Why New Businesses Fail, and What This Module Asks For

Innovation & New Business Proposal - TUHH Institute of Entrepreneurship & Institute of Innovation Marketing, Hamburg · part of my Technology Management MBA · study notes for revision.

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This module is the second stop in the Innovation and New Business Development track. The first module was about finding an opportunity and shaping an idea worth defending. This one takes that idea and asks the harder question: is there really a market, and can we actually build the thing? Every team therefore walks in carrying its own venture project, and that project stays with us for the whole semester. The brief states the consequence bluntly: there is no time to develop a new business idea from scratch here. A team may abandon its old project, but only for another idea that is already clear and already validated enough to lead real project work.

Before any tool or framework appears, the module spends its opening slides on a question that sounds pessimistic but is actually the entire rationale: why do so many new businesses fail, and why do we keep repeating the warning? Everything the module asks for afterwards is a direct answer to that question.

Tip

The one idea to carry through. New ventures die mostly for market and customer reasons, not because the technology proved impossible or the money ran out first. So the job this semester is not to polish the idea, it is to collect evidence: that a defined group of customers has an important need, that our solution really solves it, that those customers are numerous and profitable enough, and that nobody else solves it better. Evidence beats opinion, and first-hand evidence beats desk research.

1 · Where this module sits, and how it is graded

The module runs as a mix of input sessions, project work and coaching, delivered by three lecturers. The rhythm repeats: a session gives input and content, teams apply that input to their own venture in a post-session assignment, and coaching sessions review what came out. Late in the semester the coaching turns into individual appointments per team, and the module ends in a project presentation of roughly half an hour in which the team pitches the summary of everything it did.

Input sessionconcepts, methods, frameworks

→

Post-session assignmentapply it to your own venture

→

Coachingteam by team review of results

→

Project presentationthe pitch of all activities

The loop the module repeats. The input is never the deliverable; the deliverable is what the input produced on your own project.

The grade tells you where to put the effort: market, customer and competitor part 20%, business model and revenue model part 25%, prototyping and experimentation part 25%, and the final project presentation 30%. Roughly a quarter for each of the three taught blocks, and the single largest slice, about 30 percent, for the pitch at the end. The presentation is not an afterthought, it is the biggest item on the list.

2 · The number one reason ventures fail

Ask people why start-ups die and most will name money or the team. The module puts the ranking the other way round: the top reason is market and customer related. Liquidity and funding problems, team problems and competition are all real, but they come behind it.

Rank 1the dominant cause

Market and customer relatednobody who mattered wanted it, or not at that price

Also fatalfurther down the list

Liquidity and funding problemsmoney gone before the model works

Team problemsconflict, skill gaps, people leaving

Competitionsomeone else takes the position first

The failure ranking behind the whole module. If the biggest risk were technical we would spend the semester in a lab; because it is the market, we spend it talking to customers.

3 · The chain of failure

The argument is not one statement, it is a chain of four gates that an idea has to pass all of. Fail any single one and the venture is in trouble, however good the rest looks.

Gate 1 - Is the need important?most solutions address needs customers do not really care about

→

Gate 2 - Does it truly solve the problem?the need is real, but the solution is not effective and not to the point

→

Gate 3 - Enough customers, and profitable ones?a genuine, widely shared need held by too few or unprofitable customers still kills the business

→

Gate 4 - Unique and better?if competition solves it just as well, nobody has a reason to switch

The four gates. Gates 3 and 4 are the ones teams skip: relevant, widely shared needs are still not sufficient on their own.

Read as a chain, a vague worry becomes four checkable questions. Most teams are confident about gate 1 and have never seriously tested gate 3.

4 · Why real projects, and how to get the most out of them

Working on a live venture instead of a tidy case is messier on purpose. The reasons given for it are:

real-world learning opportunitycomplements case study workdevelops problem-solving skillsbuilds teamwork experiencetrains you to work with uncertainty

A case has a clean ending. A real project has missing data, customers who never reply and technical questions nobody can answer yet. The module is explicit about the working style that separates a strong team result from a weak one, and it splits into how you gather knowledge and how you run yourselves.

