3 Mistakes I learned from my Start-Up

  • Poor Value Propositions can kill your business.
  • Avoid Complicated Problems. Embrace Simple Problems.
  • Don’t build a team unless, you have funding.

OpenVessel was a start-up I attempt to get off the ground back in 2020 to 2021. When the Covid pandemic started I was in the middle of a program called Nittany AI Challenge at Penn State.

We were awarded for $5,000 for our technical solution & pitch. I learned many lessons from that experience. However, today’s lesson will, be about the business mistakes & technical side of OpenVessel. What mistakes we made as a start up and hopefully you can avoid also.

My advice for anyone is to learn about good value proposition and communication first. Take a paper and pen and figure out your value proposition all over again. It was most likely not good in the first place. A vague or broad value proposition can kill your prospects.

Unfortunately, OpenVessel ultimately failed as a start-up. It could not communicate its value to investors or trigger purchase from its customers. OpenVessel had a poor value proposition. What does poor value proposition look like? Let’s take a look.

We served as an “AI research consultant”. We offered services to develop data science solutions. Our target was academic physicians.

Ok a niche is good. However, the proposition of a consultant is vague. It doesn’t speak to academic physicians. It was nowhere near what their real problems were about. Value props speak to or relate to their specific problem so it didn’t catch on. This was very long value prop and it was not concise for reader.

What does a good Value Prop look like? QuickBooks is a great case study on good onboarding design. Their Value Prop on the front pages directly addresses the customer’s problem. Small businesses want to save time and track their money. People are already aware of their own problems. Speaking to it directly, like save time and track money, is straight to the point.

When it comes to writing good Value props you have two options

  1. Speak about what the person cares about and values
  2. Compliment the person, then say However (Reasons they are wrong/tell them something they haven’t hear before)

If you want an in-depth answer on how to communicate value to others, I recommend this lecture by Larry McEnerney. He is the Director of the University of Chicago’s Writing Program. It’s the best example of how people write in the real world.

Communicate concisely and valuable.

Because of this lecture my email got my foot in the door with my first customers.

This led us to refactoring & building system a algorithm called Liver Segmentation.

You can check our improvements on the Liver Segmentation Model with from Github here https://github.com/OpenVessel/liverseg-2017-nipsws its open source.

Well you could be asking what does liver even mean? What are you even going on about? In short we basically had take 1000s of slices(images) that compose CT scans images basically detect tumors. This leads into my second Mistake.

Nittany AI challenge had four areas of application you had to chose Environment, Health, Humanitarianism, and Education. We chose health. I cannot stress enough that there are many problems in healthcare. These problems include technological, political, data storage/privacy, and culture issues riddled within healthcare.

AI/ML learning cannot alone fix healthcare’s problems. Many stakeholders, including doctors, patients, clinical researchers, software engineers, administrators, IT departments, and insurance companies, must get involved. This collaboration is necessary to move the needle for problems inside the healthcare system. Healthcare is too expensive in the United States. There are no mechanisms or incentives to make optimized improvements. These improvements could save time, save money, and save lives.

I am not saying don’t solve those problems. Choose smaller problems that you can solve faster than the big problems. There is a massive amount of problems/burning pain points in healthcare. These can translate to opportunities for start-ups/investors worth billions. However, political and cultural barriers make it challenging for a small team of college students to effect change. These obstacles were too great to overcome at the time. That was OpenVessel. So chose wisely.

We performed Pro Bono work for a institutions it took 4 months and total of 1,680 hours of work. To create value and impact, we must change healthcare.

This requires a PhD (integrity and experience). We also need healthy funding (Immense Wealth) and political capital (Trust and connections to leadership). These elements are necessary to make any improvements in the healthcare system.

Which are really obvious reason, but before you take on a complicate problem, find Integrity, Experience, Investors, and Make connections.

Otherwise chose a simply problem.

This was one of my greatest mistakes. I wish I could have rewarded my team better for their hard work and contribution. OpenVessel as a failed start-up but it was worth it for our careers. It launch padded so many opportunities for members our team & myself. Even if it’s hard to do, you will fail at some point. However, it was worth doing to build skills that translate into the future.

If you are in a leadership position, don’t convince so many people to join. Focus on building the company with those who are already spending their time with you. I questioned whether it was worth continuing OpenVessel or disbanding it.

Was it a sunken cost fallacy? or were we onto something? So we did math and found out we were unsustainable unless we closed a large contract.

These were the lessons I wish I knew or someone had told me about when starting a start-up company. I just wanted to thank everyone. Special thanks to all the team members at OpenVessel: Rishyak Panchal, Nathaniel Leies, Gregory Glazter, Alexander (Alex) Schweizer, and Nathan Reilly. They saw the closing of OpenVessel. Also Dane Sapienza for handling the legal stuff thanks for supporting us there. Finally, all the Interns Amber Lai, Ethan Wright, Lindsey Xu, and Vaibhav Gupta. And many others I could not name, we had ton of support. I will keep writing these lessons, and educating others in programming.

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