Our real world problem
Every year, more than 75% of new and small companies from around the world shut down.
If failure is referred as failing to see the projected return on investment, then the failure rate is 70% to 80%. However, if failure is defined as declaring a projection and then falling short of meeting it, then the failure rate is a whopping 90% to 95%. (Professor Shikhar Ghosh, Management Practice, Harvard Business School)
The failure rate of companies failing and shutting down every year is staggeringly high.
This is why we are sharing our findings to encourage our audience (such as students, aspiring entrepreneurs, researchers, investors, and so on) to learn from past failures so that we can reduce costly mistakes and make data-informed decisions.
From our database, we investigated 150 startups and did a simple descriptive analysis to have an overview understanding of their top 30 reasons for failure. We also aim to regularly update the statistics in order to discover meaningful patterns so we can draw educational insights from our analyses.
First, we created a glossary of business failures that includes business terminologies and definitions commonly used by entrepreneurs and investors to classify our reasons for failure.
Second, we examined each companies’ post-mortem analyses to identify their multiple reasons for failure.
Third, from our classification of reasons for failure, we gathered a total of 82 unique reasons, and did a count of the top 30 unique reasons. We converted the sum of each unique reasons into percentage out of 150 startups, which determined the percentage of startups sharing the same unique reasons.
calculated percentage % = [(numbers of specific failure reason) divided by (total number for companies examined)] multiplied by 100
Fourth, we also counted the total of countries and total of industries that these startups were from. Similarly, we also converted the sum of each count into percentage out of 150 startups.
calculated percentage % = (n/150)*100
From our simple statistical analysis, the following charts are our findings based on 150 startups that shut down.
- Top no. 1 reason for failure: poor business model experienced by 34 startups at 23%.
According to our glossary, poor business model is defined as ‘when the business occurs high costs with low profit margin. A poor business model can also means that the business has no clear commercial or monetisation model’.
- Top no. 2 reason for failure: strong competition experienced by 29 startups at 19%.
According to our glossary, strong competition is defined as ‘when strong rivalry places a business at risk for losing its market share and/or customers to a competitor. This factor is also known as competitive disadvantage’.
- Top no. 3 reason for failure: no product-market fit experienced by 25 startups at 17%.
In order to understand what no product-market fit means, we first need to understand the definition of product-market fit. According to our glossary, no product-market fit is defined as ‘when a product was not able to meet the needs of a market, or failed to be in a good market to satisfy that market’ (Marc Andreessen, Co-founder & General Partner of Andreessen Horowitz VC firm).
It is also important to note that it is difficult to precisely define product-market fit. That said, Clément Vouillon (Senior Research Analyst of Point Nine Capital) gave a very clear explanation that product-market fit happens when the product (a set of features that have a clear value proposition) resonates with customers (which are of a certain type and have defined needs) that you know how to reach and convert (through marketing and sales).
As we are organising our database, most of our current published companies are from the English-speaking countries.
- Top no. 1 location: 70 startups at 46.7% were based in United States.
- Top no. 2 location: 43 startups at 28.7% were based in India.
- Top no. 3 location: 12 startups at 8% were based in United Kingdom.
As we are building our taxonomy of industries, we currently organized our companies into industrial groupings based on similar business activities, production processes, commercial functions and markets.
- Top no. 1 industry: 73 startups at 48.7% whose business activities are classified as internet industry.
- Top no. 2 industry: 8 startups at 5.3% whose business activities are classified as information technology and services industry.
- Top no. 3 industry: 7 startups at 4.7% whose business activities are classified as retail industry.
By understanding why companies shut down, we can draw educational insights to learn from past mistakes or mishaps in order to reduce our own rate of business failures.
Importantly, by being informed of what competitors and similar companies were or are offering to the markets, we will be able to provide more creative and valuable product-or-solution offerings to the markets.
In other words, if you know what other companies are doing or offering, you may be able to do or offering something different.
We will regularly conduct our statistical data analyses to discover meaningful patterns, and share our findings with you.
Last edited on 12 March 2020.