This model should help to collect news from all over the world and put them into cause and effect relation to each other, and to the factors that define the economy, the societies, the environment, and everyone. Those factors we call targets, colored yellow. Whenever some interesting news pops up we may add further target factors to connect them with the central target of our all well being. The model should remain as general as possible. A small manual is provided with the Menu ... Presenter.
News could come from different sources, yet there should be just one factor for any specific topic. We can add other sources to the description texts of the factors and connections and soon (with iM-Document Manager) even documents and discussions.
When you add news see whether with similar words they aren't already included and just need to reference another source via their description text, and whether they can be connected to
- the benefit for the people in the rich and the poorer countries
- as a potential for businesses in the rich and the poorer countries
- with an effect on the environment or the use of resources
What is not explicit, yet, is the effect on the spending power. So far it is just wealth and the increase of prices for food and energy.
If possible, reflect with the four KNOW-WHY Questions on what leads to more or less of you new factor, now or in the future. Some aspect might already be in the model.
There are already some predefined categories. We may add additional ones for different purposes, e.g. for possible arguments that are not categorized, yet. Also categories can help to make distinctions e.g. between social inventions, energy technologies, e-mobility, etc. just to make it easier to get a list of factors from one specific field.
Right now factors have a quantitative attribute that could be used to note an estimation on how many percentage of a population e.g. currently use it or are influenced by it.
The weighting of the connection arrows should be based on the effect that a very high percentage would have. In the Insight Matrix the position of a factor shows the potential influence on different areas of our life. The diameter of a factor based on its quantitative attribute shows the likelihood or the current state of a development.
The time horizon should be
1 to 5 years short term,
5 to 15 years medium term, and
more than 15 years long term.
As the headline of this model is horizon scanning and megatrend forecast we can use categories to distinguish different factors as potentials, trends, megatrends, emerging trends, or similar.
Some trend's potentials are not just described by their direct connections to parts of the targets and their current dissemination. Rather their potential is revealed by the analysis of the interconnections, feedback loops and a critical thought on potential obstacles that add as factors to the mere collection of news. In other words: as already mentioned we should also ask the four KNOW-WHY-Questions for factors we find interesting. Don't be shy, give it a try ;-)
While the discussion tool coming with the iM-Document Manager is not ready, yet, we should directly communicate larger changes with the discussion on know-why.net. Smaller ones should simply be done as we expect this model to grow fairly large.
The model will be of increased relevance. At the beginning it is just a collection of some news. After a while you may search for news. Later, hopefully a community will start to reflect on more aspects. Only then a weighting of the connections and an allocation of attributes should follow so it is not just a source for information but a tool to analyze trends.
As all Open Source projects it depends on our willingness to invest some time and share something in order to get something in return later. The changelog rewards you by naming you as a contributor and possibly as an expert. Consider to use a real profile on KNOW-WHY.NET to establish yourself as an expert.
Finally some remarks on the benefits of this approach: Most approaches offer a variety of sometimes very convenient ways to collect news, usually by tagging the information. But once the amount of sources for each tag or a combination of tags grows it becomes extremely arduous to grasp or to just read through them not alone keep them updated and get rid of redundant information. With a cause and effect model we put all information into the context of cause and effect relations, not just content correlation. This is a major difference. News are translated into narratives. New information alters existing narratives or add to them or are simply additional sources for an existing narrative (the iMODELER will provide better functionality for this).
Please do not hesitate to ask for additional information or place your remarks via comments.
Sources (add your sources as well)
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