Finding solutions for invention problems is one of the most ancient human activity. In fact, the decision to pick up a stick and use it was the first innovative decision.
Paradoxically, the area of innovation continues to remain amazingly conservative: our ancestors needed thousands of years to invent the wheel. Today, as during a thousand years ago, at the heart of the technology of invention lies the trial and error method, based on sequentially proposing and considering all possible ways of solving a particular problem.
There are no search rules and no rules for the initial evaluation of an idea. This method is quite suitable for the solution of simple problems. However, if the solution is hidden among hundreds or thousands of possible variants, getting to the right answer can take years, or may be beyond one's reach.
Development of high technologies depends, first of all, on the appearance and implementation of fundamentally new ideas, processes, and products. These are frequently unbelievably complicated. Here, the classical trial and error method appears powerless.
How then should one resolve difficult, nontrivial problems? By lengthy reflection, sorting through all possible variants, expectation of inspiration on the basis of lucky guesses? These processes combine poorly with market requirements, and the necessity to manage projects and develop and release products within fixed time limits.
At various times, different scientists have attempted to address this problem.
More than 30 years ago, the Soviet scientist G. Altshuller developed a theory of invention management: "The theory of inventor's problem solving", TRIZ. He analyzed tens of thousands of patents and singled out the basic methods through which people used came to innovative ideas. The uniqueness of his technique was that he searched not for specific solutions, but patterns - ways of thinking - that lead to strong, effective decisions for various problems. As a result, he determined the 40 most typical ways to solve scientific research problems.
Many years later, our team, led by a talented young scientist, A. Tovchigrechko, similarly developed its own method. After analyzing some sections of cognitive psychology and experimentally collecting a base of most typical problem-solving methods, we have singled out 20 of the most probable ways to find solutions to complex problems in the field of computer algorithms development.
Our transition from finding solutions to separate problems to finding general methods that solve large groups of similar problems at once has turned out to be very fruitful. In recent years, we have repeatedly seen that our methods allow for the quick and in-depth study of any algorithmic problem and lead to elegant and effective decisions.
It should be noted that on projects, we do not use only our algorithmic problem-solving methods. Whenever necessary, we also use TRIZ, The Theory of Constraints, and Blue Ocean Strategy.
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