Reasons for Startup Failure

The Product Failure Malaise

According to several articles and books, over 70 to 80% (some claim 90%) of new products fail or at least fail to meet the success criteria that were defined for them at launch.

• Only one percent of apps in the Apple App Store are financially successful.

• 92% of startups fail within 3 years.

• Even for the fortunate few companies that raise venture funding, seventy-five percent will fail to generate a return on investors’ capital. These statistics give credence to the assumption regarding the struggle to build successful products.

The Reasons for Startup Failure

One must be careful not to assign all the “blame” (responsibility) for product (company) failure to incomplete initial research and strategy. There could be other factors involved. For example, in the Startup Genome report, unequal (premature) scaling in one dimension is an important cause of startup failure. The five dimensions identified in the report are Customer, Product, Team, Business Model and Financials.

In our Product Success® Framework, we explore all these aspects except for Team. Business Model and Financials are closely aligned. Though a Business Model is designed and Financials are more a result of the Business Model and decisions about funding (and spending). The Startup Genome report is more about operations and looks at the results statistically rather than qualitatively.

CBInsights is the definitive source for data on Startups. They have carried out a postmortem on the failure of almost 250 companies. The comprehensive study by CBInsights over the years consistently lists the top reason for startup failure as “building a product no one wants (no market need)”.

It is amazing that out of the top 20 reasons why startups fail, almost 50% of the companies attributed it to misjudging the market need. This is an eye-popping and mind-numbing figure. Most of the startups listed in the report are not mom-and-pop outfits, but well-funded companies that raised at least round A of financing.

Another interesting infographic on startup failure:

In essence, poor product strategy would definitely seem to be one of the top reasons for startup failure. However, experience has shown that just because they are failing at something, does not mean that people are willing to try something new.

Customer Advocacy is Not Enough

The real question for us is, “Why is the abysmal state of affairs the way it is?”

There is no dearth of advocates of customer-centricity, jobs-to-be-done, and design thinking (among other approaches) in product and service development. Innumerable marketing and product pundits have been promoting not only the benefits but also the necessity of building products and marketing messages with the customer in mind.

So then why have people not listened? Why do entrepreneurs and companies big and small continue to build products that satisfy some pet peeve or serve a personal (corporate) agenda? Why do companies continue to add unnecessary features and bloat their offerings? It is hard to believe that this shortsightedness stems from pure pigheadedness. Whatever the case, it is a question that needs investigation.

One of the comments on the Strategyzer blog lays it out:

In the corporate business world, I sometimes have the feeling that there is an additional No. 1 mistake: NOT GETTING EVEN CLOSE TO THE INSIGHT of “building something nobody wants“ due to

• political reasons
• too less resources and time to work in the “business search modus”
• not enough confidence in the method and the working steps to search for new business
• change in management positions
• bad / miss-interpretation of achieved (learning) results
• wrong / not helpful measurement of the performance of the innovation team
• corporate auto-immune-system towards „innovation“ This is why many corporate BMI-initiatives are running the danger of starving a silent death.

At our end, we can hypothesize a few possible reasons:

1. People are not aware of the failure statistics and the proper methods to build products.
2. Ideas are given too much credence (importance) in popular media. The pursuit of one’s ideas is considered the holy grail of intrepid entrepreneurs.
3. Asking questions about one’s assumptions or considering that one could be wrong is looked down upon. It’s all about confidence in oneself.
4. It costs too much or is too difficult to conduct user research and it is simpler to just go with one’s instinct or with something that has always been done.
5. The steps involved in user-centric product development have not been enunciated and clarified enough. There is no easy “formula” to apply. There is still an aura of mysticism surrounding interviewing techniques and understanding customer needs.
6. “Try and try until something sticks” attitude has gained popularity. Cost of building software, renting servers, etc. has dramatically reduced. It is seductive to start building (giving an impression of movement) rather than doing research upfront.
7. Some products (product ideas) are large or complex, and appear too daunting to get inputs on.
8. Regular customer feedback and inputs are difficult to gather and there are no internal processes to capture and utilize insights.
9. It is too difficult to introduce something new in the company as it means upsetting people, processes, and existing systems.
10. The advent of big data, and the resulting stance of throwing data at a problem to somehow miraculously solve it in a blackbox fashion.
11. A combination of some or all of the above.

