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In the modern knowledge-based and digital economy, the value of knowledge is growing relative to other assets and new intellectual property is being created at an ever-increasing rate. Therefore, the ability to find non-trivial solutions, systematically generate new concepts, and create intellectual property rapidly become crucial to achieving competitive advantage and leveraging the intellectual potential of organizations.
Cross-industry innovation is commonly understood as identification of analogies and interdisciplinary transfer or copying of technologies, processes, technical solutions, working principles or models between industrial sectors. In general, creative thinking in analogies belongs to the efficient ideation techniques. However, engineering graduates and specialists frequently lack the skills to think across the industry boundaries systematically. To overcome this drawback an easy-to-use method based on five analogies has been evaluated through its applications by students and engineers in numerous experiments and industrial case studies. The proposed analogies help to identify and resolve engineering contradictions and apply approaches of the Theory of Inventive Problem Solving TRIZ and biomimetics. The paper analyses the outcomes of the systematized analogies-based ideation and outlines that its performance continuously grows with the engineering experience. It defines metrics for ideation efficiency and ideation performance function.
The paper is addressing the needs of the universities regarding qualification of students as future R&D specialists in efficient techniques for successfully running innovation process. It briefly describes the program of a novel one-semester-course of 150 hours in new product development and inventive problem solving with TRIZ methodology, offered for the master students at the Beuth University of Applied Sciences in Berlin. The paper outlines multi-source educational approach, which includes a new product development project (about 50% of the complete course), theory, practical work, self-learning with the software tools for computer-aided innovation, and demonstrates examples of the students work. The research part analyses the learning experience, identifies the factors that impact the innovation and problem solving performance of the students, and underlines the main difficulties faced by the students in the course. It describes a method for measurement of education efficiency and compares the results with educational experience in the industry. The presented results can help universities to establish the education in new product development or to improve its performance.
Using patent information for identification of new product features with high market potential
(2014)
CONTEXT
The paper addresses the needs of medium and small businesses regarding qualification of R&D specialists in the interdisciplinary cross-industry innovation, which promises a considerable reduction of investments and R&D expenditures. The cross-industry innovation is commonly understood as identification of analogies and transfer of technologies, processes, technical solutions, working principles or business models between industrial sectors. However, engineering graduates and specialists frequently lack the advanced skills and knowledge required to run interdisciplinary innovation across the industry boundaries.
PURPOSE
The study compares the efficiency of the cross-industry innovation methods in one semester project-oriented course. It identifies the individual challenges and preferred working techniques of the students with different prior knowledge, sets of experiences, and cultural contexts, which require attention by engineering educators.
APPROACH
Two parallel one-semester courses were offered to the mechanical and process engineering students enrolled in bachelor’s and master’s degree programs at the faculty of mechanical and process engineering. The students from different years of study were working in 12 teams of 3…6 persons each on different innovation projects, spending two hours a week in the classroom and additionally on average two hours weekly on their project research. Students' feedback and self-assessments concerning gained skills, efficiency of learned tools and intermediate findings were documented, analysed, and discussed regularly along the course.
RESULTS
Analysis of numerous student projects allows to compare and to select the tools most appropriate for finding cross-industry solutions, such as thinking in analogies, web monitoring, function-oriented search, databases of technological effects and processes, special creativity techniques and others. The utilization of learned skills in practical innovation work strengthens the motivation of students and enhances their entrepreneurial competences. Suggested learning course and given recommendations help facilitate sustainable education of ambitious specialists.
CONCLUSIONS
The structured cross-industry innovation can be successfully run as a systematic process and learned in one semester course. The choice of the preferred working teqniques made by the students is affected by their prior knowledge in science, practical experience, and cultural contexts. Major outcomes of the students’ innovation projects such as feasibility, novelty and customer value of the concepts are primarily influenced by students’ engineering design skills, prior knowledge of the technologies, and industrial or business experience.
The comprehensive assessment method includes 80 innovation performance parameters and 10 key indicators of innovation capability, such as innovation process performance, innovating system performance, market and customer orientation, technology orientation, creativity, leadership, communication and knowledge management, risk and cost management, innovative climate, and innovation competences. The cross-industry study identifies parameters critical for innovation success and reveals different innovation performance patterns in companies.
The paper conceptualizes the systemic approach for enhancing innovative and competitive capacity of industrial companies (named as Advanced Innovation Design Approach – AIDA) including analysis, optimizations and further development of the innovation process and promoting the innovation climate in industrial companies. The innovation process is understood as a holistic stage-gate system comprising following typical phases with feedback loops and simultaneous auxiliary or follow-up processes: uncovering of solution-neutral customer needs, technology and market trends, identification of the needs and problems with high market potential and formulation of the innovation tasks and strategy, idea generation and problem solving, evaluation and enhancement of solution ideas, creation of innovation concepts based on solution ideas, evaluation of the innovation concepts as well as implementation, validation and market launch of chosen innovation concepts. The article presents the current state of innovation research and discusses the actual status of innovation process in the industrial environment. It defines the future research tasks for amplification of the innovation process with self-configuration, self-optimization, self-diagnostics and intelligent information processing and communication.
The internal crowdsourcing-based ideation within a company can be defined as an involvement of its staff, specialists, managers, and other employees, to propose solution ideas for a pre-defined problem. This paper addresses a question, how many participants of the company-internal ideation process are required to nearly reach the ideation limit for the problems with a finite number of workable solutions. To answer the research question, the author proposes a set of metrics and a non-linear ideation performance function with a positive decreasing slope and ideation limit for the closed-ended problems. Three series of experiments helped to explore relationships between the metric attributes and resulted in a mathematical model which allows companies to predict the productivity metrics of their crowdsourcing ideation activities such as quantity of different ideas and ideation limit as a function of the number of contributors, their average personal creativity and ideation efficiency of a contributors’ group.
The effective executing innovation projects requires multiple estimation of market success of new product features in the early stages of customer-centered innovation process such as strategy formulation, evaluation of ideas and concepts and also at a stage close to the market launch. The attempts to integrate customers for estimation of the market success often result in time-consuming customer interviews or lengthy field research. For this reason, industrial companies usually try to skip customer surveys even if they risk that their innovations will fail to bring the anticipated economic outcomes. In many practical cases, the customer surveys are simply not feasible or too expensive. As a result, the internal assessments within companies are frequently the only resource available in innovation process in the industrial environment. The paper discusses the possibilities of the fast identification of promising innovation opportunities and new product features based on the internal competences of companies. It compares the results of customer surveys with the estimation of internal company-experts and analyses the accuracy and validity of the expert assessments. The presented case studies demonstrate the accuracy rate between 43% and 77% for prediction of new product features with high market potential by company-internal experts. The paper proposes the evaluation methods to increase the accuracy rate and outlines that one of the essential requirements for reliable forecasting by the experts is their profound understanding of the customer working process, the ability to estimate the importance of customer needs and to assess the level of customer satisfaction with current products on the market.