a new method for resolving design and manufacturing problems in new product development
Random, “lightning bolt” creativity may work for poets, but it won't help a manufacturer leapfrog over the competition. Here's a knowledge-based system that enhances team creativity.
Traditional views of creativity in product innovation assume that the ideation process is one of chance—an ad hoc, random discovery process. That traditional assumption needs to change. Creativity is not a purely intuitive process. Your team's ability to develop innovative products is not merely a matter of chance. Rather, creativity can be learned, encouraged, enhanced, and developed through the use of structured creativity methods. New techniques can help teams find high-level solutions to technical contradictions in new product development.
One technique, Systematic Innovation (also known as TRIZ or TIPS from the Russian and English acronyms for the Theory for Inventive Problem Solving) has helped teams to predict trends, develop product design features, and solve tough technical problems that do not involve tradeoffs in the quality of design or efficiency of production techniques. It is one way teams can increase the quantity and quality of promising solution concepts for solving technical problems.
In the current competitive climate, the ability to leapfrog, not just catch up with, the competition is increasingly more important. Thomas Edison had over 1,000 unsuccessful trials before inventing the incandescent light bulb. Few companies today can afford that level of investment in resources or in time-to-market to develop a new product or service. By using the methods of Systematic Innovation, solutions that are not likely to be successful can be screened out to reduce the number of trials required to prove a concept.
Definitions and History
Relatively new to the United States, Systematic Innovation is a knowledge-based system, not a theory, derived from the analysis of patents by Russian researcher G.S. Altshuller and his associates. Systematic Innovation (SI) is a set of methods and principles for examining technical problems that informs the design team of possible solution concepts from other industries and other sciences. Among them are standard solutions or principles that have been used to solve similar problems. Altshuller's study of patents began in the U.S.S.R. in the 1940s and included the study of patents all over the world. From this research, standard problems and standard solutions of the general technical system were developed and formulated into algorithms, principles, and standard approaches to solving technical problems along with forecasting the evolution of technical systems.
Barriers to the Process
By definition, new products do not yet exist and the risk of not being able to deliver the new product or service on time and within budget is much higher than for existing products and services. There are several points where a team can reach an impasse in the course of developing new products and services. The standstill can normally be attributable either to team problems (organizational, political, administrative) or to technical problems, such as a genuine lack of suitable options for manufacturing or design of the new product or service. When faced with technical problems, the team will look for the optimal solution, and may settle for a solution that is the “least painful,” or a tradeoff. This acceptance of tradeoffs occurs because engineers and scientists traditionally do not “challenge” accepted rules and natural laws. In fact, this “psychological inertia” is often seen as the sign of a level-headed and practical engineer. Time and budget pressures from the organization will often lead the team to accept the first solution that meets minimum criteria. This practice is known in Systematic Innovation as accepting the “harm” with the “good.” The goal of SI is “Ideality,” where the ideal system is one that delivers its output, but does not exist.
Design Problem. A bicycle manufacturer wanted to develop a new racing bike. The manufacturer knew that spoked wheels are the lightest in weight, but are difficult to manufacture and adjust, while solid wheels are easier to manufacture, but are too heavy for a racing bike. Choosing either solid or spoked wheels is accepting a less-than-optimum solution. The application of Systematic Innovation can yield another option that eliminates the undesirable features of the two obvious solutions while retaining the good features of the two original options.
A good feature of the spoked wheel (light weight) comes with an undesirable feature (difficult to manufacture). In the case of the solid wheel, the good feature (easy to manufacture) comes with an undesirable feature (heavy). This design dilemma can be reduced to a standard problem and stated as a “technical contradiction.” Improving the weight of the wheel (making it lighter using spokes) has the effect of deteriorating the ease of manufacture (spokes are harder to make). This situation is defined as a technical contradiction because improving one part of the wheel system degrades another part of the wheel system.
Solution. Systematic Innovation changed the original problem into a standard one by defining the technical contradiction(s). SI helps to solve this contradiction by substituting generic parameters (weight, strength) for the original design parameters. Contradictions between generic parameters point to principles that may eliminate the contradiction. The principle of segmentation—breaking the object into independent parts, increasing the number of parts, or making the object sectional—provided the breakthrough the designers needed. Through Systematic Innovation, the designers opted to make wheels using two thin discs under tension instead of spokes. The tension strengthened the discs and retained the light weight without increasing the difficulty of manufacture. Using the principles of invention suggested by Systematic Innovation prevented the team from pursuing less promising solution concepts.
It is also useful to look at all the contradictions in a design problem, i.e., improving the weight of the wheel could also deteriorate the strength of the wheel. For complex design problems there may be dozens of technical contradictions. By examining each pair of contradictions, a design team can systematically work through them and avoid tradeoffs. Often, a formal and careful definition of the problem is enough for the design team to solve it.
Other Components of Systematic Innovation
The bicycle wheel design example demonstrates the most basic components of Systematic Innovation: namely, principles, standard solutions to standard problems, and problem analysis. The designers used standard characteristics of standard problems to define the technical contradictions. More complicated problems require more detailed analysis, more sophisticated solutions and an ability to forecast the evolution of technical systems.
Evolution of Technical Systems: Forecasting for Competitive Advantage
The forecasting component of Systematic Innovation attempts to predict where technology will develop in a given technical system. For example, the pointer has evolved from a rigid stick to a laser beam. The pattern of evolution has been increasing flexibility—from a rigid stick with no hinges to the telescoping style (with many hinges), to a laser beam (the use of fields, i.e., light). The Swiss Army knife follows a different pattern, the monopoly cycle. It has evolved from a single blade to two scissors blades, to many blades, then consolidating the many into one “wrapped” unit. SI's forecasting methods allow the prediction of the next technical innovation—where your competitors are headed in their efforts to meet your customers' current and future needs. Not only do they enable you to improve the planning and timing of your R&D investments, they also help you to analyze and predict the speed and direction of your suppliers' technologies so you can match products with existing parts and processes. Perhaps best of all, you will delight your customers by offering solutions to problems they don't know they have—yet. ■
Ellen Domb, Ph.D., is president of the PQR Group in Upland, Calif., a consulting firm specializing in applying Total Quality Management. She has been a director of the Aerojet Electronic Systems Division with specific responsibility for TQM implementation.
Bob King is chairman/CEO of GOAL/QPC, a Methuen, Mass., not-for-profit management research, training and publishing organization. He is author of Better Designs in Half the Time: Implementing QFD in America and Hoshin Planning: the Developmental Approach.
Karen Tate, PMP, is president of The Griffin Tate Group, Cincinnati, Ohio, specializing in technical creativity and project management. She has been a project manager, senior construction engineer, and director of continuous improvement for two major consulting engineering firms.
PM Network • March 1996