Startup is an exiting journey for the entrepreneurs. There are ups and downs and if you do it correctly there is a chance to score big at the Exit. Yet it is not an easy task by any means. According to the U.S. Bureau of Labor Statistics (BLS) approximately 20% of the startups fail during the first two years of inception, about 45% of the startups failing in the first five years, with 65% during the first 10 years.
Only 25% of new businesses survive for 15 years or more [1]. Below is an excerpt statistic on the survival of private sector startup businesses by their opening year:
Surviving Total Employment Survival Rates Survival Rates of Average Employment
Establishments of Survivors Since Birth Previous Year's of Survivors
Survivors
March 1994 569,387 4,127,123 100.0 _ 7.2
March 1995 453,105 4,135,330 79.6 79.6 9.1
March 1996 387,838 4,006,528 68.1 85.6 10.3
March 1997 345,128 3,943,372 60.6 89.0 11.4
March 1998 309,064 3,858,652 54.3 89.6 12.5
March 1999 282,466 3,716,558 49.6 91.4 13.2
March 2000 257,476 3,651,825 45.2 91.2 14.2
March 2001 236,088 3,503,445 41.5 91.7 14.8
March 2002 218,169 3,274,362 38.3 92.4 15.0
March 2003 203,484 3,115,044 35.7 93.3 15.3
March 2004 191,435 3,024,138 33.6 94.1 15.8
March 2005 180,919 2,962,277 31.8 94.5 16.4
March 2006 172,816 2,913,403 30.4 95.5 16.9
March 2007 163,491 2,855,611 28.7 94.6 17.5
March 2008 154,955 2,771,148 27.2 94.8 17.9
March 2009 145,131 2,536,302 25.5 93.7 17.5
March 2010 137,003 2,422,416 24.1 94.4 17.7
March 2011 131,017 2,405,238 23.0 95.6 18.4
March 2012 125,389 2,400,879 22.0 95.7 19.1
March 2013 120,631 2,386,345 21.2 96.2 19.8
March 2014 115,662 2,373,765 20.3 95.9 20.5
March 2015 111,209 2,357,225 19.5 96.1 21.2
March 2016 106,799 2,339,513 18.8 96.0 21.9
March 2017 102,396 2,322,735 18.0 95.9 22.7
March 2018 98,047 2,296,103 17.2 95.8 23.4
March 2019 94,347 2,249,737 16.6 96.2 23.8
March 2020 89,716 2,191,170 15.8 95.1 24.4
March 2021 85,161 2,002,502 15.0 94.9 23.5
Hence my mantra for startups: if you are failing, fail fast and fail early. But,
How to identify if your startup is on the road to failure and if so how to turn-around it?
The turn-around strategy is not easy to come by, but based on my two+ decades of years of experience in the field, I try to summarize few pointers below for your understanding, and I hope you will find them useful and include them in your business plans and strategy. If you need more in-depth discussions about your particular business scenario, please do not hesitate to drop-in a message for a free consultation.
All startups start with a great vision, yet they drop the ball in the execution. A business vision that does not stem from the customers' pain points is not likely to succeed in the market. A Minimum Viable Product (MVP) that does not address the most pressing issue of customers is not likely to raise enough funds from VCs. Forecasts and plans made on the whiteboard without consideration to the real-world practical scenarios or the target audience is likely to endup being just numbers on the board without real conversion into the dollars.
A real-world example: Shyp, an US based startup that closed its operations in 2018, after 5 years of operations, raising $62.1M in 3 rounds with 34 investors onboard.
So what went wrong?
Derived from the idea of Uber, this San Francisco based startup had everything what the investors would look for, which attracted the likes of Tim Ferris, when the world was driving crazy for on-demand service-based startups.
Shyp provided the service which would allow you to take photo of what you want to ship, upload it on its platform, have the pick up guy sent to your doorstep and then handed over to the third party delivery services.
The mistake they made, however, is: overestimating the market conditions, let alone a flat $5 fee for shipping even for small items and the extra $3 packaging charges. Unlike the essential services such as cab rides and food delivery, shipping was a sporadic activity, which they failed to consider.
