| 授業名 | Design Thinking |
|---|---|
| Course Title | Design Thinking |
| 担当教員 Instructor Name | Giulio Toscani |
| コード Couse Code | NUC467_N25B |
| 授業形態 Class Type | 講義 Regular course |
| 授業形式 Class Format | On Campus |
| 単位 Credits | 2 |
| 言語 Language | EN |
| 学位 Degree | BBA |
| 開講情報 Terms / Location | 2025 UG Nisshin Term4 |
授業の概要 Course Overview
Mission Statementとの関係性 / Connection to our Mission Statement
This course empowers emerging and established leaders across industries to apply Design Thinking principles in harnessing Big Data and AI for strategic advantage. Participants will learn to empathize with customer needs, define key challenges, ideate innovative solutions, and prototype data-driven strategies that strengthen customer relationships and differentiate their organizations. Rather than focusing solely on analysis and technology adoption, the course emphasizes human-centered problem solving—enabling leaders to reimagine their capabilities and integrate AI and Big Data into broader organizational strategies. By applying Disruptive Innovation as part of the Design Thinking toolkit, participants will develop a mindset that goes beyond understanding data and technology—enabling them to creatively leverage these tools to lead transformation and deliver impactful business results.
授業の目的（意義） / Importance of this course
This course is a game-changer for leaders seeking to stay ahead of the curve, equipping them to harness the power of Design Thinking before their competitors. Participants will develop a deep understanding of Design Thinking in the context of Big Data and Generative AI, learning how to identify emerging threats and uncover strategic opportunities within their own organizations.
到達目標 / Achievement Goal
By studying this course, students will be able to:
Understand the forces of disruption that could impact their business and see how to spot them early
Uncover a new approach for customer centricity to spot and shape new opportunities by applying the jobs to be done framework
Learn, through practical examples, how to leverage new business models and potential application for their companies
Get hands-on experience using the disruptive innovation toolkit
Understand the forces of disruption that could impact their business and see how to spot them early
Uncover a new approach for customer centricity to spot and shape new opportunities by applying the jobs to be done framework
Learn, through practical examples, how to leverage new business models and potential application for their companies
Get hands-on experience using the disruptive innovation toolkit
本授業の該当ラーニングゴール Learning Goals
*本学の教育ミッションを具現化する形で設定されています。
LG1 Critical Thinking
LG4 Effective Communication
LG5 Business Perspectives (BSc)
LG6 Managerial Perspectives (BBA)
LG7 International Perspectives (BA)
LG4 Effective Communication
LG5 Business Perspectives (BSc)
LG6 Managerial Perspectives (BBA)
LG7 International Perspectives (BA)
受講後得られる具体的スキルや知識 Learning Outcomes
Empathize with Data-Driven Challenges: Participants will develop a human-centered understanding of how Big Data and AI can be strategically used to address real-world problems and create a sustainable competitive advantage.
Define Opportunities Through Technological Insight: Learners will explore emerging AI and Big Data technologies, gaining the ability to identify unmet needs and redefine business challenges through an innovation-focused lens.
Ideate Customer-Centric Solutions: By integrating Disruptive Innovation within the Design Thinking framework, participants will learn to generate creative, data-informed solutions that respond to evolving customer expectations and behaviors.
Prototype and Test Strategic Leadership Skills: Participants will practice iterative thinking and agile decision-making, preparing them to lead transformative initiatives that align data and technology with broader organizational goals.
Drive Innovation Through Integrated Thinking: Upon completion, learners will be equipped to bridge the gap between technical potential and human impact—emerging as strategic leaders who can design and implement future-ready solutions in an AI-driven world.
Define Opportunities Through Technological Insight: Learners will explore emerging AI and Big Data technologies, gaining the ability to identify unmet needs and redefine business challenges through an innovation-focused lens.
Ideate Customer-Centric Solutions: By integrating Disruptive Innovation within the Design Thinking framework, participants will learn to generate creative, data-informed solutions that respond to evolving customer expectations and behaviors.
