Vector algorithm
Simple Troublehacking algorithm that works though
the catalogue of inventive ideas of Troublehacking
the catalogue of inventive ideas of Troublehacking
TERMS
Vector Algorithm is a simplified Troublehacking method designed for invention of effective problem-solving solutions. It is based on associative thinking through the analysis of the Catalogue of Inventive Ideas.
Troublehacking Inventive Ideas Register is a structured set of ideas that provides "vector" for the increase of system development by a Troublehacker, i.e. maximum realization of the goal's core with minimum resources.
Troublehacking Inventive Ideas Register is a structured set of ideas that provides "vector" for the increase of system development by a Troublehacker, i.e. maximum realization of the goal's core with minimum resources.
VECTOR ALGRORITHM DESCRIPTION
1. Description a problem in simple form.
* What do you want and what stops you? What do you want to improve?
2. Goals core formula.
* Answer the question "what is being done?" for the goal (pursuing an objective or elimination of problems). In other words what should be being done (by you, others, systems) for you to be happy about the results. Without it the results are not sufficient.
* The most effective goal's core can be found in the past or future. To find it use root cause analysis. To analyze the past, ask "for what reason?". To analyze the future, ask "what's next?".
3. Choose category in the troublehacking ideas catalogue that suits your goal's core the most.
4. Choose ideas for the realization of your goal's core: the most original and potentially effective.
* In other words, "trying on" of the ideas from Troublehacking Ideas Catalogue for your goal's core. What ideas seem promising?
5. Invention of realization methods for each chosen idea in practice though answering the questions related to different life resources.
* Goal's cores realization options should answer the question "what is being done" (by me or others). In other words, we're compiling a task list.
6. Sorting of the list with goals core realization methods. Highlight the simplest for implementation (you can try to realize them with minimum expenses) and effective (the greatest anticipated result).
7. Solutions testing in life practice with minimum expenses.
*Try to implement few of them with minimum expenses (money, time, etc.) to find out which work. The testing should be implemented in the nearest future using self-motivation methods.
* Most of the time working results are most unusual, but to know this you have to exhaust many solutions in practice.
8. Scaling of the working solutions.
* If some solutions work we start to invest resources to achieve the maximum effect from the realization of the goal's cores.
* What do you want and what stops you? What do you want to improve?
2. Goals core formula.
* Answer the question "what is being done?" for the goal (pursuing an objective or elimination of problems). In other words what should be being done (by you, others, systems) for you to be happy about the results. Without it the results are not sufficient.
* The most effective goal's core can be found in the past or future. To find it use root cause analysis. To analyze the past, ask "for what reason?". To analyze the future, ask "what's next?".
3. Choose category in the troublehacking ideas catalogue that suits your goal's core the most.
4. Choose ideas for the realization of your goal's core: the most original and potentially effective.
* In other words, "trying on" of the ideas from Troublehacking Ideas Catalogue for your goal's core. What ideas seem promising?
5. Invention of realization methods for each chosen idea in practice though answering the questions related to different life resources.
* Goal's cores realization options should answer the question "what is being done" (by me or others). In other words, we're compiling a task list.
6. Sorting of the list with goals core realization methods. Highlight the simplest for implementation (you can try to realize them with minimum expenses) and effective (the greatest anticipated result).
7. Solutions testing in life practice with minimum expenses.
*Try to implement few of them with minimum expenses (money, time, etc.) to find out which work. The testing should be implemented in the nearest future using self-motivation methods.
* Most of the time working results are most unusual, but to know this you have to exhaust many solutions in practice.
8. Scaling of the working solutions.
* If some solutions work we start to invest resources to achieve the maximum effect from the realization of the goal's cores.
HISTORY
Vector algorithm was developed by Ilya Volochkov in 2019 specifically to adapt Troublehacking for people without technical thinking. Vector algorithm is an attempt to simplify Troublehacking and an attempt to make it accessible by anyone.