Tips
One of the key parts in working with foresight and a future related information is to make sense of it all. Mostly, what it means for your own business or given scenarios you have chosen to work with. It's not a problem to acquire the data or store it in data lakes and such, but the challenges come when trying to find those influential pieces of information from the mass. With vasts amounts of written data, it can be a painstaking job to figure out what piece of news may be affecting or should be linked to a given trend. Nowadays algorithms and technology can assist us and go way beyond just finding matching keywords or tags, they can suggest based on the written text which content could be related to one another, find the similarities or opposite arguments within the semantic context. It can all be very useful for horizon scanning and sense-making before diving deeper into the meaning of it all.
In this FIBRES tips, we show how you can discover and link trend related content together in a few clicks. In future, we are bringing even more intelligence "under the hood" to assist users working on their futures and strategy, more about that later though. (Psst. Don't have your own FIBRES yet...give it a try and sign-up here.)
Below are a few basic cases how to use FIBRES to find those new connections, but first a few basics:
This is typically used when evaluating new content on the platform, for example, to simply see what kinds of new observations and signals there could be that may form another trend. Maybe you wish to create a new signal cluster out of them for later sense-making and prepping a "deep-dive" session.
First, start out in 'Discovery'-section and choose a signal you wish to start working with. Click the "card" of the signal and you'll see a green check next to it. On the bottom of the screen, you'll see a choice 'Suggest Grouping', choose that and FIBRES will find and show suggestions that could be grouped together. Uncheck the signals that you don't need and carry on grouping the content, choose the type you wish to create (a signal cluster, trend or a workspace).
See a short video below.
[embed]https://youtu.be/fDG5y8c1ACw[/embed]
In the same way, this is a good tool while you are preparing the content for further analysis or a "deep-dive" session. Open a specific content you wish to work with and scroll down to the spot where you see related content. Then choose 'Suggest Linkages' to see what kind of content there is that might be good for linking. Then simply verify, select the ones and save. Simple!
If suggestions are not what you want to use, just search for those what you wish to link by clicking 'Add or Remove Linkages' instead. You'll see a list of the latest content in the platform, but notice, these are not "suggestions as such". Once you found what you were looking for, just save and you're ready to discuss all the linkages with others!
Here is another short video below.
[embed]https://youtu.be/LhvaGBbvroU[/embed]
Trend Network is a visualisation that shows exactly that. View all the trends and signal clusters in your FIBRES and see also the underlying linkages formed by signals. This is something that can be used for discovering something completely new too. View the map and start asking questions, "which trends are most connected", "what are the trends that aren't linked to anything yet"? Spot a start of a new growing trend perhaps?
The map itself is for simply viewing purposes, so it is best used as a tool when visualising the big picture. Use filters to highlight the content that matters and follow that to the Trend Radar, where you can show the hand-picked trends and their estimated impact.
[embed]https://youtu.be/agUN_qYcsLQ[/embed]
The suggestions work on the 'Roadmap' also. The principles are the same: simply use suggestions to see if there is something that is not been linked before but could be influential. An easy way to keep up-to-date with what insight your organization is building for strategic planning purposes.
Now, of course, could be a good moment to try the suggestions, check the visualizations and perhaps invite other colleagues to collaborate.
Until next time!
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