Operational Resilience Simulation for Variable Severity and Recovery

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Solution Overview

Problem

Existing business continuity planning systems fail to account for varying levels of severity and recovery times of adverse events, leading to inadequate preparation and resource allocation.

Innovation Solution

A method and system for business continuity simulation that utilizes a scenario repository to analyze infrastructure element objects, applying filters, Monte Carlo processing, and loss value rules to estimate potential impacts and recovery times across a range of event severities, considering prophylactic measures and operational levels.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If automated business continuity planning tools process assets against specified scenarios, then the production of asset exposure manifests is improved, but the ability to account for varying levels of severity and recovery times deteriorates

Engineering Contradiction:

Improveautomation of business continuity planningVSAvoidaccounting for varying severity and recovery times

Core Design Contradiction:

Extent of automationVSAdaptability or versatility

Solution Approach 1:

The system dynamically adjusts simulation parameters including severity levels and recovery times based on the specific adverse event scenario. The simulation engine modifies susceptibility values and recovery time distributions according to the selected event type and its impact characteristics, enabling the automated system to adapt to varying conditions without manual intervention.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The invention changes key parameters such as susceptibility values, recovery time distributions, and loss calculations based on the selected adverse event scenario. The system adjusts these parameters dynamically during simulation to accurately reflect the varying severity and recovery characteristics of different event types, resolving the contradiction between automation and adaptability.

Inventive Principle:

Principle #35Parameter changes

2Adaptability or versatility

If manual business continuity planning processes are used, then the ability to consider varying severity levels is improved, but productivity deteriorates

Engineering Contradiction:

Improveconsideration of varying severity levelsVSAvoidplanning process efficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system performs self-service simulation by automatically executing scenario analysis without requiring manual analyst intervention. The simulation engine independently processes adverse event scenarios, calculates susceptibility values, determines recovery times, and generates loss estimates, thereby maintaining high adaptability while dramatically improving productivity compared to manual processes.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The invention replaces manual mechanical planning processes with an automated computer-based simulation system. The mechanical process of manually analyzing scenarios and calculating impacts is substituted with electronic computation, enabling the system to consider varying severity levels through algorithmic processing rather than human analysis, thus improving both adaptability and productivity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Reliability

If recovery time is reduced for critical infrastructure elements, then operational resilience is improved, but cost increases

Engineering Contradiction:

Improveoperational resilienceVSAvoidrecovery cost

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system changes the parameter of recovery time based on the criticality and susceptibility of infrastructure elements. By dynamically adjusting recovery time parameters according to the simulated adverse event scenario and the specific element's characteristics, the system optimizes the balance between operational resilience and recovery cost without using fixed timeframes.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The recovery time parameter is made dynamic rather than static, allowing the system to adjust recovery time requirements based on the simulated scenario's severity, the infrastructure element's criticality, and the cost implications. This dynamic adjustment enables optimization of the resilience-cost tradeoff for each specific situation.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS20250335861A1Operational resilience scenario simulation

Publication Date: 2025.10.30 FUSION RISK MANAGEMENT INC

AI summary

Simulation for business continuity includes querying a scenario repository for a specific adverse event and responding to the query by selecting and retrieving from the repository infrastructure element objects that are associated with the specific adverse event. The simulation executes a Monte Carlo scenario test of the infrastructure element objects across a range of the susceptibility values through the computation of an average of the susceptibility values for each infrastructure element object for randomly selected different degrees of severity of the event. The simulation additionally executes a recovery simulation of the infrastructure element objects across a range of recovery times by computing an average recovery time for each infrastructure element object amongst the range of the recovery times. Finally, the simulation includes applying one or more loss value rules to the scenario tested and recovery simulated infrastructure element objects in order to produce a loss estimate for the target environment.