Product and service innovations are the result of mutually interacting creative and coordination tasks within a system that has to balance technical decisions, marketplace taste, personnel management, and stakeholder commitment. The constituent elements of such systems are often scattered across multiple firms and across the globe and constitute a complex system consisting of many interacting parts.

In the spirit of the "butterfly effect," metaphorically describing the sensitivity to initials conditions of chaotic systems, this book builds an argument that "innovation butterflies" can, in the short term, take up significant amounts of effort and sap efficiencies within individual innovation projects. Such "innovation butterflies" can be prompted by external forces such as government legislation or unexpected spikes in the price of basic goods (such as oil), unexpected shifts in market tastes, or from a company manager's decisions or those of its competitors. Even the smallest change, the smallest disruption, to this system can steer a firm down an unpredictable and irreversibly different path in terms of technology and market evolution.

In the long term, they can shift the balance of the entire innovation portfolio into unplanned directions. More importantly, we describe how innovation leaders can influence the emergent behavior of the system for good or ill.

The first half of the book draws parallels from physics, economics, and sociology as well as evidence from multiple industries to describe the structural and behavioral causes of emergent phenomena in innovation settings as well as their often negative impacts. In the second half of the book, we turn to distributed management of innovation under emergence. We show that innovation butterflies, if improperly managed, most often lead to negative outcomes. On the other hand, it is also argued that while the complexity of the innovation system and the desire to experiment and try new and emergent alternatives precludes precise planning, innovation leaders can actually tame innovation butterflies through the design and implementation of appropriate processes, strategies, tools and leadership choices.

Product and service innovations are the result of mutually interacting creative and coordination tasks within a system that has to balance technical decisions, marketplace taste, personnel management, and stakeholder commitment. The constituent elements of such systems are often scattered across multiple firms and across the globe and constitute a complex system consisting of many interacting parts. In the spirit of the "butterfly effect", metaphorically describing the sensitivity to initials conditions of chaotic systems, this book builds an argument that "innovation butterflies" can, in the short term, take up significant amounts of effort and sap efficiencies within individual innovation projects. Such "innovation butterflies" can be prompted by external forces such as government legislation or unexpected spikes in the price of basic goods (such as oil), unexpected shifts in market tastes, or from a company manager's decisions or those of its competitors. Even the smallest change, the smallest disruption, to this system can steer a firm down an unpredictable and irreversibly different path in terms of technology and market evolution. In the long term, they can shift the balance of the entire innovation portfolio into unplanned directions. More importantly, we describe how innovation leaders can influence the emergent behavior of the system for good or ill. The first half of the book draws parallels from physics, economics, and sociology as well as evidence from multiple industries to describe the structural and behavioral causes of emergent phenomena in innovation settings as well as their often negative impacts. In the second half of the book, we turn to distributed management of innovation under emergence. We show that innovation butterflies, if improperly managed, most often lead to negative outcomes. On the other hand, it is also argued that while the complexity of the innovation system and the desire to experiment and try new and emergent alternatives precludes precise planning, innovation leaders can actually tame innovation butterflies through the design and implementation of appropriate processes, strategies, tools and leadership choices.

A guide to achieving business successes through statistical methods

Statistical methods are a key ingredient in providing data-based guidance to research and development as well as to manufacturing. Understanding the concepts and specific steps involved in each statistical method is critical for achieving consistent and on-target performance.

Written by a recognized educator in the field, Statistical Methods for Six Sigma: In R&D and Manufacturing is specifically geared to engineers, scientists, technical managers, and other technical professionals in industry. Emphasizing practical learning, applications, and performance improvement, Dr. Joglekar’s text shows today’s industry professionals how to:

• Summarize and interpret data to make decisions
• Determine the amount of data to collect
• Compare product and process designs
• Build equations relating inputs and outputs
• Establish specifications and validate processes
• Reduce risk and cost-of-process control
• Quantify and reduce economic loss due to variability
• Estimate process capability and plan process improvements
• Identify key causes and their contributions to variability
• Analyze and improve measurement systems

This long-awaited guide for students and professionals in research, development, quality, and manufacturing does not presume any prior knowledge of statistics. It covers a large number of useful statistical methods compactly, in a language and depth necessary to make successful applications. Statistical methods in this book include: variance components analysis, variance transmission analysis, risk-based control charts, capability and performance indices, quality planning, regression analysis, comparative experiments, descriptive statistics, sample size determination, confidence intervals, tolerance intervals, and measurement systems analysis. The book also contains a wealth of case studies and examples, and features a unique test to evaluate the reader’s understanding of the subject.