Prototype and Test Strategic Leadership Skills: Participants will practice iterative thinking and agile decision-making, preparing them to lead transformative initiatives that align data and technology with broader organizational goals.
Drive Innovation Through Integrated Thinking: Upon completion, learners will be equipped to bridge the gap between technical potential and human impact—emerging as strategic leaders who can design and implement future-ready solutions in an AI-driven world.
SDGsとの関連性 Relevance to Sustainable Development Goals
Goal 4 質の高い教育をみんなに（Quality Education）
教育手法 Teaching Method
| 教育手法 Teaching Method | % of Course Time | |
|---|---|---|
| インプット型 Traditional | 50 % | |
| 参加者中心型 Participant-Centered Learning | ケースメソッド Case Method | 30 % |
| フィールドメソッド Field Method | 20 % | 合計 Total | 100 % |
事前学修と事後学修の内容、レポート、課題に対するフィードバック方法 Pre- and Post-Course Learning, Report, Feedback methods
Before the course begins, participants will receive curated reading materials and case studies to establish foundational insights,
Following the course, participants will develop an assignment to apply key learnings in their professional environments. They will engage in case study analysis to address cross-cultural digital challenges.
The post-course assessment will measure individual progress, complemented by instructor feedback, upon request, to offer insights into leadership strengths and areas for improvement. Participants will complete a course feedback survey to evaluate the program’s effectiveness Required amount of preparation: there will be 7 cases and a final individual report. The cases require at least 2 hours each, Minimum 14 hours.The final report is approximately 10 hours
Following the course, participants will develop an assignment to apply key learnings in their professional environments. They will engage in case study analysis to address cross-cultural digital challenges.
The post-course assessment will measure individual progress, complemented by instructor feedback, upon request, to offer insights into leadership strengths and areas for improvement. Participants will complete a course feedback survey to evaluate the program’s effectiveness Required amount of preparation: there will be 7 cases and a final individual report. The cases require at least 2 hours each, Minimum 14 hours.The final report is approximately 10 hours
授業スケジュール Course Schedule
第1日（Day1）
Design Thinking for the Age of Big Data and Generative AIIn this session, we will explore the concept of disruption and its impact on various industries. We will delve into the fundamentals of Big Data AI and how it is revolutionizing traditional business models. You will gain insights into the potential of data-driven innovation and understand the key components of a disruptive ecosystem.
Design thinking for disruption Workshop
●使用するケース
The four Dimensions of companies’ disruption第2日（Day2）
In this session, participants will empathize with the complexity of data-driven ecosystems by exploring how Big Data and AI technologies shape today’s innovation landscape. Rather than a purely technical overview, the session will focus on human-centered insights—how data is collected, processed, and transformed into intelligent solutions that meet real-world needs.Through the lens of Design Thinking, participants will define key challenges and opportunities presented by the convergence of Big Data and AI. We will explore the foundational principles of scalable data systems and AI algorithms, and examine their role in enabling disruptive innovation.
