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Data Driven Business Creation (former Start-ups) Class Notes €7,49
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Data Driven Business Creation (former Start-ups) Class Notes

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These notes are mainly based on lecture slides. The papers are summarized and also at the end I have prepared (AI generated) 20 multiple choice questions to help with understanding the subjects

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  • 20 april 2023
  • 77
  • 2022/2023
  • College aantekeningen
  • Werner liebregts
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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

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