Tags: Creativity Research · Systematic Innovation · Problem Solving · TRIZ
There is a scene early in The Innovation Algorithm where Altshuller quotes Nicola Tesla’s assessment of Thomas Edison: Edison, Tesla wrote, would not “lose time determining the most probable location” of a needle in a haystack — he would begin picking up straws one by one until he found it. “His methods were very inefficient. He would spend a lot of time and energy reaching nothing — unless luck was with him.” Altshuller uses this portrait not to belittle Edison, but to name the problem his life’s work was designed to solve: the overwhelming majority of inventive effort, however heroic, is organised around the wrong method.
That method is trial and error — what Altshuller calls the search along the Inertia Vector: the tendency of inventors to begin from what they already know and to push stubbornly in familiar directions, rarely breaking toward genuinely new solution spaces. The book’s central argument is that this is not an inevitable feature of human creativity. It is a correctable methodological failure — and correcting it requires not inspiration, but a science.
The Hierarchy of Inventive Difficulty
Before proposing his solution, Altshuller establishes why the problem is harder than it appears. He develops a taxonomy of five levels of inventive complexity that is one of the book’s most illuminating contributions. At Level One, solutions require no new principles — they draw on knowledge already available within a single specialist’s experience, and the number of trials needed rarely exceeds ten. At Level Five, the problem and its solution exist outside the boundaries of contemporary science: a new discovery must be made before invention becomes possible, and the search space runs to tens of thousands of trials or more.
The critical insight is that the psychological and cognitive tools appropriate to lower-level problems are not merely insufficient at higher levels — they are actively misleading. The brain, Altshuller argues, has been shaped by evolution to solve problems quickly using familiar patterns. For Level One and Two problems, this serves the inventor well. For Level Four and Five problems, the very fluency of this habitual thinking becomes the primary obstacle: “The tragedy of the inventing process is that people use methods for higher level problem solving that are relevant only to the lower levels.”
This is why Altshuller is sceptical not only of trial and error, but of the refinements proposed to improve it — brainstorming, morphological analysis, synectics, pilot question lists. Each of these methods, he argues, accelerates the search within an existing search space rather than redirecting it. Brainstorming, for instance, “doesn’t eliminate chaotic searching — in reality it makes searching even more chaotic.” The methods are better than nothing, but their ceiling is low: second-level problems, occasionally third.
Technical Contradictions and the Ideal Final Result
The architecture of Altshuller’s alternative rests on two foundational concepts.
The first is the technical contradiction. In Altshuller’s analysis, every significant inventive problem contains at its core a situation in which improving one parameter of a technical system necessarily degrades another. The conventional engineering response is compromise — the designer accepts a suboptimal balance and calls it the best available solution. Altshuller’s position is uncompromising: “The essence of inventive creativity is to find a way where compromise will not be needed.” The invention consists precisely in dissolving the contradiction rather than managing it. He supports this claim through an extensive catalogue of real engineering cases — aviation, shipbuilding, mining, electronics, optics — demonstrating that the pattern of contradiction is not the exception but the structural norm of inventive progress.
The second concept is the Ideal Final Result (IFR): the theoretical endpoint of a technical system’s development, in which the desired function is achieved with no additional apparatus, no costs, and no harmful side effects. The IFR is not a design specification but a directional beacon — it tells the inventor which way to search before the search begins, dramatically narrowing an otherwise unbounded problem space. “An ideal solution is a machine that does not exist — with the same result as if a machine did exist.” Altshuller illustrates this with memorable examples: in the icebreaker problem, the ideal ship would move through ice “as if the ice were not there”; in the sprinkler irrigation problem, the wings would “be suspended above the field by themselves.”
To navigate from stated contradiction to resolved IFR, Altshuller developed ARIZ (Algorithm of Inventive Problem Solving) — a structured, multi-stage analytical procedure that constitutes the book’s second section. ARIZ does not generate solutions mechanically; it progressively refines the problem formulation, eliminates unproductive directions, and focuses the solver’s attention on the specific physical or structural conflict at the problem’s core. The book traces the algorithm’s evolution across multiple versions (ARIZ-61 through ARIZ-71), presenting worked solutions to a series of concrete technical problems — icebreaker design, mine rescue equipment, wire winding on ferrite rings, oil pipeline separation — that demonstrate the procedure in action.
Supporting ARIZ is the Contradiction Matrix: a 39×39 table mapping pairs of conflicting engineering parameters to the most productive subset of 40 inventive principles for resolving them, derived from the analysis of over 40,000 patents. The principles themselves — segmentation, extraction, prior action, dynamicity, phase transition, inert environment, and so on — represent the distilled grammar of inventive solutions across engineering history.
The Psychological Dimension
The book’s third section, Man and Algorithm, addresses what Altshuller considers the deepest obstacle to systematic invention: not technical ignorance but psychological inertia. An inventor who knows the principles and understands the algorithm may still fail to use them, because the language in which a problem is stated carries hidden directives. “The real invention can only come when old terms, or their combinations, are given new contents.” Every technical term preserves the architecture of past solutions and quietly steers the solver away from conceptually new ones.
Altshuller identifies the mechanism with precision: inventors work through what he calls the Inertia Vector, beginning from the most familiar prototype and modifying it incrementally. The vector leads systematically away from the strongest solutions, which typically lie in directions the terminology of the problem has already foreclosed. The function of ARIZ, beyond its analytical steps, is to break this vector — to force the reformulation of problems in language stripped of technical assumptions, to surface contradictions that familiarity has made invisible, and to reorient the solver toward the Ideal Final Result rather than toward the nearest available improvement.
The final chapter develops what Altshuller calls ARIZ mind: the characteristic thinking style of an inventor trained in the methodology. It involves a tendency to push problems toward greater complexity before simplifying them; the willingness to pursue “fantastic” — apparently impossible — formulations of the IFR; the simultaneous perception of a technical system at the level of its components, its current form, and its evolutionary trajectory; and a progressive liberation from the constraints of specialisation. “Higher Level solutions (Fourth and Fifth) are almost always involved with stepping out of one’s own field of specialisation.” The algorithm, in other words, is not only a procedure for solving problems — it is a programme for developing a particular kind of mind.
The Argument’s Enduring Force
Altshuller’s own biography — arrested under Stalin, sentenced to the Gulag, continuing to develop TRIZ in the Varkuta coal mines while surviving through improvised applications of his own methodology — lends the book an authority beyond the purely intellectual. The theory was not developed in comfortable conditions. It was tested, repeatedly and under pressure, against real problems and real constraints.
For researchers and practitioners working in creativity, The Innovation Algorithm poses a challenge that deepens rather than diminishes with time. If the strongest inventive solutions cluster around a finite set of strategies for resolving structural contradictions — if the patterns of invention can be mapped, taught, and applied — then the question of whether creativity is a gift or a competence receives a definitive answer. Altshuller’s answer, argued over 250 pages with considerable rigour, is that it is a competence: learnable, improvable, and most powerfully expressed not in solitary inspiration but in the systematic deployment of accumulated human inventive knowledge.
Original source: Altshuller, G. (1999). The Innovation Algorithm: TRIZ, Systematic Innovation, and Technical Creativity. Worcester, MA: Technical Innovation Center.