Case 2
●使用するケース
Navozyme第3日（Day3）
In this session, we will explore how organizations can apply Design Thinking principles to harness Big Data as a catalyst for disruption and innovation. Through real-world case studies, participants will examine how industry leaders have used data to reframe problems, uncover unmet needs, and redesign business models for a competitive edge. You will learn how to empathize with data-driven challenges, define opportunity areas, and ideate disruptive strategies that transform insights into impactful innovation. This session emphasizes a human-centered, iterative approach to identifying and acting on data-driven opportunities for meaningful change.●使用するケース
Eatwith第4日（Day4）
Building on the previous session, this module explores the transformative potential of AI through the lens of Design Thinking. Participants will examine how technologies such as machine learning and deep learning can be used not just for automation, but as tools to reimagine value creation and user experiences. By analyzing real-world case studies, you will uncover how AI-powered solutions are reshaping industries—starting from human needs and working toward innovative, data-driven responses. This session encourages you to ideate and prototype around emerging opportunities, fostering a mindset of disruption grounded in empathy and experimentation.●使用するケース
Via 0n-demand transport第5日（Day5）
Disruption through Big Data AI is not without its challenges. In this session, we will discuss the obstacles and risks associated with data-driven innovation. We will address issues such as data privacy, ethical considerations, and regulatory frameworks. You will gain insights into best practices for mitigating risks and navigating the complex landscape of disruptive technologies.●使用するケース
Deepseek第6日（Day6）
Design Thinking plays a crucial role in the process of disruption. In this session, we will explore the principles of design thinking and its application in driving data-driven innovation. You will learn how to adopt a user-centric approach to identify unmet needs, prototype disruptive solutions, and create meaningful experiences for customers in the digital era.●使用するケース
Polaroid第7日（Day7）
In the final session, we will examine strategies for embracing disruption and capitalizing on the opportunities presented by Big Data AI. We will explore organizational agility, talent acquisition, and cultural transformation as key drivers for success in disruptive environments. You will leave with actionable insights and a roadmap for harnessing the power of data-driven innovation to shape the future of your industry.●使用するケース
Peloton成績評価方法 Evaluation Criteria
*成績は下記該当項目を基に決定されます。
*クラス貢献度合計はコールドコールと授業内での挙手発言の合算値です。
*クラス貢献度合計はコールドコールと授業内での挙手発言の合算値です。
| 講師用内規準拠 Method of Assessment | Weights |
|---|---|
| コールドコール Cold Call | 0 % |
| 授業内での挙手発言 Class Contribution | 75 % |
| クラス貢献度合計 Class Contribution Total | 75 % |
| 予習レポート Preparation Report | 0 % |
| 小テスト Quizzes / Tests | 0 % |
| シミュレーション成績 Simulation | 0 % |
| ケース試験 Case Exam | 0 % |
| 最終レポート Final Report | 25 % |
| 期末試験 Final Exam | 0 % |
| 参加者による相互評価 Peer Assessment | 0 % |
| 合計 Total | 100 % |
評価の留意事項 Notes on Evaluation Criteria
教科書 Textbook
- Giulio Toscani「augmented: prAIority to Enhance Human Judgment through Data and AI」CRC Press（2025）
参考文献・資料 Additional Readings and Resource
How Incumbents Survive and Thrive By: Julian Birkinshaw
Persuade Your Company to Change Before It's Too Late By: Pontus M.A. Siren; Scott D. Anthony; Utsav Bhatt
Adapting to Digital Disruption By: Julian Birkinshaw; Thomas W. Malnight; Ivy Buche; Pontus M.A. Siren; Scott D. Anthony; Utsav Bhatt; Jonathan Knee; Alison Beard
Can Big Tech Be Disrupted? By: Jonathan Knee; Alison Beard
Persuade Your Company to Change Before It's Too Late By: Pontus M.A. Siren; Scott D. Anthony; Utsav Bhatt
Adapting to Digital Disruption By: Julian Birkinshaw; Thomas W. Malnight; Ivy Buche; Pontus M.A. Siren; Scott D. Anthony; Utsav Bhatt; Jonathan Knee; Alison Beard
Can Big Tech Be Disrupted? By: Jonathan Knee; Alison Beard
授業調査に対するコメント Comment on Course Evaluation
The cases have been uddated according to students feedback
担当教員のプロフィール About the Instructor
EDUCATION: Artificial Intelligence: Implications for Business Strategy (2018.) MIT, Massachusetts Institute of Technology, Sloan & MIT CSAIL. Cambridge, USA
PhD in Management (2018).KTH, Royal Institute of Technology. Stockholm, Sweden.
