Q3 Scenario - definição. O que é Q3 Scenario. Significado, conceito
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O que (quem) é Q3 Scenario - definição

A STRATEGIC PLANNING METHOD THAT SOME ORGANIZATIONS USE TO MAKE FLEXIBLE LONG-TERM PLAN FOR DECISION MAKERS
Scenario analysis; Scenario thinking; Scenario building; Scenario Method; Scenario Prediction; Scenario prediction; Scenario planner
  • Process for classifying a phenomenon as a scenario in the Intuitive Logics tradition.

Scenario planning         
Scenario planning, scenario thinking, scenario analysis, scenario prediction and the scenario method all describe a strategic planning method that some organizations use to make flexible long-term plans. It is in large part an adaptation and generalization of classic methods used by military intelligence.
Scenario testing         
SOFTWARE TESTING USING SCENARIOS (HYPOTHETICAL STORIES TO HELP THE TESTER WORK THROUGH A COMPLEX TEST SYSTEM)
Test scenario; Scenario test
Scenario testing is a software testing activity that uses scenarios: hypothetical stories to help the tester work through a complex problem or test system. The ideal scenario test is a credible, complex, compelling or motivating story; the outcome of which is easy to evaluate.
Scenario (computing)         
NARRATIVE OF FORESEEABLE INTERACTIONS OF USER ROLES AND THE TECHNICAL SYSTEM, WHICH USUALLY INCLUDES COMPUTER HARDWARE AND SOFTWARE
User scenario; User scenarios
In computing, a scenario (, ; borrowed from Italian scenario (), derived from Latin scena, meaning "scene"etymonline.com) is a narrative of foreseeable interactions of user roles (known in the Unified Modeling Language as 'actors') and the technical system, which usually includes computer hardware and software.

Wikipédia

Scenario planning

Scenario planning, scenario thinking, scenario analysis, scenario prediction and the scenario method all describe a strategic planning method that some organizations use to make flexible long-term plans. It is in large part an adaptation and generalization of classic methods used by military intelligence.

In the most common application of the method, analysts generate simulation games for policy makers. The method combines known facts, such as demographics, geography and mineral reserves, with military, political, and industrial information, and key driving forces identified by considering social, technical, economic, environmental, and political ("STEEP") trends.

In business applications, the emphasis on understanding the behavior of opponents has been reduced while more attention is now paid to changes in the natural environment. At Royal Dutch Shell for example, scenario planning has been described as changing mindsets about the exogenous part of the world prior to formulating specific strategies.

Scenario planning may involve aspects of systems thinking, specifically the recognition that many factors may combine in complex ways to create sometimes surprising futures (due to non-linear feedback loops). The method also allows the inclusion of factors that are difficult to formalize, such as novel insights about the future, deep shifts in values, and unprecedented regulations or inventions. Systems thinking used in conjunction with scenario planning leads to plausible scenario storylines because the causal relationship between factors can be demonstrated. These cases, in which scenario planning is integrated with a systems thinking approach to scenario development, are sometimes referred to as "dynamic scenarios".

Critics of using a subjective and heuristic methodology to deal with uncertainty and complexity argue that the technique has not been examined rigorously, nor influenced sufficiently by scientific evidence. They caution against using such methods to "predict" based on what can be described as arbitrary themes and "forecasting techniques".

A challenge and a strength of scenario-building is that "predictors are part of the social context about which they are trying to make a prediction and may influence that context in the process". As a consequence, societal predictions can become self-destructing. For example, a scenario in which a large percentage of a population will become HIV infected based on existing trends may cause more people to avoid risky behavior and thus reduce the HIV infection rate, invalidating the forecast (which might have remained correct if it had not been publicly known). Or, a prediction that cybersecurity will become a major issue may cause organizations to implement more secure cybersecurity measures, thus limiting the issue.