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Related Experiment Video

Updated: Jun 2, 2026

A Workflow for Lipid Nanoparticle (LNP) Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models (SVEM)

A Workflow for Lipid Nanoparticle (LNP) Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models (SVEM)

Published on: August 18, 2023

Value-driven ERM: making ERM an engine for simultaneous value creation and value protection.

John Celona¹, Jeffrey Driver, Edward Hall

¹Stanford Strategic Decision and Risk Management Certificate Program, Stanford, California, USA.

Journal of Healthcare Risk Management : the Journal of the American Society for Healthcare Risk Management

|April 21, 2011

Summary

Enterprise risk management (ERM) needs a new value-driven framework to address both value protection and creation. Decision analysis methods enable comprehensive risk coverage, integrating upside and downside risks for better organizational strategy.

Related Experiment Videos

Last Updated: Jun 2, 2026

A Workflow for Lipid Nanoparticle (LNP) Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models (SVEM)

A Workflow for Lipid Nanoparticle (LNP) Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models (SVEM)

Published on: August 18, 2023

Area of Science:

Business Management
Decision Science
Risk Management

Background:

Traditional enterprise risk management (ERM) focused on integrating disparate risk silos.
Growing recognition of the need to manage upside risks for value creation.
Existing tools like heat maps and risk registers are insufficient for comprehensive risk management.

Purpose of the Study:

To introduce a conceptually new, value-driven framework for ERM.
To enable enterprise-wide coverage of all risks, encompassing both value protection and creation.
To integrate decision analysis methodology into ERM.

Main Methods:

Developed a value-driven framework for ERM.
Integrated decision analysis methodology to capture systemic, correlated, and value-creation risks.
Applied the framework at Stanford University Medical Center.

Main Results:

The value-driven ERM framework effectively integrates upside and downside risks.
Decision analysis provides a robust method for assessing diverse risk types.
The approach facilitates a more holistic view of organizational risk.

Conclusions:

A value-driven ERM approach, enhanced by decision analysis, is necessary for modern risk management.
This framework addresses the limitations of traditional ERM tools.
Successful application at Stanford University Medical Center demonstrates practical utility.