The Myth of Big Data

Big data, AI, Machine Learning – these are big buzzwords these days. Companies are swimming in data. There are definitely areas where this approach yields results, and there is a case to be made for using AI and machine learning (for example, in optimization of a parameter). But unfortunately, understanding humans and their behavior is not one of them. Customer motivation is multi-faceted and nuanced, and the variation in response is immense given the context and situation.

Observed patterns and correlations can feed our inquiry into jobs that people are trying get done. But there is no substitute for the ability to ask the right questions.

The Job as the Unit of Focus

Knowing the Customer is not enough (it’s an interesting topic in itself – what does it mean to know your customer?). Learning every possible attribute of a customer (Personas) is not enough. Building empathy is not enough (though it certainly helps).

What is necessary, is to understand what a customer is trying to achieve without the product. What is the gap she is trying to fill? What did the product do that fulfilled her requirement? Why did she choose this manner of fulfillment? Was there another way she could have achieved the same result? Would she choose this method every time a similar situation arises, or was there something specific about this one? What other things did she have to do along with using our product or service to completely finish what she was trying to do? Could we have done something more or something else that would have aided in that job? What are the emotional factors she considers when doing that job? Do they aid her or inhibit her in performing that task?

By thinking around the product we don’t get trapped into the product-focused mindset. We first understand the job (problem, situation, context, task) and then figure out the best way to fulfill the job.

But understanding the job in itself to be able to turn it into a successful business. Are there enough people out there that face similar situations and use similar ways to solve their problem? What are they willing to pay for? Can we deliver a product or service reasonably at that price? Is it scalable, sustainable, and profitable? These are all questions on the business model that must be answered? A lot of startups focus so much on the product, that they completely overlook this absolutely critical part. This is the factor that ultimately decides which company thrives and which goes belly up.

The third crucial component that jobs thinking brings is the concept of competition. Startups and established companies alike box themselves into product categories and completely miss out on competition that eats into the customer’s share of wallet, as well as share of mind. One of the most overlooked form of competition is non-consumption, where consumers choose to do nothing at all when they could be using a product. Or customers could be using a sub-optimal substitute to do a job that a new product could be doing much better. Studying competition in this way, also gives a good indicator acceptable pricing in a customer’s mind.

Jobs thinking gives us an excellent roadmap to iterative product development, as it tells us what is most important to the customer and why. It also tells us what jobs are currently not fulfilled to satisfaction. It’s a recipe for MVPs like no other. Moving away from featuritis to delivering true value, convenience, lower cost, less effort, or whatever else the customer is looking for in a solution. Once a product fulfills its purpose, there is no need to keep adding features. There are always more jobs to be explored, because we as humans are never satisfied; it is the human condition.

Keep it as simple as possible, and no less.

    – Albert Einstein

Success (and failure) metrics should always be defined from the point of view of the customer job – how well or poorly the product is helping them achieve it. Jobs thinking gives a very clear picture about what customers value and those are the only criteria by which a company can judge its performance.

Jobs-to-be-done offer a natural way of segmenting the market around users looking to achieve similar outcomes. Traditional marketing has relied on segmenting based on customer attribute variables such as demographic, ethnographic, and psychographic. These variables do not offer any insight as to why those segments would buy a product or be influenced by certain marketing messages. But as groups of people in similar circumstances trying to achieve similar outcomes and valuing similar characteristics in a solution, are much more likely to behave in a similar fashion, respond in a similar manner once they are made aware how a product solves their job-to-be-done.