Decision Analysis and Portfolio Management in the Biopharma Industry

Richard Bayney is the President and Founder of Project & Portfolio Value Creation (PPVC), a specialized consulting boutique that delivers an integrated suite of services spanning executive education, decision-support analytics, asset valuation, and R&D portfolio strategy. PPVC's work is grounded in rigorous applications of Decision Analysis, Risk Analysis, and Portfolio Management, and is applied across multiple innovation-driven sectors, including Biopharmaceuticals, Medical Devices and Diagnostics, Consumer Care, and Agriculture. Through this work, Richard advises organizations on aligning scientific uncertainty, regulatory risk, and capital allocation with long-term strategic and commercial objectives. In parallel with his consulting practice, Richard has an extensive academic and professional speaking background. He has served as a lecturer at the University of Pennsylvania, where he taught graduate and executive courses in Decision Modeling and Project Portfolio Management. He is also a frequently invited speaker at industry forums, where he addresses topics such as decision and risk analysis, portfolio optimization, and strategic planning in drug development. Richard brings more than four decades of industry and consulting experience to his work. He is a 23-year veteran of the Biopharma industry, having held roles at Merck, Bayer, Bristol-Myers Squibb, and Johnson & Johnson. In addition, he has spent 18 years in management consulting, working primarily with clients in the United States and Europe. Over the course of his career, he has built and led functions in Strategic Planning, Decision Analysis, and Portfolio Management, and has hands-on operational experience, including two years as an international project manager for a marketed cardiovascular therapy. Earlier in his career, Richard spent a decade as a molecular biologist, conducting research on gene expression in drug detoxification systems and in the pathophysiology of Alzheimer’s disease. He has an M.Sc. and Ph.D. from the University of London, an MBA from Columbia University, and professional certification as a Project Management Professional (PMP) from the Project Management Institute. Jose Orellana is a Senior Business Consultant and Quantitative Solutions Engineer at Lumivero with over 25 years of experience applying numerical modeling to high-stakes decision making. As a globally recognized expert in the DecisionTools Suite (@RISK, PrecisionTree, Evolver) and XLSTAT, Jose has advised organizations worldwide on navigating the inherent uncertainties of complex R&D cycles. While his foundational expertise was forged in the demanding engineering environments of Schlumberger and P&G, his work now focuses on the “last mile” of decision analysis—the critical bridge between raw data and executive strategy. Leveraging a mastery of Python, machine learning, and traditional Monte Carlo simulation, Jose provides a robust framework for modeling the binary outcomes and long-tail risks characteristic of the pharmaceutical and life sciences sectors. Jose holds a B.S. in Electrical Engineering from Cornell University, where he graduated Magna Cum Laude and was inducted into the Tau Beta Pi and Eta Kappa Nu honor societies. His interdisciplinary approach is further bolstered by a Data Analytics certification from UC Berkeley and a Diploma of Management from the Australian Institute of Management. He currently resides in Perth, Western Australia, with his wife and two teenage daughters.

• Chapter 1: Drug Research and Development Within an Evolving Industry1.1 The Research & Development Funnel – The Impact of Risk, Cost, and Time to Productivity1.2 The Valley of Clinical Death1.3 The Stage Gate Review ProcessChapter 2: Scenario Analysis and Strategic Planning2.1 Scenario Analysis as a Strategic Instrument Under Uncertainty2.2 Core Concepts of Strategic Planning Under UncertaintyChapter 3: Decision Analysis and Portfolio Management3.1 Introduction to Decision Analysis and Its Utility in Decision Making3.2 Risk as a Quantitative Construct: Probability as the Common Language3.3 Uncertainty – The Language of Outcomes3.4 Decision Making Under Conditions of Risk and Uncertainty3.5 Decision Framing and Data Integrity3.6 Portfolio Management3.7 Portfolio Selection3.8 The Future of Enterprise Project Portfolio ManagementChapter 4: Project CategorizationChapter 5: Risk Analysis5.1 Conceptual Foundations of Risk and Uncertainty in Biopharmaceutical R&D5.2 Project Risk5.3 Program Risk5.4 Portfolio RiskChapter 6: Integrated Evaluation6.1 Key Financial Valuation Concepts6.2 Anatomy of a Decision Tree6.3 From Project Evaluation to Program Evaluation6.4 Sensitivity Analysis to Decision Tree Parameters6.5 Disease Sequencing: Maximizing Risk-adjusted Value for a Drug in Pursuit of Multiple Diseases6.6 Bayesian Revision and the Value of Information from Early Clinical Trials6.7 Integrated Valuation Based on Utility ValueChapter 7: Portfolio Optimization7.1 Key Concepts7.2 The Efficient Frontier in Portfolio Selection7.3 Application of Deterministic Single Objective Optimization for R&D Portfolio Selection7.4 Application of Deterministic Multiple Objective Optimization for R&D Portfolio Selection7.5 Application of Stochastic Optimization for R&D Portfolio SelectionChapter 8: Project Prioritization8.1 Comparison of Portfolio Selection by Prioritization and Optimization8.2 Prioritization in Research: Challenges, Tensions, and Emerging Practice8.3 A Matter of Weights – The Utility of AHPChapter 9: Best Practices in Portfolio Management9.1 Key Concepts9.2 Capability Maturity Model9.3 Roles and Responsibilities in Decision Analysis and Portfolio Management9.4 Portfolio Analysis and Presentation9.5 Risk Management9.6 Resource Management9.7 Stakeholder Management9.8 A Practical Approach to Improving Enterprise Portfolio Management CompetenciesChapter 10: Epilogue