Open Source Horizon Scanning Trend Forecast Foresight Model (1)

Welcome to the open source collaborative horizon scanning model on know-why.net. This model should help to collect and connect inventions, trends, findings from all over the world in order to forecast potential trends. The model is going to grow really big and improve over time. Here, with the presenter, I would like to provide a guidance on how to use the model. First you should know that the central target of the model is "People's well being". From there the model diversifies into different areas, mostly targets (yellow) that get more and more detailed as we need them. For example right now it is just the rich world and the poor world. If you want to add a trend, social invention, etc. that is only for a specific region feel free to restructure the targets. If you shy away from this leave a post on know-why.net describing the information you want to add to the model and someone else might help inserting it.

So let us see how it works. Maybe you have read on trendwatching.com that there is going to be trend from Asia that let people make contacts in social media they see as practical peers that help them to exchange rather practical than personal things, e.g. information, tools, products, accommodation, etc.

First, you decide where to add and connect a factor to the existing model. You may navigate to the "well being in the rich world" (click on the factor and than on the button on its right). From there you will probably find an area where your new information can get connected to, e.g. "cultural activities/leisure in the rich world".

Once you have change to view the model from the perspective of "cultural activities ...." you may find out that you miss a factor that you can connect you information with. Here I added "traveling in the rich world" and chose via the factor's properties (click on the factor and then the "i" button) the category "target" that comes with the color yellow for it.

After that I added the new factor and chose via its properties the category "trend". Don't forget to link the source for you information in the description text of the factor's properties. Also you may decide to attach further categories to the factor, e.g. "leisure" and "mobility" or any new one you think that is feasible.

Next you should consider to connect your information to more areas. Quite often you can connect it to business potentials. Also it might have a direct or indirect effect on the environment and the use of resources. Feel free to add additional factors as you need them. Put them as less specific as you can so they can be reused to connect other information as well. For example you shouldn't name a factor "sharing of a hammer" if "sharing of tools and gadgets" also suits.

So far the major aim of the model is to put inventions, products, scientific findings, behavior, social, environmental and political developments into cause and effect relations. As the model grows we can add further information to each factor via its description texts or via additional factors. If several factors combined describe a trend or megatrend, we can name this trend via a category that we assign to these factors. That makes it possible to choose a clustered view (Menu ... Filter/Cluster) of the factors.

The qualitative modeling features of the iMODELER allow for a weighting of the connections and an analysis of the model via Insight Matrices. They will make perfectly sense once we add all kind of arguments to the factors, e.g. a negative influence of a growing fear of data fraud.

We may even add attributes to the factors via their properties to estimate the current state / spread of something. The Insight Matrix of any factor from the model then shows how this is influences by other factors. The position show the potential strength of the factor's influence, the diameter of the cycles the current state. In this example "Toxic materials in 3D printers" have a slightly negative impact and the current state is that nearly all printers use toxic materials.
Of course, in order to gain valid insights from the matrices we need to weight all the connections properly. So please be careful interpreting early results.

Just another example

An alternative view of the insight matrix. The results will change once the connections within the model are properly weighted.

Once you are done please return to the central target to make it easier for others to navigate to the area where they want to add their information.
Please make use of the discussion thread on know-why.net. Very soon we will add additional discussion features and a document manager to the iMODELER to make this open source model even more productive.