Adapt to Thrive: The Role of Pivoting in Startups

Jolly Nanda, CEO & Founder of Altheia

Note: This is an edited transcript from the MedTech Summit talk Jolly presented on July 8, 2025.

Introduction

Pivoting is sometimes a hard topic to talk about, but I'll first start with just introducing myself. I play several roles: mom and wife, dishwasher, laundry fairy—I love doing laundry, it relaxes me.

I founded two companies, Althea, which is a healthcare SaaS platform, and I've had VIKIRITI management consulting for about 10 years now. I have two decades of corporate experience and throw some startups in there as well. So over a decade plus of entrepreneurship experience. I speak from experience in healthcare, life sciences, consulting, manufacturing, and high tech retail. I'm an avid gardener, love arts and crafts, and I'm a foodie.

The Reality of Startup Statistics

We've all heard that 90% of startups are doomed. The stats are actually quite sad.

First of all, it takes tenacity to be a founder with stats like this thrown at your face every day. We have only 10 to 20% of startups that actually make it in the long term. We have 34% that fail because of product market fit. 10% just die off the first year. And you can see the stats—the main areas of focus are either you don't have your marketing strategy correct, it's either your team, cashflow issues, and operational issues.

Those are the basic categories. So you really have to either be really stubborn or true to your mission. And that's what makes pivoting really hard. Because most founders are extremely passionate about what they do. They're not in there just to make money quick because with these stats, no one in their right mind would go, "Hey, let's go do this to make some money quickly."

When you talk about pivoting, it's really hard for founders to do that, especially in life sciences and healthcare because the investment it takes to get something to market is just so long.

Why Pivoting Matters

So it is really hard looking at why you pivot, and why you must think about when does it matter. If you look at the areas that I talked about for why they fail, you've done the upfront work, especially in healthcare and life sciences. That's the first thing you do—you do your product market fit. And if nothing changed, then we'd be golden.

But nothing in this world is static. So everything we do constantly shifts. Market shifts, needs evolve. What you thought was novel, what you thought was unique and have an IP for—people reverse engineer and boom, or have a different solution for the same problem. And now it's no longer novel. So in the land of AI and reverse engineering, you need to move and you need to move fast.

Success Stories

Curative: Multiple Pivots

Let's take an example of some companies that have actually thrived with pivoting. I really like the example of Curative. From a life sciences and healthcare audience, people will know who they are. They went in, and they were a startup for sepsis diagnostic, and they were going to market to hospitals. And this was in 2020. And so what was going on in 2020? There was COVID-19. Hospitals were overwhelmed.

And so what they did was they quickly decided that they were not going to get into the target market for sepsis. So they pivoted and developed a COVID-19 diagnostic. And they did really well. And then, of course, the pandemic also died down. So they knew that was coming. They learned over time how healthcare insurance was working and not working, and they actually became a health plan at the end of it. So they went from being a diagnostic company to now being a health plan. I mean, that was a major pivot and they did it successfully.

So the theme here is, some companies can pivot and some companies pivot drastically. So the first pivot here going from one type of disease to another, from one diagnostic to another, kind of made sense. They have the expertise, and they're applying it in a different way. But going from being a diagnostic company to now being a health plan, that's major. So it really takes a lot to think through, "How are you going to do this and should you do this?" The key is knowing when to pivot.

Conceptus: Learning from Unexpected Results

I'm going to bring another example of a pivot that a life sciences company did. And that was Conceptus. They started with a mission that they wanted to help women conceive. And they were developing a catheter to open blocked fallopian tubes. Well, internally, during testing, what did they find out? It did the opposite.

So they had to listen to what the data said. It was blocking the tubes rather than opening them. And so they made the decision that, "Okay, well there is a huge market out there for a non-invasive sterilization method. Perhaps we go after that market."

And they did. But it took a significant amount of work to go from the mission of "we want to help women conceive" to now saying "there's an unmet need for a minimally invasive sterilization method, and we're serving that market."

But you have to be able to make those decisions if you want to stay alive. You have to be brave, flexible to be able to do that. And by pivoting they basically became the market leader and they generated over a hundred million dollars of annual revenue by pivoting.

When to Pivot

Recognizing the Signs

First of all, there have to be signs. You can't just pivot willy-nilly. There has to be some core data that's guiding you and telling you that you must pivot. Because it is a big decision. And you have to be looking at, constantly looking at feedback from your customers, your investors, but also what your employees are saying internally, because they're the ones coming up with data. And that data is really important into saying, "Okay, well what is the data telling us?"

Should we pivot from a customer segment? Should we actually pivot from a product? Should we pivot manufacturing? There's all these decisions, and again, it has to be an inclusive decision while you're making it.

The Challenge for Healthcare and Life Sciences

But how do you recognize when you can make that pivot? Especially for startups, healthcare and life sciences startups, the regulatory pathways, clinical trials is just a long runway that you have to have, and the funding dictates whether you're going to make it or not. So you have to decide quite early on, like even when you're pivoting—will you extend the runway if you pivot and make it, or are you going to pivot in the hope that money will come with the new pivot? Both risky choices. So it definitely requires some risk taking, and that's why I go back to ensuring you have the right data.

You have the feedback from the customers and really understanding the market and that it is changing constantly, keeping a pulse there, listening to what is the investment community telling us. And that's so important. And then what's your team telling you, because you can't go on this journey by yourself. The team has to be there. So whatever pivot that you make, it is a risky gamble, but it takes strength to be able to do that.

The Emotional Aspect

This is why it's really hard to make a pivot. It requires a growth and learning mindset to first look at data, to be able to proactively say, "Okay, I'm okay with pivoting." And like I said before, most founders, they have a mission. And your first couple of people that came on, they came on because of that mission. And when you pivot, you are not just impacting the founding team. You're impacting the whole company. Who's bought in, who's not?

