Why Do Most Startups Fail?
According to my significant research on the predictability of success and failure of startups, I would argue that there is a whole host of primary business principles that collectively lead to success or failure.
And this goes way beyond the amount of capital raised or the quality of the team. When I first turned to Quora to answer this question, I saw many answers about a "lack of sufficient capital", which is way too simplistic and according to my research, that kind of statement is just plain erroneous. Take Webvan for example, one of the largest dot-com disasters. They raised $1.2 billion and still failed. Not enough capital? I could give you many more examples of high-profile failures that raised mountains of cash.
And many VCs say it’s all about the team. "Just invest in a great team and they will get it right." Baloney. Webvan had $1.2 billion AND a stellar management team of some of the smartest (albeit most arrogant) executives on the planet. According to my research into the predictability of success and failure of startups and when analyzing them with the Opportunity IQ, a "rate my business" business plan scoring app I created, Webvan actually had four fatal flaws that were completely predictable. More on that in another post.
To set the stage on this topic, let's first look at the incidence of failure. According to Harvard Business School research, 70 to 80 percent of all startups fail to deliver a return on investment to investors and a whopping 90 to 95 percent fall short of meeting projections. Many experts agree that between 50% and 90% of all startups shut down completely within the first few years.
Harvard Business School’s Shikhar Ghosh explains the problem like this:
"Start-ups often fail because founders and investors neglect to look before they leap, surging forward with plans without taking the time to realize that the base assumption of the business plan is wrong. They believe they can predict the future, rather than try to create a future with their customers. Entrepreneurs tend to be single-minded with their strategies—wanting the venture to be all about the technology or all about the sales, without taking the time to form a balanced plan…failure is the norm."
But startups aren’t alone. According to my research, most business opportunities from startups to acquisitions to new product launches have similar failure rates. In addition to an incidence of high failure rates, if a business does successfully get off of the ground, the likelihood of ever reaching meaningful size and revenue are slim indeed.
In a survey conducted by the Association for Corporate Growth and as mentioned frequently in Fortune magazine, only 5% of companies ever reach a paltry $1 million in revenue and only 0.625% make it to $10 million in revenue, that’s only 1 out of every 160 companies that successfully get launched that ever make it to the lower middle market in terms of size. Given all of the above, it’s safe to say that most business opportunities of any nature fail.
To diagnose the issues, first, let’s look at how decisions are made by entrepreneurs (and everyone else).
Startup Failure Issue #1: We Make Decisions Emotionally
When we pursue an opportunity, whether it is the next big startup idea, a very attractive acquisition or investment candidate, that new franchise that is exploding, or a new product idea that might change the world, we get emotionally attached to our opportunity. As neuroscientist Antonio Damasio has discovered, we make decisions emotionally, not rationally or logically.
Damasio explains his findings as follows:
"Often we feel emotions instinctively…gut feeling “marks” the chosen alternative, coloring it with a certain emotional hue so that it is more salient than the other alternatives…As psychologists and behavioral economists have shown, the average person’s day-to-day reasoning is often quite faulty. The human mind is terrible at calculating probabilities and a vivid, dramatic image can dominate someone’s mental landscape. For instance, a person may be quite scared of flying after picturing a plane full of screaming passengers dropping 6,000 feet out of the sky and exploding. Yet the same person may be quite comfortable traveling by car. The irony is that the odds of dying in a plane crash are far lower than the odds of dying on the freeway."
Pursuing an opportunity is rather like that exuberant emotional rush of being in love and overlooking the other person’s flaws that are obvious to everyone else. That leads to a very real problem. Our emotional attachment to our opportunities means we tend to turn a blind eye to the potential issues and not fully explore the downsides.
Every venture capitalist sees this with entrepreneurs during a “pitch” meeting. The entrepreneur is often so wildly enthusiastic about his or her idea that they don’t seem to rationally listen to any potential risks. On the other side of the table, in the “deal” world, those pursuing an acquisition or investment will often go with their “gut” because they really like the entrepreneur, the management team, or the deal itself. There is a saying that acquirers and investors tend to “cave to close” and give up key terms just to get a deal done. It’s the same for any opportunity. We are emotionally wed to our pursuits and we don’t want logic and reasoning to get in the way.
But even when we do analyze an opportunity, there is another problem.
Startup Failure Issue #2: We Resist Deep Thinking or Analysis
The Nobel Prize–winning economist Daniel Kahneman points out that even if we take the time to analyze something, we tend to stay on the surface in our analysis and come to quick, erroneous conclusions. It's a problem he identified as the “Law of Small Numbers.” We tend to take a few inputs and then make huge leaps in our judgment and fake ourselves out to think that we’ve properly analyzed the situation. We rarely spend the mental effort to really analyze a situation, much like how we tend to hate to learn math because it is mentally grueling.
Kahneman describes the two-system theory of emotional vs. rational decision making as follows:
"Many of us who study the subject think that there are two thinking systems, which actually have two very different characteristics. You can call them intuition and reasoning, although some of us label them System 1 and System 2. There are some thoughts that come to mind on their own; most thinking is really like that, most of the time. That’s System 1. It’s not like we’re on automatic pilot, but we respond to the world in ways that we’re not conscious of, that we don’t control. The operations of System 1 are fast, effortless, associative, and often emotionally charged; they’re also governed by habit, so they’re difficult either to modify or to control. There is another system, System 2, which is the reasoning system. It’s conscious, it’s deliberate; it’s slower, serial, effortful, and deliberately controlled, but it can follow rules. The difference in effort provides the most useful indicator of whether a given mental process should be assigned to System 1 or System 2."
He goes on to explain the problem with why decision makers rarely delve into System 2 thinking:
"Emotion becomes dominant. And emotion is dominated primarily by the possibility, by what might happen, and not so much by the probability. The more emotional the event is, the less sensible people are. So there is a big gap."