Get out of the building how to gather knowledge

• Take the coaching on offer. Bring problems to the coaching sessions instead of sitting on them, and use the input sessions to ask about your own project.
• Go out. Talk, interview, test. Collect first-hand information and data from real people.
• Do not stop at secondary information found with search engines and chatbots. Desk research is a starting point, never the evidence base.

Run the project properly how to organise the team

• Take the pilot seat, not the passenger seat. Own the direction instead of waiting to be told.
• Start right away and work constantly. This work does not compress into the last two weeks.
• Plan tasks and time, split the work, then join forces again and bring results together with frequent, short update meetings.

The working advice for the semester. Split the work to move fast, reconverge often so the parts still form one story at the pitch.

5 · Required results, block one: market and customer

This is the checklist the final presentation is measured against. Six results are expected on the market and customer side.

Required result	What counts as done
Validated value proposition	Checked against the market and against customer feedback through surveys, interviews or experiments, not internal conviction
Defined market and potential	The market is clearly defined and the potential calculated in a transparent and informed way (TAM, SAM), with a rough but substantiated sales prediction (SOM)
Substantiated target segments	Segment choice backed by data and justified, customer profiles clearly defined, and the most promising first target customers named: lead users, innovators and early adopters, pilot and launching customers
Assessed preferences	Preferences for attributes, features, functionality, desired performance and quality, assessed primarily on the basis of customer data
Revenue model	Outlined and justified: how money is earned, and why that fits these customers
Competitors analysed	Direct and indirect competitors examined on unique selling point, strategy, marketing approach and funding, leading to a clear market position and competitive strategy

Two details are easy to lose. The market potential must be transparent, so a reader can follow the arithmetic from the total market down to the realistic slice rather than just admire the final number. And competitors include the indirect ones: the alternative ways customers solve this problem today, often a spreadsheet, a phone call, or doing nothing.

6 · Required results, block two: product or service design

The second block asks whether the thing can actually be built, at what cost, and with which risks still open.

Required result	What it means in practice
Technological options analysed	Options compared on feasibility, cost, time and risk; the critical technological uncertainties are known and the technical questions still to be answered are outlined
Designs and first prototypes, if realistic	Wireframes or simple mock-ups where the project allows it; otherwise illustrative verbal descriptions, sketches and simple simulations, which already make research with real users far more valid
Resources roughly estimated	Monetary and non-monetary resources, including development partners and key suppliers, plus suggested ideas for getting access to them

The honesty requirement deserves underlining: naming what you do not yet know technically counts as a result. A confident claim with no basis is worth less than a clearly stated open question with a plan to answer it.

7 · The activities that produce those results

None of that appears by thinking harder. The semester consists of concrete activities:

• Scanning the market environment: market statistics, industry reports, data on target customers, competitor websites.
• Interviews and surveys with market and technology experts, targeted customers and potential partners, ideally supported by sketches, illustrations or simple simulations so people react to something concrete.
• Simple market and customer experiments, wherever they are feasible.
• Scanning technical options and solution paths that close the gap between customer needs and what the current technology can deliver.
• Calculating the main cost drivers and making a first estimate of total cost.

8 · The business-model building blocks you end up with

Put both result blocks together and you have most of a business model or business plan. These are the pieces the module hands you:

Value proposition relevance and uniqueness

• Why it matters to the chosen target customers, and how it differs from what competitors already offer

Target customers who exactly

• Product-customer fit, characteristics, needs and preferences, willingness to pay

Money and size the commercial side

• Revenue and pricing model, plus market potential built from TAM and SAM down to SOM

Product and service can we build it

• Development status, main technical risks, features still needed to meet requirements, and the key resources and partnerships required

9 · How the work is judged

Four criteria are used, and each is best read as a failure mode to avoid.

Criterion	What it rewards	The failure it catches
Completeness	Covers all, or at least most, relevant aspects	A deep dive into one favourite topic while whole blocks are missing
Methodological soundness	Key issues analysed on secondary data (reports, statistics, papers) and primary data (interviews, surveys, experiments), with visible effort to collect evidence	Confident assertions with nothing behind them
Consistency	Logical presentation where it is clear how results and recommendations were derived	Conclusions that do not follow from the slides before them
Makes the point	Precise results and clear recommendations	A tour of activities that never says what to do next

Note

Effort is judged in context. The criteria explicitly allow for the fact that these are part-time student projects, that most teams lack deep expertise in the field, and that some projects depend on input from project partners. Nobody expects an agency-grade market report. What is expected is visible, honest evidence collection and a clear account of what that evidence showed.

