Principles and Practices of Global Innovation 2015 Fall Semester, 2nd Phase

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Principles and Practices of Global Innovation

Background

This course is conducted in the iPodia format, which is an innovative approach to deliver content, yet allow students to become aware of their dynamic and global learning context. Therefore, the second phase of this course will be conducted by Prof. Ben Koo of Tsinghua University from Beijing. By having a different instructor leading discussions, it will bring out different content focus and further emphasize the learning context will change constantly.

To bridge between these changes, the want to ensure that the academic content uses a consistent vocabulary, enabling students to better understand the second phase of the course using the knowledge learned from earlier lectures. Moreover, we will also integrate cross culture activities and the creation of a team-based "mini" industry analysis report to get students' involved in a global learning experience.

Instructors

The 2015 Fall Semester, Session B of "Principles and Practices of Global Innovation" is taught by three instructors from USC, THU, and NTU, three universities. They are:

  1. Prof. Stephen Lu of USC
  2. Prof. Ben Koo of THU.
  3. Prof. 刘霆 ( Liu Ting) of NTU

Studying Objective

The goal of the second phase is to guide students in writing mini-industry analysis reports that reflect on the conceptual framework presented by Prof. Lu in the first phase of this course.

Output

Student teams will create a minimum 10 page mini Industry Analysis Report before the end of this semester. In this report, students must leverage the technical terms learned in this semester to present their analytical and synthetic solutions toward a topic or product/service type of their own interest. Starting from the second phase, we will introduce Thomas Kuhn's idea of paradigm shifts, intellectual property laws, patent search databases, and open/free software movement on top of other ideas already presented in this semester. Students need to use these terms to identify and explain the opportunities and risks in the market place and the internal motivations or challenges of individual firms. The report should include the following elements:

  1. A brief description of the product of service of interest
  2. An overview of the marketplace with quantitative assessment, government policies regarding the product/service, cultural norms in terms of how people generally perceive the product.
  3. Search on at least 2 patent databases and list a number of patents relates to the key components of your product.
  4. A assessment discussion section summarizing the market outlook of the product/service of your choosing.

Specification

The content of your report should demonstrate that you and your team members have learned the technical terms of this course. When you make quantitative and qualitative arguments, please make sure the following diagrams and technical terms are used:

  1. S-Curve as a qualitative description of your product/service. If you can find quantitative data to show S-Curve, please include it in the report.
  2. Explain the dominant design and commodity market of your product/service.
  3. Talk about Red Ocean and Blue Ocean, in terms of "Paradigm Shift" arguments presented by Kuhn.
  4. Identify critical patents or inventions that trigger the paradigm shift, and explicitly list the patent or describe the relevant inventions.
  5. You must assess how Open Source Movement and the Free Software Movement is or is not going to affect your product, why and how.
  6. If relevant, talk about how Big Data approaches and breakthroughs in Artificial Intelligence could affect your products/services.

Pedagogy

The pedagogical approach in Phase II of this course is to let students apply the knowledge learned in Phase 1 to their projects of interest. We will enter the second phase of this course assuming students roughly believe in the following three things:

  1. Innovation is messy! It requires many adjustments for the society to make sense of these new ideas.
  2. When and if innovation comes with certain regularity, it might come at a surprisingly fast speed. Otherwise, it usually is not considered to be a revolutionary idea.
  3. In order to analyze, synthesize, and present a cohesive argument in an innovation process, students need a new set of tools.

Therefore, we will organize our following in-class hours to recognize these features of innovation.

Content

This section of the course will be divided into four separate weeks starting on October 27th:

Week 1

The first week of phase II is to introduce the tool set for analyzing Global Innovation opportunities. The tool set for this class includes :

  1. A meta-scientific reasoning framework: Kuhn's Structure of Scientific Revolutions.
  2. Crowd-Sourcing Knowledge Management Tool: e.g. MediaWiki and the Wiki-related community
  3. Quantitative analysis models, and proven predictive models: Moore's Law

A Meta Framework to reason about Sciences

To enable students better understand the source of innovation, week one starts with Kuhn’s theory as presented in the book: Structure of Scientific Revolutions. Kuhn's theory is directly relevant to our course, since he presented a meta-theory on how scientific discoveries and technological breakthroughs can be analyzed in terms of “paradigms". His work has profound influence on technology and business innovators, and was mentioned by Prof. Lu in earlier PPGI lectures. Kuhn's theory is not only popular, but also having well documented commentaries and even video lectures readily available for students' references. Therefore, we expect students to read the book or at least watch the videos on youtube. Web links to these material will be provided before and after class.