One of the reasons I created the Startup Financial Model was to help entrepreneurs and startup founders and teams use our business plan template to quickly create a very detailed and very thorough set of financial statements, financial ratios, and key metrics -- such as Customer Lifetime Value -- to help them be much more robust in their startup planning.
Kahneman also pointed out the real problem of optimism that we see so much in entrepreneurs and business opportunity sponsors:
Startup Failure Issue #3: Entrepreneurs Are Too Optimistic
Kahneman's research also showed that one of the major biases in risky decision-making is optimism. Optimism itself is a source of high-risk thinking. But aren’t business decisions usually rational decisions? Let’s look further at how we actually act rather than how we should act.
Startup Failure Issue #4: We Resist Tracking Decisions and Applying Lessons Learned
Kahneman further notes that typical business decision-making processes are flawed because of the lack of decision analysis and the lack of capturing lessons learned:
"The thing that astonishes me when I talk to businesspeople in the context of decision analysis is that you have an organization that’s making lots of decisions and they’re not keeping track. They’re not trying to learn from their own mistakes; they’re not investing the smallest amount in trying to actually figure out what they’ve done wrong. And that’s not an accident: They don’t want to know…they won’t want to do it."
Now that we know we need additional rigor and accountability in our analysis of opportunities, where do we turn to find that?
Startup Failure Issue #5: We Lack a Rigorous Opportunity Analysis or Due Diligence Framework
The more I studied this issue of high failure rates, the more I realized that there wasn’t a good framework or construct for analyzing an opportunity. Most decisions and business due diligence were simply ad hoc. I saw this in the Fortune 500 world, the venture capital investment industry, the investment banking industry, the M&A process, and with startup entrepreneurs. There was a lack of process discipline around what to analyze and how to objectively measure the opportunity to assess its probability of success or failure. There didn't seem to be a good process for filtering out all of that dangerous optimism.
Over the years I’ve read thousands of business cases in business school, thousands of news stories about business, and thousands of business plans. And I’ve advised hundreds of businesses, from rank startups to Fortune 500 clients. I’ve also invested in startups, launched many businesses, and acquired quite a few others. So I went on a journey of discovery and analyzed everything – what went wrong and what worked well in all of those different situations.
What I discovered was that in most cases, the outcome of a particular opportunity was completely predictable. No matter how much entrepreneurial energy, no matter how much wild optimism and no matter how many hours of effort poured into an opportunity by a high-quality management team, if the business model was fatally flawed, the opportunity failed. As it turns out, there are many core principles at play that can be identified and measured to predict success or failure and used to vastly improve an opportunity once the weaknesses are known. In response to this issue, I created Opportunity IQ with 50+ proven principles ranging from the market dynamics to the financial characteristics to the operational characteristics to the offering itself to the customer relationship – all of which can be used as a tool to measure and assess any business opportunity.
I also created the Startup Financial Model to address the primary weaknesses of not understanding the key financial aspects of the business plan: break-even timing, burn-rate, fume date, how much cash is required, the impact of the business model, etc.
Example Principle That Affects Success or Failure
For example, let’s look at just one of the principles and its impact on potential success: the Cash Cycle. I define the Cash Cycle as follows:
Cash Cycle: The average amount of elapsed time between when an opportunity experiences the costs of the offering being delivered and when the cash is collected from the customer.
The more efficient the Cash Cycle, the faster you get paid, and the better the opportunity. The more efficient the Cash Cycle, the more cash flow is generated, and the less the need for external financing for working capital and growth.
Many business models have problematic Cash Cycles, especially any opportunity that requires an offering to be produced ahead of demand.
Let’s look at two easy to understand examples: spec homebuilders and automakers. Both types of businesses invest heavily in labor and materials for up to several months in advance of selling a home or a car. Both types of businesses consume enormous amounts of cash to fund growth, usually in the form of debt. And during economic downturns, they often go bankrupt when sales slow down, their Cash Cycle lengthens, and they can no longer service the debt on their balance sheets.
By contrast, e-commerce business models like Amazon are usually amazingly capital efficient because they get paid up-front by charging the customer’s credit card first and only later experience the costs associated with processing and fulfilling that order, which in Amazon’s case, is outsourced to the publisher or manufacturer. (Because of Amazon’s scale, it has the negotiating leverage to extract extended payment terms.) This type of Cash Cycle means Amazon continues to grow their cash as their business grows rather than consuming cash. The faster they grow, the more cash they produce. Any e-commerce or SaaS app startup will have the same advantage, but only if you plan your business model and customer billing choices correctly.
Objectively and rationally measuring the Cash Cycle of your startup is one example that should be on everyone’s due diligence list prior to launching or investing in an opportunity, yet most entrepreneurs are completely unaware of the principle and very few ever measure its impact.
To greatly simplify the need for heavy-lift analysis, you have up to a dozen choices on billing and collecting cash from customers when writing a business plan with our Startup Financial Model app. Our app also allows you to very quickly see the impact of your business model inputs. For example, if you are writing a SaaS app business plan, billing and collecting from your customers quarterly in advance, instead of billing and collecting monthly in arrears, has an enormous impact on how much capital you need to raise from venture capital investors. You are financing much of your growth with customer cash if you are billing quarterly in advance and will need far less capital. Our app allows you to see the impact with only a couple of clicks of your mouse as you toggle back and forth between billing choices and see your cash balance change. And, importantly, our app automatically handles the appropriate accounting, such as adding Deferred Revenue to your Balance Sheet when billing and collecting in advance.
The bottom line is that startup failure is astonishingly high. However, the good news is that you now have some very powerful tools to help you tilt the odds in your favor.