🏦
Data Driven Business Creation
Overview
Week 1 Introduction
Week 2 - 4 Opportunity Discovery
Lecture 1- In a nutshell (slides 2-21)
Lecture 2- Market Opportunity Set (slides 22-37)
Lecture 3- Attractiveness Map (slides 38-63)
Lecture 4- Agile Focus Strategy (slides 64-86)
Lecture 5- Implications and benefits (slides 87-100)
Week 5 Customer Development
Week 6-8 Product Development
Week 9-10 Pitching
Lecture 1
Important notes regarding the course structure:
Data Driven Business Creation 1
, In order to pass the course, a minimum grade of 5.0 is required for the written exam
(50%, individual). Obviously, one also needs to obtain a final grade of at least 6.0 as
a result of the weighted average of all four partial grades
There is no resit opportunity for the assignments except the written exam
In order to participate in the resit for the written exam, first you should fail the 1st
attempt
Lean Startup Framework
very important article: Lean startup framework by Shepherd & Gruber (2021)*
Some lean startup principles
Get products in front of customers quickly
Learn from early user interactions
Adapt plans swiftly
Testing ideas before building, committing very little, and experimenting a lot
Five building blocks
1. Finding and prioritizing market opportunities
2. Designing business models
3. Validated learning (including customer development)
4. Building Minimum Viable Products (MVPs)
5. Persevere with or pivot from the current course of action
Experimentation revisited (Felin et al., 2020)**
The entrepreneur as scientist:
“Entrepreneurs are increasingly viewed by practitioners and scholars alike as actors
engaged in quasi-scientific experimentation” (p.1)
Data Driven Business Creation 2
, Substantiated critique on the assumptions behind the lean startup:
Only generates incremental value
The business model canvas lacks specificity
Hypothesis-driven approach (Camuffo et al., 2020)**
Randomized controlled trial (RCT)
Treatment group: Rigorous hypothesis testing
Control group: Intuition and search heuristics
A scientific approach to entrepreneurial decision making …
… does not reduce the probability that startups exit
… increases the probability of finding a valuable idea after a pivot • … increases
revenue
… allows entrepreneurs to better mitigate their confirmation biases and (other)
imprecisions
The lean startup framework during this course
Four generic stages
1. Opportunity discovery: Where to play & business model development
2. Customer development: Validated learning
3. Product development: Minimum Viable Products (MVPs)
4. Pitching your idea
But: Every business creation process is different! Pivoting likely to occur!
Emergence of opportunities
Two basic origins of new business opportunities:
Creation of opportunities:
“Knowledge-push”
Based on a new technology or capability
Data Driven Business Creation 3
, Solution looking for a problem
Discovery of opportunities:
“Demand-pull”
Based on an existing opportunity
Problem looking for a solution
Creation of opportunities
Innovations that potentially have many applications,
eg. The Internet (of Things)
Artificial Intelligence
Business creation needs to find a suitable commercial application,
i.e., needs to find the right problem to solve
Need to develop the technology further, so that it solves a problem
Creates market readiness
Business model canvas
A template for developing new or documenting existing business models
Data Driven Business Creation 4
Data Driven Business Creation
Overview
Week 1 Introduction
Week 2 - 4 Opportunity Discovery
Lecture 1- In a nutshell (slides 2-21)
Lecture 2- Market Opportunity Set (slides 22-37)
Lecture 3- Attractiveness Map (slides 38-63)
Lecture 4- Agile Focus Strategy (slides 64-86)
Lecture 5- Implications and benefits (slides 87-100)
Week 5 Customer Development
Week 6-8 Product Development
Week 9-10 Pitching
Lecture 1
Important notes regarding the course structure:
Data Driven Business Creation 1
, In order to pass the course, a minimum grade of 5.0 is required for the written exam
(50%, individual). Obviously, one also needs to obtain a final grade of at least 6.0 as
a result of the weighted average of all four partial grades
There is no resit opportunity for the assignments except the written exam
In order to participate in the resit for the written exam, first you should fail the 1st
attempt
Lean Startup Framework
very important article: Lean startup framework by Shepherd & Gruber (2021)*
Some lean startup principles
Get products in front of customers quickly
Learn from early user interactions
Adapt plans swiftly
Testing ideas before building, committing very little, and experimenting a lot
Five building blocks
1. Finding and prioritizing market opportunities
2. Designing business models
3. Validated learning (including customer development)
4. Building Minimum Viable Products (MVPs)
5. Persevere with or pivot from the current course of action
Experimentation revisited (Felin et al., 2020)**
The entrepreneur as scientist:
“Entrepreneurs are increasingly viewed by practitioners and scholars alike as actors
engaged in quasi-scientific experimentation” (p.1)
Data Driven Business Creation 2
, Substantiated critique on the assumptions behind the lean startup:
Only generates incremental value
The business model canvas lacks specificity
Hypothesis-driven approach (Camuffo et al., 2020)**
Randomized controlled trial (RCT)
Treatment group: Rigorous hypothesis testing
Control group: Intuition and search heuristics
A scientific approach to entrepreneurial decision making …
… does not reduce the probability that startups exit
… increases the probability of finding a valuable idea after a pivot • … increases
revenue
… allows entrepreneurs to better mitigate their confirmation biases and (other)
imprecisions
The lean startup framework during this course
Four generic stages
1. Opportunity discovery: Where to play & business model development
2. Customer development: Validated learning
3. Product development: Minimum Viable Products (MVPs)
4. Pitching your idea
But: Every business creation process is different! Pivoting likely to occur!
Emergence of opportunities
Two basic origins of new business opportunities:
Creation of opportunities:
“Knowledge-push”
Based on a new technology or capability
Data Driven Business Creation 3
, Solution looking for a problem
Discovery of opportunities:
“Demand-pull”
Based on an existing opportunity
Problem looking for a solution
Creation of opportunities
Innovations that potentially have many applications,
eg. The Internet (of Things)
Artificial Intelligence
Business creation needs to find a suitable commercial application,
i.e., needs to find the right problem to solve
Need to develop the technology further, so that it solves a problem
Creates market readiness
Business model canvas
A template for developing new or documenting existing business models
Data Driven Business Creation 4