As a science historian, Kuhn didn't focus on one point of scientific fact, he provided a generalizable framework to capture a wide range of scientific reasoning processes. Kuhn's framework can be conceptually applied to various stages of scientific revolutions. His units of revolutionary stages are called "paradigms". Relating to Prof. Lu's terminology, the applicability of a technology paradigm can be mapped onto the time span of an S-Curve. When new technologies or new scientific theory gets adopted to a society, a new S-curve emerges. We want students to study this book as a reference, and use this well-adopted lingua-franca to analyze the product or service of your own interests.

A "paradigm shift" is a social evolution process. In many cases, scientific or technological revolutions triggers social revolution as well. In any case, a paradigm shift needs the society under its influence to adopt a new language, or at least a new set of vocabulary to absorb the changing paradigm. Therefore, Kuhn considers the old society not able to comprehend the life style meaning or the society running under a new paradigm. After nearly 30 years of the publication of Structure of Scientific Revolutions, he started writing an article called:The Road Since Structure. In this article, later republished as a compiled book of essays, talked about the notion of Incommensurability extensively. This leads to the second point of our lecture.

A Sociable Knowledge Management tool

To predict or intentionally manage innovation, detecting how people are using their vocabulary to express metaphors and understanding mechanisms would be a useful channel to assess how certain crowd is perceiving certain technologies or social services. MediaWiki as a web-based technology is a tool that can serve this purpose well. We have been using this tool to help students manage their collective impression about their learning activities, and sharing learning notes in a classroom. It has also been the main source for many artificial intelligence engines to mine human knowledge. We found it very useful to help groups of students to write and publish their learning reports, so that we will invite all iPodia students in the future to use this popular tool. More importantly, this tool can help us better organize the vocabulary introduced in this course. We think many of its statistical features can also help us identify the changing metaphors used daily writing, might be an objective measurement of how society is viewing certain objects or technologies differently, signaling a change or a revolution in the making. This signal can be used as a way to strategically identify the direction and opportunities for innovation. In short, we think getting students to learn to use and produce in wiki-compatible knowledge management tool is an essential skill, so that we have already created accounts for all participating students.

A Predictive Model for Innovation

We also want to point out that the amount and the quality of wiki entries provide a possible source to analyze social awareness of certain technologies or technical knowledge. These quantitative metrics can be used to signal or measure the speed of change or the type of change. A known predictive model for innovation is called Moore's Law. We will also talk about this in this week. In Week 1, we present Moore's Law as a quantitative assessment of technology evolution speed. The most extreme case can be attributed to futurist:Ray Kurzweil. Kurzweil believes that the ever increasing speed of technology evolution will create a singularity point in human civilization. This idea itself is an example of paradigm shift. Whether this singularity point would happen or not, Moore's law has been proven to work within the last 50 years. This is also relevant to innovation practice analysis, because this exponential growth rule also marks a category of paradigm shift, it makes the society to start believe in the fact that exponential growth is possible. More importantly, many business strategies and technology development schedule is determined by this exponential growth factor.

Your Product

Week 1 or Phase II is about introducing this "language-oriented" practice to analyze or synthesize opportunities of innovation. To better integrate with Kuhn's view, we introduce Kuhn's Cycle, and invite all teams to follow Kuhn's Cycle to create a mini-Industry Analysis Report(IAR). We believe that students will gain more insight when they apply this framework to analyze or synthesize a innovative solution of their interest.

To help students manage the complex process of developing a new language, we first introduce the MediaWiki website. This is a way to get a large number of people to manage a rather large vocabulary. As participants add more entries to this knowledge base, it will naturally support the retention of knowledge and allow better analysis of the usage and re-definition of certain terms.

Students can use the Wiki Platform as a content authoring platform. It will incrementally capture digitized content of the whole team. Therefore, I believe that this instrument should help various teams to coordinate their IAR creation effort.

The process of identifying product development opportunities may sound daunting. However, it is spelled out on this website in four steps.

  1. Define the Original Problem: Find out what is the Right thing to do.
  2. Root Cause Analysis: Find out who or which organization is ultimately responsible and capable of conciously making changes.
  3. Process-Driven Analysis: Define the Goals, Effects, Output Validation mechanisms, before pre-maturely locking down to seat-off-the-pants solutions.
  4. Model-Driven Analysis: Do the things Right, by employing qualitative/quantitative reasoning framework to define the plan in precise technical details.


We want to show students that innovation is about "language" or "knowledge" management on a societal scale, therefore, new tools such as artificial intelligence, search engines, User-Created Content, and high speed communication is having a significant impact on how new S-Curve is going to appear at a higher rate. These tools are going to profoundly change the way we assess market and design new products.

To help students grasp these ideas quickly, we will present a few simple diagrams, proposed by thought leaders such as Kuhn and Lessig, so that students can find ways to become familiar with the literature body when they want to learn more about these topics. At the same time, they can build a commonly known mental image on how to tackle these kind of innovation challenges based on existing practices and tools.

