Bài giảng Disruptive innovation môn Design thinking in Big data & AI | Trường Đại học Văn Lang

6/1/26 Let them believe to think and they wil love you Let them real y think and they wil hate you 1 2 LEARNING vs. PERFORMANCE Attention UaE 1. (Unplugged and emptied) Active engagement 2. Error feedback 3. Consolidation 4. (Dehaene 2020) 3 5 1 6/1/26 The Linkedin Assignment Due by Two weeks Competition. after the end of the course Apply the framework learned Minimum 2000 words, no maximum in the course to a real
problem. Clearly articulate the 10% FAILURE RATE problem framing, data assumptions, AI’s role, and
CONSERVATIVE PEDAGOGIC APPROACH, human decision points. Share
AESTHETICALLY COMPLEX, GROUNDED OF THE COURSE. your outcome in one slide or short video. Evaluation wil LOTS OF SLIDES COPIED
focus on methodological rigor, coherence, and thoughtful use of AI and Big Data. 6 7 DISRUPTIVE ROAD MAP INNOVATION IN BIG 1. Disruptive innovation 2. Innovation Mindset DATA & AI
3. Introduction to Big Data and AI 4. Examples of disruption
5. Companies’ disruptive policies 6. AI & Customers
7. Disruptive innovation workshop 8 9 2 6/1/26 GEARBOX COURSE, NOT ENGINE AI DOES NOT ACT FOR YOU, IT CHANGES WHAT
This course is not about learning how YOU CAN SEE AND to build engines. THEREFORE WHAT YOU
It is about learning how to choose the DECIDE
right gear, at the right moment, for the right terrain.
A TERRAIN THAT DOES NOT EXIST YET 10 11 ENGINE vs. GEARBOX YES teaching:
When AI adds leverage vs. when it
Engines = algorithms, models, tools adds risk (technical domain) How data changes decision
Gears = business methods, decision asymmetries How organizational structure, frameworks, and leverage
incentives, and timing matter more Terrain = market conditions, than tools
uncertainty, regulation, competition NO teaching: Driver = executive judgment How to code How to tune models How to select architectures 12 13 3 6/1/26 A telescope does not make decisions. Two people with the same telescope can make radical y different choices. The advantage lies in
interpretation, framing, and action, not optics. 14 15 Patterns ≠ causality
Models amplify assumptions
The cost of being wrong is a business cost, not a technical one
The kil er executive takeaway COMPANIES EXAMPLE
“The biggest AI risk is not that the model is wrong.
It is that the organization acts as if it cannot be wrong.”
West India Company, Uber, Suez canal, Enron
Boradband, Lehman Brothers, Nokia, ChatGPT, IBM,
10. Final framing sentence (to close the loop) You end with:
Netflix, Amazon, Microsoft, Fujifilm, Disney,
“If this course were about tools, we would have used computers.
We did not — because AI leadership is about judgment, not code.” The Biased Market” — experiencing data, ML, and
Patagonia Provisions, Moderna, P&G, ElBulli, Airbnb, business judgment
Telegram, Zipline, Google, McDonald, Linkedin, Objective
Let executives physically experience:
Nespresso, Zoom, Wikipedia,Navozyme, Expedia, Data generation Bias
Tesla, Del , Philips, Michelin, Rol s Royce, Teatreneu, Model training Overfitting
America’s Cup, Heinz Ketchup, Duolingo, 80 acrees
Strategic misuse of predictions All without technology.
farm, Equilips, TikTok, Vokswagen, Mastercard,
Telefonica, Bottega Calzolaio, Starbucks, Booking, 4. Setup (15 minutes)
Spotify, NyTimes, Ikea, Adobe, AlphaFold. Materials (simple) Sticky notes (3 colors) Index cards Markers 16 17 Whiteboard or flip chart Coins or dice Room layout 3–5 groups of 5–6 people One facilitator per room (you)
5. Phase 1 — Data generation (The market) 4 Instructions
Each group represents a company trying to predict customer churn.
You, the facilitator, are “the market”.
You distribute index cards, each representing a “customer” with 3 attributes:
Age group (Young / Middle / Senior)
Product usage (Low / Medium / High) Region (A / B) But here is the trick:
The distribution is intentional y biased
Some groups receive clean data
Some receive skewed or incomplete data They don’t know this.
6. Phase 2 — “Training the model” (Analogue ML) Each group must:
Identify patterns using only discussion and whiteboard logic Create rules like:
“High usage + Region A → low churn”
“Senior + low usage → high churn”
These rules are their model. They must write: Their top 3 predictive rules One confidence assumption This simulates: Feature selection Pattern extraction Model simplification No math required.
