Profile
Founder of Data & Story LLC
(Professional Business Problem-Solving Skill Trainer)
Visiting Professor at Tama Graduate School of Business
1995-2003 | Sales Engineer for overseas markets at Hitachi in Japan. |
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2003 | MBA at Goizueta Business School (U.S.) |
2004-2014 | Manager of Global Marketing & Sales and Business Transformation Group at Nissan (Master Black Belt of Nissan’s proprietary Six Sigma program) Solved a variety of business and management problems at Nissan’s global headquarters; they involved new business development, process optimization, organization restructuring, etc. |
2014- | Founder of Data & Story LLC |
Published 18 business books about decision making and data analysis in Japan, Korea, China, Vietnam and Taiwan.
Practical data analysis training programs
Program | Outline | |
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A | For beginners (half-day to one-day) |
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B | Standard programs (one-day) |
Hypothesis-driven analysis program (B-1)
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Story-making program (B-2)
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C | Data literacy program for managers (half-day) |
Unique program specific to managers who are not involved in data analysis but need to make decisions based on it.
You can improve the quality of your decision making by answering the following questions:
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D | Customized program | A program organized for clients (in most cases, actual business issues and data are used) |
An intensive class/program (e.g. a one-week/two-week program) for universities is also available
Business logical thinking/problem solving/ hypothesis development(Active-learning programs)
Program | Outline | |
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A | Hypothesis-development skill program (one-day) |
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B | Problem solving with logical thinking and framework (one-day) |
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C | Customized program | A program organized for clients |
An intensive class/program (e.g. a one-week/two-week program) for universities is also available
Program schedule (Example of one-day business data analysis)
1. How can you use data for your daily business? | Lecture | 30 min. |
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2. From “Data-processing” to “Data-analysis” | Lecture | 30 min. |
3. Hypothesis-driven approach | Lecture + Exercise | 30 min. |
4. How to identify issue points | Lecture + Exercise | 40 min. |
5. How to capture the characteristics of data and compare | Lecture + Exercise | 90 min. |
6. How to find relation of two data sets | Lecture + Exercise | 60 min. |
7. How to quantify the data relation | Lecture + Exercise | 40 min. |
8. How to effectively present your analysis results | Lecture | 30 min. |