Study Questions

  1. What does Kuhn mean by "Paradigm"?
  2. How does Kuhn define the term "Scientific Revolutions"?
  3. Does Kuhn's definition of "commensurability" problem help explain the cognitive gap between early adoption and late majority in the marketplace?
  4. How is the term "Paradigm" or "Paradigm Shift" relates to the practice of Innovation. Please think in terms of S-Curve, Blue/Red Ocean, Dominant Design, and other ideas presented in the modern literature presented in the first phase of this course.
  5. How does Lessig define the term architecture? And how does the idea of architecture relates to dominant design in the product development literature?

Week 2

I would like to show a bit of patent search, and various patent search sites to students. So that they can be a bit familiar with these resources. Then, I want to show students the Contradiction Table/Matrix developed by the TRIZ community. I want to show them how innovation can happen using a concrete tool to guide a rather abstract conceptual tool. I will also explain a bit about Prof. Nam Suh's Axiomatic Design, and how the terms Functional Requirements and Design Parameters can be used to formalize the requirement statements of a product system.

In this week, students are welcome to pick a product or product system of choice to apply the above tools to try out relevant patent searches and Contradiction Table examples. We will probably continue to use the Self-Driving Vehicle or an Electronic Car Charging system as an example.

Study Questions

  1. What are the major publicly searchable patent databases?
  2. What is a Contradiction Matrix? How is it related to innovation?
  3. Please create a simple example that illustrate your team's use of Contraction Table or Axiomatic Design?
  4. Can Axiomatic Design and Contradiction Matrix used conjunction? Please give an illustrative example or a counter example.

Week 3

I want students to learn a bit about the Free Software Movement, and how Richard Stallman's personal crusade profoundly changed the landscape of intellectual property rights of the modern world. This breaks down the monopoly to a wide range of technologies for many firms and countries to enter high-tech businesses.This historical event is also a major source that stimulated innovation that took place in the last 30 years. We will talk about the differences between Open Source Technologies and Free Software Licenses. What are the implications to innovators. We will also examine the ideas of Lawrence Lessig, and his books on Freedom of Ideas and his work on Creative Commons.

Study Questions

  1. What is the difference between Open Software License and Free Software License according to Richard Stallman?
  2. List three commonly known Open/Free Software Licenses, show their key differences.
  3. What is Creative Common License, why is it relevant to innovation?
  4. Imagine a world without the Open Source Movement, can we have the iPhones and Tesla's as we have it today?
  5. Do we consider Hacker community as a legitimate innovation contributor, or do we consider them pranksters that will always be marginalized in the society?

Week 4

Artificial Intelligence and Big Data is becoming a major threat to many knowledge workers. In 2011, IBM's cognitive computing service beat the world champion at the Jeopardy Game. Gartner Group predicts that within a few years, at least 30 percent of business contracts, and many standard technical reports will be generated by machines, not written by humans anymore. How would this change the global strategies of product development? How would this accelerating trend affect our lives? Speficially, we learned that the biological technologies are evolving a rate 5 times higher than the Moore's Law. Sequencing a human Genome used to cost 1 billion dollars 15 years ago, now, it costs about 1000 USD. This is clearly changing the game. Can we continue to use the business analysis tools to think about Innovation Strategies? In this week's work, we will identify a number of known products that are accelerating at a pace much faster than the Moore's law, and we will show that these products or services may or may not be analyzed using S-curve. Some analytical tools, such as Multi-Agent simulation program NetLogo will be introduced and shown in this week.

Study Questions

  1. In the world of Big Data and IBM's Cognitive Computing, what kind of knowledge intensive job functions will continue to be only conducted by humans?
  2. How can we use a combination of predictive and prescriptive models to reason about uncertain decisions, in ways that big data services and computers cannot compete against our judgement? What skill sets should humans be trained at this point to better co-exist with ever more advanced machines?
  3. Innovations in banking such as Bitcoin and Blockchain is challenging traditional businesses even government services in the cyberspace. What is the working principles behind these technologies?
  4. Identify three products or services whose price drop or performance increase more than doubles every two years in the last 20 years.

Reference Material

  1. Structure of Scientific Revolutions 3nd Ed, by Thomas Kuhn, University of Chicago Press, 1996
  2. Innovator's Dilemma, by Clayton M. Christensen, Harvard Business School Press, 1997
  3. (Amazon Link:http://www.amazon.com/gp/product/0226458040?keywords=Structure%20of%20Scientific%20revolutions&qid=1445276370&ref_=sr_1_3&sr=8-3 )
  4. A website on Kuhn's Cycle: http://www.thwink.org/sustain/glossary/KuhnCycle.htm
  5. Videos on the book: Structure of Scientific Revolutions Part 1, 2 and 3 by Duadnews2009 on Youtube 
   Part 1: https://youtu.be/T5m9x-Sjugo  8'11"
   Part 2: https://youtu.be/HYm58BTrHcQ  8'08"
   Part 3: https://youtu.be/EjWkQoBZEGY  6'39"
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