7. Phase 3 — Validation shock
Now you introduce new customers (new index cards). Here is the key:
The new data follows a different distribution Some previous patterns fail Groups must: Apply their rules Predict churn (Yes/No) Defend their logic You then reveal: Which predictions failed Why
This creates an immediate, emotional experience of: Overfitting Dataset shift False confidence 6/1/26 ROAD MAP
1. Big Data Advantage: Leveraging vast data sets for competitive edge through insight and precision.
1. Disruptive innovation
2. AI Integration: Using AI tools to automate, predict, and personalize customer 2. Innovation Mindset experiences.
3. Introduction to Big Data and AI
3. Customer Connection: Building deeper relationships through data-driven understanding of expectations.
4. Identifying Opportunities for Disruption
4. Disruptive Innovation: Employing novel methods to outpace competitors and
5. Implementing AI for competitive adapt to changing markets. advantage
5. Data Strategy Alignment: Integrating data insights into overarching organizational strategy.
6. Overcoming Challenges in AI and Big
6. Industry-Spanning Relevance: Tailored for leaders across sectors seeking more Data than basic data analysis.
7. Leadership in Technology: Empowering leaders to adopt data-driven, tech-
7. Disruptive innovation workshop forward strategic visions. 20 21 STABILITY, AN ILLUSION DISRUPTION, A REALITY
1. What if everything you knew about
1. Disruption is inevitable Ignoring change won’t stop it. stability was an il usion?
2. Innovation can be a threat Like WIC, dismissing new tech can be fatal.
2. The Calm Before the Storm– The Dutch
3. Competitors aren’t always visible Uber blindsided the West India Company (WIC) taxi industry.
3. The Unpredictable Twist– Uber vs. Taxi
4. Complexity itself is a disruptor The Suez Canal Medal ions
blockage exposed systemic fragility.
4. The Hidden Threat– The Suez Canal
5. Adaptability wins Those who anticipate disruption Blockage survive.
5. The Final Revelation– The Big Picture 22 23 5 6/1/26 THE ILLUSION OF STABILITY
LEVERAGE FINANCIAL MARKET INSIGHTS
"If you put a frog in boiling water, it jumps
“Financial bubbles form when investors ignore warning
out. But if you heat the water gradual y, it signs” stays until it's too late."
Many companies mistake stability for safety.
Lehman Brothers ignored the risks of subprime mortgages
Enron assumed its energy market dominance gave it the
because the market seemed stable, until it col apsed in
stability to enter broadband, but it underestimated the tech 2008.
complexity and shifts in media consumption, mistaking market
stability for innovation readiness.
THE ONLY CERTAINTY? UNCERTAINTY 24 25 RED QUEEN EFFECT
CURRENT CASE STUDY Generative AI
"In business, staying in place means fal ing WHO IS RUNNING FASTER? behind”.
ChatGPT, Gemini or Deepseek?
RED QUEEN EFFECT: Run FASTER, or just stay in And Agentic AI? place. And Quantum computing? Nokia vs. Apple 26 27 6 6/1/26
STABILITY IS AN ILLUSION, ADAPTABILITY IS POWER
STABILITY IS A MIRAGE: NAVIGATING
DUTCH WEST INDIE COMPANY, BLOCKBUSTER
Question comfort: If things feel stable, ask CHANGE BEFORE IT HITS
Anticipate disruption: Watch for weak signals
Run experiments: Explore new technologies, markets, and business
1. What smal signals in your industry today could
indicate a major disruption tomorrow?
IBM From hardware to AI & cloud computing
Netflix From DVD rentals to streaming & AI content
2. Are you experimenting enough outside your
Amazon From booksel er to e-commerce, cloud, and AI
comfort zone to stay ahead of inevitable change?
Microsoft From Windows to cloud & AI dominance
Fujifilm From photography to healthcare & biotech
Disney From animation to a global media empire 28 29 INNOVATION DEFINITION 30 31 7 6/1/26 PLAYING THE LONG GAME: CREATIVITY OR INNOVATION PATAGONIA PROVISIONS
Bold Choice: Prioritized regenerative agriculture
Innovation is about executing ideas and sustainable sourcing to create value.
Short-Term Trade-Off: Slower growth and limited
Innovation is very different from scalability creativity.
