The paper presents the explicit and objective measurement method for innovation performances by using the extensive version of Analytic Hierarchy Process (AHP). A hierarchical framework is constructed for the innovation performance criteria and giving the guideline for innovation performance of companies. By applying AHP Expansion framework, the innovation performance measurement factors can be prioritized and descending-order rank list of the performance factors can be made in order to select the best strategies to improve the innovativeness of companies. This new framework of innovation measurement is targeted for implementation at the actual analysis for innovation competitiveness of companies and expected to provide the milestones of measuring the innovation more effectively. 1. Introduction Current corporate world understands that innovation is more evident and creating business value is the purpose of innovation. Global companies are focused on making innovation more understandable to be able to manage and improve their business because the companies are facing high competition because of endless globalization. The value of innovation can be considered in many different forms. Regardless of company size, modern companies are driven to survive and to grow. Finding the solution for the rapidly changing market which is to innovative effectively is the way to survive. But most of companies fail to sustain their innovativeness because they miss the critical parts of the equation: metrics and measurements. Innovation uncertainty principle means that the procedure to measure innovation of the company may interrupt the innovation process because innovation by itself involves venture for the unknown factors, and the company could make the unknown factors harder to realize or recognize if the company tries to pin these unknowns down too fast . The criteria to measure the innovation are the critical issue and several researches [2–7] suggest the framework of innovation metric criteria. Innovation can be viewed as having three distinct approaches. There are many alternatives for choosing the innovation metrics but three distinct approaches are appropriate approaches [2–5]. All three components should be measured thoroughly. The practical ways of measuring innovation differ highly from the metrics suggested by theory, through highly unbalanced and seemingly random metrics. There is a need for a framework on how to select which innovation metrics that an organization should use. The aim of creating this framework is to show that despite small changes of the
E. Triantaphyllou and S. H. Mann, “Using the Analytic Hierarchy Process for decision making in engineering applications: some challenges,” International Journal of Industrial Engineering: Applications and Practice, vol. 2, no. 1, pp. 35–44, 1995.