Evaluation of the Effectiveness of Modern TRIZ Based on Practical Results in New Product Development

  • Oleg Y. AbramovEmail author
  • Alexander V. Medvedev
  • Vladimir Y. Rychagov
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 572)


Today’s innovation processes used in industry are generally inefficient: various sources indicate that only one out of three-thousand, raw ideas yield a commercial product. Fortunately, most of the ideas are quickly rejected before much time and money are spent on their development. Still, approximately 300 of the raw ideas are normally selected for further investigation and development, which results in launching around 125 small pilot projects and in other time and money-consuming activities – all for the sake of a single commercially successful product. TRIZ-practitioners claim a much higher efficacy with the TRIZ-based innovation process because TRIZ provides a more systematic approach for innovation and dramatically speeds up the new product development (NPD) process. A number of case studies using TRIZ for NPD back up this statement; however, there is so far no solid quantitative data available to support this statement. In this paper, the authors have tried to evaluate the effectiveness of modern TRIZ in NPD by analyzing a pool of technical solutions for new products developed for different companies in actual TRIZ-consulting projects. For each solution, the authors have tried to identify whether the new product was ultimately launched. This analysis revealed the number of solutions/ideas that TRIZ consultants developed in order to launch one new product and the percentage of successful projects. The results show that using TRIZ improves the efficiency of the NPD process from about 5 to 12 times, which confirms that TRIZ brings high value to NPD.


Innovation funnel New product development NPD Quantum Economic Analysis QEA TRIZ 



The authors would like to thank Deborah Abramov for her helpful comments and for editing this paper.


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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.Algorithm Ltd.St. PetersburgRussia

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