Long-Term Vision: Building trust, ecosystem
health, and future-proof food systems
Creativity is about ideas and
A clear example of sacrificing speed for
innovation is about executing those ideas. sustainability 32 33 DISRUPTION & ITERATION DISRUPTION: INTELLIGENCE CYCLE
Creativity generates ideas → Innovation turns TASKING
ideas into solutions → Disruption occurs when What you want to Know
an innovation changes the market dynamics. COLLECTION DISSEMINATION The James Bond part Delivering it Observation Part NEED DEEPER SOLUTION NEED ANALYSIS PRODUCTION Making what it makes sense DO IT Making sense of it, The Story BETTER ABSTRACTION SYNTHESIS
Expanding, Reducing, Denying, Opposing
Prioritising what real y makes sense
https://www.intelligencecareers.gov/icintelligence.html 34 35 8 6/1/26 EVOLUTION DESIGNED US TO BE UNAWARE AND REACTIVE ABSTRACTION IS THE Unconscious HARDEST FOR system: HUMANS 11 mil ion bit/s “CLICHÉS” Conscious system: 60 bit/sec 36 37
REAL-ABSTRACT-REAL JOURNEY DISRUPT® Luke Wil iams, NYU Stern T AC WHAT IF STR
• “Think the unthinkable AB NARROW DOWN OPTIONS • Do the undoable” STORYTELLING BREAKING THE CLICHÉS
COLLECT AND ANALYSE DATA L A SYNTHESIS RE
DEFINE WHAT YOU WHAT TO KNOW 38 39 9 6/1/26 THE WHOLE STORY FROM PROBLEM TO OPPORTUNITY REAL USER DISCOVERY REAL EXPERIMENT ABSTRACT: WHAT IF 40 41 WHERE TO START FROM? EXAMPLES OF INTERVIEW THE USER DISCOVERY
http://youtube.com/watch? OBSERVING, v=Js4qoQp1Emo INTERVIEWING PEOPLE and CHAT GPT WHAT?
What they do and may need. HOW?
How the service/products fits into it. 42 45 10 6/1/26
THE ART OF ASKING QUESTIONS (PROBLEM FOCUS)
CL: What is it? Coffee in a paper cup
AD: What else? Coffe in a mug, cappuccino
FU: Could you include this
step/change? From coffe to tea
EL: Taking a step back, what is
the problem to address? 46 47 MODERNA FLAGSHIP PIONEERING P&G INNOVATION TO SURVIVE
Ful chain Concept creation - Delivery?
Fal ing in love with the Problem, not the solution.
Irresistible Superiority: it is about surviving by emotions, not just products.
Keep kil ing solutions, so naming company ”18”: NO ATTACHMENT
Keep kil ing solutions and project, but not Problems. 48 49 11 6/1/26 WHAT IS PROBLEM FRAMING? P&G INNOVATION QUESTIONS Are you solving the right WHAT DID YOU LEARN?
problem, or just the fastest one? HOW DO YOU KNOW?
Are you driven by curiosity or by WHAT TO LEARN NEXT? impatience? HOW CAN I HELP YOU? Do you fal in love with the
problem or the solution? 50 51 OBSERVING OR INTERVIEWING
ENTREPRENEURS? DETACHING FROM USER PEOPLE You are not your users Can you answer, what is the Be aware of your anchoring problem, after observing or interviewing? Just observe and report what is real The WHOLE PICTURE, not WHAT IS THE DEEPER NEED? YOUR PICTURE 52 53 12 6/1/26
DESIGN THINKING VS. DISRUPTIVE INNOVATION: CORE FOCUS Design Thinking: Human-centered Empathy-driven Solving user problems Disruptive Innovation:
Technology/business model focus Reshapes markets
Smal entrants chal enge incumbents 54 55 HOW THEY WORK END RESULTS Design Thinking: Design Thinking:
Empathize → Define → Ideate → Better user experience Prototype → Test Improved products/services Iterative cycle Incremental innovation Disruptive Innovation: Disruptive Innovation: New market dynamics Enters low-end market or niche Industry shifts Improves over time Old players displaced Overtakes incumbents 56 57 13 6/1/26 PEOPLE NEED TO SIT DISRUPT, STAY ON DEEPER NEED
1,3,5,7,9 DESIGN THINKING TEAMS
2,4,6,8,10 DISRUPTIVE INNOVATION
Design a better chair using TEAMS
empathy, user needs, and Make sitting obsolete iterative improvement Instructions: Instructions: Chal enge al assumptions • Expansion
Interview classmates (1–2 min) Forget what a chair is
Identify pain points: comfort, style, Reframe the problem entirely mobility, ergonomics, price Imagine radical alternatives • Reduction Sketch improvements
(architecture → exoskeleton → reclining Prototype
spaces → VR posture suspension → • Opposite Pitch the improved chair
micro-break culture → no-sit society)
Pitch a “solution” that destroys the chair • Denial Goal: market Incremental, human-centered Goal: enhancement.
