Uncertainty management ()
PURI: http://data.europa.eu/2sa/elap/uncertainty-management Category: Digital Public Service Implementation Scope: Business agnostic Principle: Uncertainty management Statement: (Statement) Uncertainty management acknowledges the degree of confidence in decisions made during the analysis and design of Digital Public Services, arising from imperfect, unknown, or partial information. IoP Layer: Legal IoP, Organisational IoP, Semantic IoP, Technical IoP Principle Source: Hubbard Decision Research About source: The document titled "Decisions Under Uncertainty" by Hubbard Decision Research provides a comprehensive overview of probabilistic models and Monte Carlo methods for decision-making. It emphasises the importance of explicitly modelling uncertainty to improve decision outcomes. The document covers topics such as risk tolerance, the value of information, and the application of Applied Information Economics (AIE) to optimise decisions by focusing measurements where they matter most. PA Governance: Common Influence in DPS Implementation life-cycle: Desire Influence in implemented DPS attribute: Desire
elap:PURIhttp://data.europa.eu/2sa/elap/uncertainty-management
dct:titleUncertainty management
dct:description(Statement) Uncertainty management acknowledges the degree of confidence in decisions made during the analysis and design of Digital Public Services, arising from imperfect, unknown, or partial information.
dct:description(Rationale) Uncertainty management is crucial for recognising and managing the inherent limitations in knowledge and information. By acknowledging uncertainty, organisations can make more informed decisions, anticipate potential risks, and develop strategies to mitigate them. This principle helps improve the quality of problem descriptions and solutions by encouraging thorough analysis and consideration of various possible outcomes. Addressing uncertainty enhances the robustness and adaptability of Digital Public Services, ensuring they can effectively operate in partially observable or stochastic environments.
dct:description(Implications) Organisations must adopt practices that recognise and address the limitations in information and knowledge. Business processes should include thorough risk assessments and scenario planning to anticipate and mitigate potential uncertainties. Technically, solutions must be designed to be flexible and adaptable, capable of handling incomplete or evolving information. Continuous monitoring and feedback mechanisms are essential to update and refine solutions as new information becomes available.
elap:scopeBusiness agnostic
elap:CategoryDigital Public Service Implementation
dct:sourceHubbard Decision Research
dct:sourcehttps://hubbardresearch.com/wp-content/uploads/2020/07/Decisions-Under-Uncertainty-23-July-2020-PDF.pdf
rdfs:commentThe document titled "Decisions Under Uncertainty" by Hubbard Decision Research provides a comprehensive overview of probabilistic models and Monte Carlo methods for decision-making. It emphasises the importance of explicitly modelling uncertainty to improve decision outcomes. The document covers topics such as risk tolerance, the value of information, and the application of Applied Information Economics (AIE) to optimise decisions by focusing measurements where they matter most.
dcat:themeLegal IoP, Organisational IoP, Semantic IoP, Technical IoP
elap:paGovernanceCommon
elap:influenceInDPSLifecycleDesire
elap:influenceInDPSAttributeDesire