Vision
Vision
Embedded Files
Conflicting interests
Conflicting interests
"And if we are to live together and not die together, we should learn the kind of tolerance which is absolutely vital to the continuation of human life on this planet."
Bertrand Russell
We believe in the intensive employment of multi-objective optimization (MOO) as a way to help building the necessary consensus between parties that allows reaching agreement. Once each stakeholders' interests have been properly recognized, MOO yields a set of compromise-solutions capable of meeting the needs of the various stakeholders.
We codify our models so that each solution provided conveys a different strategy, representing each stakeholder's best responses to other stakehpolders' demands. The analysis of this information allows us to identify equilibriums between objectives, and to delineate regions of convergence between interests.
Based on this we can build bridges signifying common interests, and progressively approach a situation of understanding from which solutions affording an acceptable level of satisfaction for all the involved parties may be drawn.
Increased understanding among parties due to the improved knowledge on problem dynamics provided by analysing interests' trade-offs
Approach to agreement through the delimitation of the space of solutions containing agreement opportunities
Uncertainty
Uncertainty
"Uncertainty, in the presence of vivid hopes and fears, is painful, but must be endured if we wish to live without the support of comforting fairy tales."
Bertrand Russell
In the real world, full of complexity and uncertainties, we can not predict the future, but we can be ready and know how to adapt. By incorporating uncertainty in our decision support systems, we put into question all the assumptions embodied in the operational models we design.
Instead of using a deterministic approach with our assumptions, we prefer to be realistic, accepting that there are uncertainties, and to incorporate them by means of probability distribution functions.
This way, we overcome the limitations of an scenarios' narrow-minded, ex-ante definition, as well as we avoid falling into eventual narrative fallacies. As a result, our analysis cover practically all possible situations, identifying which scenarios, due to their impact and probability, are especially relevant.
Based on an adequate identification of the relevant scenarios, we propose strategies keeping safe from undesired outcomes, while they allow taking advantage of eventually favorable contexts, thus contributing to your project's success
Risks and Opportunities
Risks and Opportunities
"I initially used the image of the barbell to describe a dual attitude of playing it safe in some areas (robust to negative Black Swans) and taking a lot of small risks in others (open to positive Black Swans*), hence achieving antifragility."
* Black Swan: Improbable, yet possible extreme event
N. Taleb
The D-ROSE (Simultaneous Evaluation and Dynamics of Risks and Opportunities) method allows an ex-post selection, according to the adopted risk profile, of a set of relevant scenarios and then to evaluate the risks and opportunities that, for different strategies, they represent .
In this way, we reveal hidden risks, and identify which strategies protect you from unfavorable situations, and at the same time allow you to take advantage of eventual opportunities.
D-ROSE in the search for strategic plans being robust to risks, and sensitive to opportunities
Relational Uncertainty
Relational Uncertainty
With the Relational and Multi-scale Risks and Opportunities (Ms-ReRO) assessment method, we can analyze the relational uncertainty attached to the organizational structure of a complex system, and determine the risks and opportunities for improvement associated with different organizational configurations.
In Mgnesio, we rely on the concept of Systems System (SoS) to model operations with complex inner relationships. In this way, we can simulate multi-scale and decentralized operative structures, and evaluate the response of the system to changes in the state of each sub-system.
Once the model is obtained, our optimization methods allow us to find-out organizational strategies with an adequate balance of risks and opportunities to, for example, design strategies for the implementation of construction, or maintenance, integral plans in urban, infrastructure or industrial decentralized systems.
Employment of Ms-ReRO to analyse policy measures for accompanying the deployment of urban infrastructure strategic plans
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