BSc and MSc in Chemical Engineering (1999). Italy/UCL London, UK
（実務経験 Work experience）
Professor and Advisor
• ESADE Business and Law School, Barcelona, Spain. Adjunct Professor
Law School degree: Digital Technologies Impact
MIBA (Master in Business Analytics) & MBA: Human + Machine strategy
Executive education: Remote teams; Digital Entrepreneurship; Leadership in AI.
• Pacifico Business School, Lima, Perú. Adjunct Professor
• University of Bath, Bath, UK. Visiting Professor. MBA Programme: Contemporary issues at the time of Big Data/ Artificial Intelligence
• NUCB Nagoya University of Commerce and Business, Nagoya, Japan. Visiting Professor. MBA programme: Disruption by Big Data|Artificial Intelligence
• Ranepa Business School, Moscow, Russia. Visiting Professor. Global MBA: Digital Entrepreneurship
• Politecnico, Milan, Italy. Visiting Professor. Master in Strategic Design: Design Thinking in AI
• Navozyme, Singapore. Advisory Board.
• Programme Director Universitas Telefónica. Barcelona, Spain.
Direction and Teaching of the Programmes for Telefonica Global Executives
Publications
Sponsees: the silent side of sponsorship research (Arts Sponsorship)
G Toscani, G Prendergast
Marketing Intelligence & Planning 36 (3), 396-408 22
2018
Arts Sponsorship Versus Sports Sponsorship: Which Is Better for Marketing Strategy?
G Toscani, G Prendergast
Journal of Nonprofit & Public Sector Marketing 19
2018
Behaviour of different treated and untreated stones exposed to salt crystallization test
R Quaresima, G Toscani
5th:; International symposium, Conservation of monuments in the … 4
2002
UNDERSTANDING THE SPONSEE'S EXPERIENCE: AN ASSESSMENT OF THE SPONSOR-SPONSEE RELATIONSHIP
G Toscani
KTH Royal Institute of Technology 2
2018
Political Art: An Investigation of the Jacob Zuma Spear Painting
BE Stiehler, G Toscani
Ideas in Marketing: Finding the New and Polishing the Old, 516-525 2
2015
Leading successful AI projects in three words: group, relevant, and empathetic
G Toscani
Do Better by ESADE 2022
How Artificial Intelligence (AI) experts’ skills relate to AI solution outputs
G Toscani
Under Review 2023
The effects of the COVID-19 pandemic for AI practitioners: the decrease in tacit knowledge sharing
G Toscani
Journal of Knowledge Management 2022
The role of reciprocity and reputation in service relationships with arts organisations (Arts Sponsorship)
G Toscani, G Prendergast
Journal of services marketing 2021
CONTRASTING SPORTS SPONSORSHIP AND ARTS SPONSORSHIP
G Toscani, G Prendergast
7th World Business Ethics Forum 2018
ARTS SPONSORSHIP VERSUS SPORTS SPONSORSHIP: WHICH IS BETTER FOR MARKETING STRATEGY?
G Toscani, G Prendergast
The sponsor-sponsee relationship through the lens of the sponsee
G Toscani, G Prendergast
Politics and art: An exploratory study investigating the hype caused by the Jacob Zuma Spear painting
G Toscani, BE Stiehler
Appendix (E): Emerged Working Papers
G Toscani, G Prendergast
Refereed Articles
- (2025) EXAPTATION AS A STRATEGIC MECHANISM IN PUBLIC R&D: CHALLENGES AND SOLUTIONS AT THE BARCELONA SUPERCOMPUTING CENTER. The Journal of Supercomputing
- (2025) El arte de la aumentación: integrando IA, datos y juicio humano en la era digital. Harvard Deusto Business review (356):
- (2025) From code to context: the impact of organizational problem framing on machine learning success. Journal of Decision Systems 34(1):
- (2025) El poder del trinomio formado por el ser humano, la IA y el ‘big data’. Harvard Deusto Business review (351):
- (2024) Creatividad e innovación en la empresa digital: una historia muy antigua. Harvard Deusto Business review (340):