Tip: If you have not spent time understanding how your customer is going to react to your business offering, then you are doing it wrong.
A great product market fit (PMF) does not automatically guarantee success, though. With evolving time, the market fitment also changes. Start-ups that might be profitable in their early years of operations might not continue to do so if they do not look outside the window on the ever evolving market conditions.
A real-world example: Before the web streaming platform came into existence, Blockbuster was a popular video rental store during 90s, with 9000+ stores and 50+ mn customers. Fast-forward to today, Blockbuster has only one store left or may be none.
Their inability to pivot quickly to the changing landscape of internet usage and deflecting the deal with Netflix for buying it for $50mn (Yes, thats right, Netflix was a young startup then), which it could have easily done then, were the pivotal reasons for its failure.
Tip: Staying successful is a continual process that requires constant innovation and open mind than being successful.
While innovation is a great way to become successful, innovating too early is also a risk. Being ahead of time is not necessarily an advantage always, especially when your offering is too radical for its time or too disruptive for the market. This is especially true for the startups operating in the emerging technologies such as Web 3.0, Artificial Intelligence, Metaverse etc. You need to time the market perfectly to make a perfect score.
A real-world example: Zoomo in 2014, based out of Bangalore, started with the aim to build trust in the Indian car resale market. The market was too young to understand how it worked and the visitors of the platform would be users who had close to no experience in the car transaction market.
Had Zoomo been launched today, it would have been a tough competition to the likes of Cars24.
Tip: Bring the change in waves, as small increments. Not all at once. Do not try to be too disruptive.
For a start-up, it is very important that all of its employees are aligned with the founder’s objectives. Dissonance between the employees and founders have turned many a startups into dust before they could every see the light of success.
A real-world example: This one does not need an explicit example, since everyone has a good understanding of how toxic culture can kill the innovative spirit of employees as well as founders. Misaligned communications, conflict of responsibilities, lack of accountability, lack of clarity on who is doing what and who is supposed to do what, etc. are all symptoms of things going in the wrong direction.
The interesting thing about culture is: one may not be able to define what a right culture should be for a startup, but one can always tell easily when the culture of a startup has gone wrong. How do you impart good culture for your startup? Defining processes is a good starting point.
Tip: Use RACI models to your advantage. Learn to implement RACI right from day one.
Early growth stage is the most critical part of a startup journey. Customer onboard, retention, scaling up the operations all need to happen in parallel. Partial or premature scaling, such as scaling up the sales team without scaling the server infrastructure or the support teams, is a dangerous move.
A real-world example: Local Banya was Mumbai's first internet convenience shop. Grocery products like fruits and vegetables, exotic veggies, groceries, personal care, household supplies, detergents, kitchen ware, breakfast, snacks, and so on were all made available on the platform. After raising $5 million, the company began to provide compelling offers by burning cash in order to boost their customer base, thereby compromising their bottom line, which led to their failure.
A Minimum Viable Product (MVP) built just for raising funds without the consideration for the future growth aspects leads to technical debt. When customers start onboarding, if the backend servers or infrastructure do not scale at the same level, businesses are likely to face SLA failures, leading to customer dissatisfaction and churn, causing retention issues.
Tip: Avoid technical debt at all costs. It can easily become a major hurdle in the growth stage.
More will be continued in the second part, coming soon...
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Gopalakrishna Palem is Startup Consultant with more than 2 decades of experience in building Enterprise Solutions and Minimum Viable Products (MVP) using Clickhouse, Web 3.0, Cryptography, Distributed Ledgers, Postgres, NoSQL, FIDO2, DID, Blockchain Development, Artificial Intelligence, IOT, Open Source, CarMusTy, CFugue, C/C++ Music Library, Carnatic Music, Song, Notation, MIDI, Typesetting, PDF, Books, Maya, Visual Effects, DirectX, OpenGL, Simulation, Predictive Analytics, Big Data, M2M Telematics, Predictive Maintenance, Condition-based Maintenance, Research. He is a Mentor for PhD scholars and is a CTO for Hire, Consulting CTO for MVP Building, CTO for Startups, providing CTO-as-a-Service, Virtual CTO and CTO Advisory Services.