Break the category, not improve it. 58 59 ANSWER NOW & THEN LET’ START FROM YOU ABOUT YOU: WHAT DO YOU HOPE TO WHAT DO YOU ACHIEVE? WHAT FEARS HOPE TO DO YOU ACHIEVE? HAVE? 60 61 14 6/1/26 DETECTING YOUR FEAR NOW, DISCOVER YOUR USER´S DEEPER NEED YOU: WHAT FEARS DO YOU HAVE? 62 63 HOW WOULD YOU EXPLAIN TO A 7YEARS WHAT SERVICES OR OLD, WHAT YOU GIVE PRODUCTS DOES THE TO THE USER? USER RECEIVE? 64 65 15 6/1/26 WHO IS THE MOST AND LEAST SATISFIED WHO IS THE USER USER? THAT USES THE MOST AND THE LEAST THE SERVICES/ PRODUCTS? 66 67 WHAT ARE THE PAINFUL WHAT IS THE MAJOR POINTS (ANNOYING) PROBLEM (IMPOSSIBLE TO FOR THE USER, IN USE) YOUR USER HAS RELATIONSHIP TO THE WITH THE SERVICES/ PRODUCTS? SERVICES/ PRODUCTS? 68 69 16 6/1/26 DECONSTRUNCTING FOOD
FERRAN’S STORY OF THE SANDWICH
AIRBNB ALLOWS TRAVELLERS TO STAY IN
PRIVATE HOMES BY ACCESSING A PLATFORM LINKING OWNERS WITH TRAVELLERS EL Bul i Restaurant by Ferran Adriá
TELEGRAM ALLOWS MOBILE PHONE OWNERS TO STAY IN
TOUCH FOR FREE BY USING INTERNET
AS AN ALTERNATIVE TO SMS MESSAGES
A [label] that al ows [users] to [benefit] by [method] 70 71
CAN YOU MAKE A TOMATO SANDWICH? A MATRIX for OPPORTUNITIES 4 DIMENSIONS FOR EACH VARIABLE Plant the seed Making it grow VARIABLES Harvest SEED GROW TIME BLEND REFINE MIX FERMENT. BAKE SOLUTION Dry Blend to make flour Idea 3 Idea 1 EXPANSION Idea 2 Idea 14 Idea 5 Refine IDEA 2 Mix with water and Yeast REDUCTION Idea 6 Idea 5 Idea 8 Idea 13 Ferment IDEA 5 Bake OPPOSITE Idea 5 Idea 11 Idea 12 DENIAL Idea 9 Idea 15 Idea 15 Idea 10 Idea 6 ABSTRACTION SYNTHESIS
Prioritising what real y makes sense
Expanding, Reducing, Denying, Opposing 72 73 17 6/1/26 INTELLIGENCE CYCLE ROUTINE vs. INNOVATION
“If I asked people, they would TASKING What you want to Know have said COLLECTION DISSEMINATION FASTER HORSES” The James Bond part Delivering it Observation Part Henry Ford CLICHÉS: ABOUT HORSES ANALYSIS PRODUCTION
Thinking DIVERGENTLY & OPENESS Making sense of it, The Story Making what it makes sense ABSTRACTION SYNTHESIS
Expanding, Reducing, Denying, Opposing
Prioritising what real y makes sense
https://www.intelligencecareers.gov/icintelligence.html 74 75 INTELLIGENCE CYCLE
AIRBNB ALLOWS TRAVELLERS TO STAY IN TASKING
PRIVATE HOMES BY ACCESSING A PLATFORM LINKING OWNERS WITH TRAVELLERS What you want to Know COLLECTION DISSEMINATION The James Bond part Delivering it
TELEGRAM ALLOWS MOBILE PHONE OWNERS TO STAY IN Observation Part
TOUCH FOR FREE BY USING INTERNET
AS AN ALTERNATIVE TO SMS MESSAGES ANALYSIS PRODUCTION
A [label] that al ows [users] to [benefit] by Making sense of it, The Story Making what it makes sense ABSTRACTION SYNTHESIS [method]
Expanding, Reducing, Denying, Opposing
Prioritising what real y makes sense
https://www.intelligencecareers.gov/icintelligence.html 76 77 18 6/1/26
DISRUPTIVE INNOVATION IN BIG DATA/AI • CREATIVITY VS. INNOVATION • DEEPER NEED • DISRUPT REAL-ABSTRACT-REAL • QUESTIONS 78 79 19