10 · Uncertainty, and why testing runs through everything

The prototyping strand frames the entrepreneurial process by one property: high uncertainty. It splits into two sources, and the split matters because you can act on one of them far more directly than the other.

External uncertainty outside the venture

• Technology trends: digitalisation, artificial intelligence
• Market dynamics and trade: globalisation, tariffs
• Regulation: emission standards and similar rules
• Black swan events: rare, high-impact shocks such as a pandemic

Internal uncertainty inside the venture or project

• Capability uncertainty: can we actually do this with the skills we have
• Financial uncertainty: will the money hold out and add up
• Organisational uncertainty: how the team and the structure around it hold together

Two families of uncertainty. External ones you mostly observe and prepare for; internal ones you can act on, which is where a student project team has the most leverage.

Prototyping is defined here in a way worth memorising: reducing chosen uncertainties in a targeted way, in other words learning what was previously unknown. That turns a prototype from an object into an experiment. The design perspective supports it, starting from an empathic exploration of user needs and then cycling between ideation and experimentation in both the problem space and the solution space.

There is an uncomfortable consequence. Learning in a high-uncertainty environment necessarily produces outcomes that do not work: ideas fail, projects fail, whole ventures fail. A prototyping strategy that cannot produce a failure cannot produce learning either, so you have to allow for failure in the search for success. How a team handles those failures emotionally, cognitively and conceptually is treated as a core entrepreneurial skill, not a side issue. This is why the loop of naming an unknown, designing the cheapest test that could answer it, accepting whatever comes back and updating the project runs underneath every method in the rest of the module.

Apply it to your project

1. Confirm the starting point. Write the venture idea in three sentences and check it is genuinely validated enough to steer a semester of work. If it is not, fix that now, because there is no time later to invent a new one.

2. Run the idea through the four gates. For each gate, write today’s honest answer and mark it as evidence-based or as assumption. Every assumption is a candidate for testing.

3. Rank the uncertainties. List the external and internal unknowns for your project and order them by how badly a wrong answer would hurt. Attack the top of that list first.

4. Define the market and show the arithmetic. Build TAM, then SAM, then a rough but substantiated SOM, exposing every assumption and source so a reader can follow each step.

5. Choose and justify the segments. Write clear customer profiles, then name the concrete first target customers you would actually approach: lead users, innovators and early adopters, pilot and launching customers.

6. Collect primary data. Book interviews and surveys with customers, experts and potential partners, and run simple experiments where you can. Take a sketch, mock-up or simple simulation into the conversation so people react to something real.

7. Turn what you hear into preferences. Record which attributes, features, functionality, performance and quality levels matter and how much, based on customer data rather than team opinion.

8. Map direct and indirect competition, noting each one’s unique selling point, strategy, marketing approach and funding, then state your intended market position and competitive strategy.

9. Work the technical side in parallel. Compare technological options on feasibility, cost, time and risk, write down the critical uncertainties and open questions, estimate the main cost drivers, and sketch the resources and partners you would need plus how to reach them.

10. Assemble the pitch against the four criteria. Check completeness, show the secondary and primary evidence, verify that each recommendation follows visibly from a result, and close with precise findings and clear recommendations.

Key terms

Term	What it means in plain words
Value proposition	The promise of value to specific customers: why it matters to them and how it differs from the alternatives
Validation	Checking a claim against real market and customer evidence instead of internal belief
TAM	Total available market: the whole demand if you could serve everyone
SAM	Serviceable available market: the part of the TAM your offer and reach could actually address
SOM	Serviceable obtainable market: the realistic slice you can win, used as the rough sales prediction
Customer profile	A clear description of a target group sharing needs, behaviour and expectations, used to keep the team focused
First target customers	Who you approach first: lead users, innovators and early adopters, pilot customers and launching customers
Willingness to pay	What a target customer would really part with, which decides whether a segment is profitable
Direct vs indirect competitor	Direct offers a similar solution; indirect solves the same problem another way, including doing nothing
Revenue model	How the venture earns money, and why that mechanism suits these customers
Primary vs secondary data	Primary you collect yourself (interviews, surveys, experiments); secondary already exists (reports, statistics, papers)
Prototyping	Reducing a chosen uncertainty in a targeted way by learning what was previously unknown

