubbard’s How to Measure Anything in Project Management (co-authored with Oxford Global Projects’ Alexander Budzier and Andreas Bang Leed)

Course 2 (LIVE)

Reference Class Forecasting: Part 1

May 5, 2026 8:00AM US CDT (2-Hours)

Presented By: Oxford Global Projects

Learning Objectives

  • Explain the Reference Class Forecasting (RCF) process, including its empirical basis and the appropriate role of expert judgment

  • Interpret RCF curves and translate results into clear, stakeholder-ready insights

  • Understand how RCF addresses “unknown unknowns” and reduces optimism bias and the planning fallacy

  • Describe why RCF is widely regarded as the most accurate forecasting approach, supported by academic validation and Nobel Prize–winning theory

  • Summarize why governments such as the United Kingdom, Hong Kong, Denmark, and Ireland have adopted RCF as a standard planning method 

    Course 3 (LIVE)

    Reference Class Forecasting: Part 2

    May 12, 2026 8:00AM US CDT (2-Hours)

    Presented By: Oxford Global Projects

    Learning Objectives

    • Apply RCF insights to organizational performance data to improve forecast realism and decision quality
    • Use evidence-based reference classes to reduce bias in portfolio planning and investment decisions
    • Demonstrate how RCF de-risks projects early by informing scope, cost, schedule, and risk allocation
    • Evaluate proven outcomes from RCF adoption, including documented cost savings (e.g., Hong Kong’s reported GBP 1.5bn per year in avoided overruns)
    • Strengthen stakeholder and funder engagement through transparent, credible, and defensible planning discussions supported by RCF outputs
    • Build the case for RCF adoption across sectors, based on validated results in government and industry

      Course 4 (LIVE)

      Intro to Probabilistic Modeling Techniques

      May 19, 2026 8:00AM US CDT (2-Hours)

      Presented By: Hubbard Decision Research

      Learning Objectives

      • Understand the fundamental properties and rules of probabilities
      • Apply Bayes Theorem to update probabilities
      • Recognize use cases for the Beta distribution
      • Apply past data to make forecasts using regression models

      course 5 (LIVE)

      Crafting a Long-Term Project Evaluation and Forecasting Model

      May 26, 2026 8:00AM US CDT (2-Hours)

      Presented By: Hubbard Decision Research

      Learning Objectives

      • Understand how to incorporate uncertainty into project cost and schedule assessments using probabilistic methods

      • Create realistic risk scenarios and apply them across project phases to quantify potential impacts

      • Update and refine models throughout the project lifecycle as new information and performance data become available

      • Evaluate the effectiveness of risk mitigations and quantify their monetized benefit to support investment decisions

        Course 6 (LIVE)

        Advanced Decision Modeling and Project Optimization

        June 2, 2026 8:00AM US CDT (2-Hours)

        Presented By: Hubbard Decision Research

        Learning Objectives

        • Build progressively from foundational methods to more advanced, scalable project evaluation models that support complex decision environments.
        • Apply internal organizational data to calibrate and refine estimates over time, strengthening model accuracy and institutional learning.
        • Evaluate and incorporate industry data and reference class insights to improve forecast realism and benchmarking.
        • Examine intervention options and decision models while exploring how emerging AI capabilities and technology adoption influence project outcomes and potential tech regret.
        • Compare projects using a utility-based risk appetite framework to support prioritization decisions, including applications such as energy investment choices.
        • Recognize tools, techniques, resources, and services that strengthen forecasting capability and model execution, including example projects that combine calibrated estimates with Reference Class Forecasting.

        Course 7 (LIVE)

        Challenges, Solutions, and Next Steps: Q&A with HDR & OGP

        June 9, 2026 8:00AM US CDT (2-Hours)

        Presented By: Hubbard Decision Research and Oxford Global Projects

        Learning Objectives

        • Clarify participant questions and confirm key takeaways
        • Identify common challenges and their underlying drivers
        • Discuss practical solutions, methods, and recommendations
        • Define next steps by applying course concepts to participant-specific project scenarios and decision contexts

          3 Asynchronous Courses Delivered Through The AIE Academy

          Course 1:

          Calibrated probability assessments

          Presented by: Hubbard Decision Research

           

          Learning Objectives 

          • You will learn several techniques that have been measurably shown to improve forecasting
          • You will be able to apply these techniques in a series of calibration exercises to assess how calibrated you are before and after techniques.
          • You will learn how to incorporate your training performance to further improve your estimates.

          Course 2:

          Simulations in Excel: Basic

          Presented by: Hubbard Decision Research

           

          Learning Objectives

          • Learn the advantages of using a Monte Carlo simulation

          • Represent uncertainty for a wide variety of variables using existing functions in Excel

          • Use a flexible new pseudo-random number generator (PRNG) that generates large sets of random numbers for better auditable flexibility and standardization than current methods

          • Use key features of Excel to run thousands of scenarios in a streamlined and compact manner

          • Chart the output of the simulation in useful graphs to provide actionable insight for decision-makers.

          Course 3:

          Simulations in Excel: Intermediate

          Presented by: Hubbard Decision Research

           Learning Objectives

          • Use more advanced probability distributions, such as the lognormal, beta, and power law distributions.
          • Compute information value when you have a model with several variables.
          • Adjust your cash flows based on a stated risk tolerance. 

          Where OGP’s project-performance intelligence meets HDR’s proven techniques for measuring uncertainty and value.

          How to Measure Anything in Project Management Forecasting Expert Series: A collaborative approach that turns project benchmarks into actionable forecasts and better decisions

           

          Signups for the training are now live. Group discounts available.

          What you will get: 

          • 10 courses including 7 live and interactive courses presented by Hubbard Decision Research and Oxford Global Projects
          • 21 total hours of content and online activities
          • A full set of Excel-based power tools for analysis
          Enroll Now