Test yourself

1. Why does the module insist that teams arrive with an already validated idea, and what exception does it allow?
2. Name the top reason new businesses fail and the three reasons ranked behind it.
3. State the four gates in the chain of failure, in order.
4. A team argues: our need is real, important and widely shared, so we are safe. Which gates have they skipped, and what could still kill them?
5. What is the difference between secondary and primary data, and why does the module push so hard towards the second?
6. Give the two families of uncertainty with two examples of each, and say in one sentence why they make failure a normal part of the process.

Answers

1. Because the semester is spent gathering evidence on market, customer, competition and technical feasibility, and there is no time to develop a business idea from scratch. The exception: a team may abandon its old project, but only for a new idea that is already clear and validated enough to lead the project work.
2. Number one is market and customer related. Behind it come liquidity and funding problems, team problems and competition.
3. Gate 1: the solution addresses unimportant needs. Gate 2: it does not solve the problem effectively and to the point. Gate 3: the need is relevant only for too few or unprofitable customers. Gate 4: it is solved neither uniquely nor better than the competition.
4. Gates 3 and 4. Even a real, widely shared need fails commercially if the addressable customers are too few or unprofitable, or if competitors already meet the need just as well, leaving nobody a reason to switch.
5. Secondary data already exists (reports, statistics, papers, competitor websites); primary data you collect yourself (interviews, surveys, experiments). Primary data is pushed because search engines and chatbots cannot tell you whether your specific customers care, and methodological soundness is judged on visible evidence collection.
6. External: technology trends and market dynamics or trade, plus regulation and black swan events. Internal: capability and financial uncertainty, plus organisational uncertainty. So much is genuinely unknown that any real learning strategy must allow for outcomes that do not work, which makes failure a by-product of the search rather than proof of a mistake.

Revision summary

Tip

The one-minute recap

• This is the second module of the Innovation and New Business Development track. Teams carry their own validated venture idea through it; there is no time to invent a new one from scratch.
• Taught by three lecturers as input sessions plus project work plus coaching, graded roughly a quarter for each of the three teaching parts plus about 30 percent for the final project presentation.
• The number one cause of failure is market and customer related, ahead of liquidity and funding, team problems and competition. That ranking drives the whole module design.
• The chain of failure has four gates: unimportant need, ineffective solution, too few or unprofitable customers, and not unique or better than competition. All four must be passed.
• Real projects are used for real-world learning, to complement case studies, and to build problem-solving skills, teamwork and the ability to work with uncertainty.
• To maximise learning: take the coaching, go out and talk, interview and test rather than stopping at search engines and chatbots, take the pilot seat, start immediately and work constantly, plan tasks and time, split the work, then reconverge with frequent short updates.
• Market and customer results: validated value proposition; defined market with transparent TAM and SAM and a substantiated SOM; justified segments with clear profiles and named first target customers; preferences assessed from customer data; revenue model outlined and justified; direct and indirect competitors analysed with a market position and competitive strategy.
• Product or service design results: technological options analysed on feasibility, cost, time and risk with critical uncertainties named; designs and first prototypes where realistic, otherwise descriptions, sketches and simple simulations; monetary and non-monetary resources roughly estimated with a route to access them.
• Activities: scan the market environment, interview and survey experts, customers and partners, run simple experiments, scan technical solution paths that close the need-to-solution gap, and calculate the main cost drivers.
• Four criteria: completeness, methodological soundness with secondary and primary evidence, consistency of the logic, and making the point with precise results and clear recommendations.
• All of it rests on uncertainty, external (technology, market dynamics and trade, regulation, black swan events) and internal (capability, finance, organisation). Reducing it in a targeted way is exactly what prototyping means, which is why learning by testing, failures included, runs through the entire module.

Next: Business Model Innovation → - the canvas, the patterns and the ten types.