I go back to again, the first statement that I made—founders are usually motivated by their mission or idea. Most will not pivot from their original idea. And particularly in life sciences, because of that regulatory pathway being so long, pivoting may not work. Because again, it takes so much time, even if you pivot, it may take so much time to get through all of the clearances that you need to be able to do all of the clinical trials.

And on top of that, when you add that emotional tie to the mission—I'm going back to the sepsis company where their mission was to reduce deaths. What were they feeling and thinking when they were pivoting? Well, during COVID, that was probably the right move and probably an easy one because their mission was about reducing death. And so the COVID tests really tied nicely to that mission. They had an easier path to get people on board internally and from a market perspective externally to say, "Hey, our mission hasn't changed." But it definitely was a different disease. They got lucky because the regulatory pathways were accelerated to get the COVID tests into the market.

If it had been during normal times and they were pivoting from one disease to another, it may not have worked for them. Sometimes there's a little bit of luck involved, timing, things that you don't really have control over—the timing just has to be right as well.

Building New Expertise

In some cases where you are pivoting, and I look at the other example where they went from the next pivot that they did from a diagnostic to being a health plan, did they even have the right expertise from an industry perspective? They had to open up and say, "Okay, we're experts in diagnostic. Hey, now we need to add some team members who are experts in healthcare and healthcare plans." And they had ideas around how to make it better because they had heard all of this feedback during COVID of what didn't work correctly, and they had a vision of what they wanted to do with it.

But how to do that requires industry expertise. And for some founders that started the company because they had that true expertise to begin with, you're basically saying, "Okay, well now I'm going to go into sort of an unknown territory and I have to be okay with it, that I'm going to bring experts, I'm going to listen to them and I will take the advice." And that takes guts too.

Getting the Right Support

So a key thing is you have to be able to not only ask for help during these key moments, even being able to talk about deciding what do you want to pivot. Sometimes it's not as easy as the data is telling you to go from, "Oh, well here it's blocking the fallopian tube"—a very easy decision to say, "Okay, it's a contraceptive versus helping with conception." Sometimes it's not that clear cut.

And so having people to talk to through this whole journey as a founder, or as a founding team or a management team, is very important because, speaking from experience, we spend a lot of time making our dreams come true and working on our passion. And yes, we have people to talk to, but usually when we're talking to them, it's about something that we want to deliver versus having the right kind of thought leadership and the thought partners to be able to help make those decisions where it's an honest discussion and a frank discussion.

So for your own mental health, if you don't have those in your startup as a founder, please get them. Please create a community for yourself so you can talk about what you're seeing, what you're noticing, talk through the data, whether it's within your team or externally. Get a friend, phone a friend, get the right expertise. And you're going to experience change when you're making pivots. You are going to potentially have to switch out people on the team, and everyone from the actual people working in the company—your advisory board members might change as you pivot. And it is a hard, hard decision.

How to Pivot Effectively

Data-Driven Approach

So how do you pivot effectively?

Letting the data guide you is really number one. Being transparent, being inclusive, collaborative, and communicative, and saying, "Okay, things are moving fast, but I still need to talk about it." You can't make a decision in a vacuum. Is this new play going to work? What do we need? You can't do everything. In most life sciences companies, it's not just a one person show; you need so many skills. It's not just, "Hey, I came up with this little device or a trinket that I'm selling."

This is like life changing stuff that we're developing. And you have a team of experts that are working with you. Leverage your team. Create a hypothesis based on the data that you're seeing and create some metrics around, "Okay, if I'm going to pivot, if I'm going to test this pivot, what are some of the metrics of success? What are those KPIs and how long do I run this test?" All of those are just so important.

But also you have to have those thresholds, but account for some of the variances. Account for, "Hey, even within the test period, things might change." So even though you have to be bold and you have to make decisions, you can't be too rash. I know this is going flipping and flopping, but you can't be too rash. So you have to give it enough time to do the test, have the data come in. But if the data tells you that you need to pivot again, you should seriously look at it. Because that's what the data said for your test. So that's not a rash decision. If you need to pivot again, that's embedded with data and learnings.

Staying Agile

So you can be agile. And I threw up a picture of a hockey game here because what's more fast changing than a game of hockey? You blink and all of a sudden there's a fight that breaks out. But they have to come back as a team if things are not working, you come back as a team and say, "Okay, well let's try this new play." And guess what, if it doesn't work, you go time out. Let's regroup again. Let's use that same concept that when you're not getting the results that you'd already outlined KPIs for, then you do need to take a timeout and look at, "Is it time to pivot?" But again you should be inclusive and it should be driven by data.

Learning Curve Examples

There's usually a huge learning curve, as I mentioned previously, when you make a pivot. And sometimes it's internal, where the pivot that you're making—the last example I gave where they had to get new expertise going from a diagnostic company to a health plan. Well, another example of this is when they had to do that from an external perspective.

So you look at Intuitive Surgical. In the late 1990s, they designed the Da Vinci system, and they were focused on cardiac surgery. Their hypothesis was that they could enable less invasive cardiac procedures—complex surgery with smaller incision, reduced trauma, faster recovery.

The steep learning curve though was on the cardiologist surgeon, and so it limited their ability to make traction that they needed. But what they noticed was in other areas of general surgery, urology, gynecology, where people were experimenting with this, it seemed like the adoption was faster, the results were compelling. So even though their mission and what they were measuring from a KPI perspective were grounded around cardiac procedures, they looked at the data and they're like, "Okay, we know that works. But the learning curve, this is too high right now. Too risky. Let's just go look at the data for general surgery and see how we can roll this out." And they did.

So they rolled it out for urology, general surgery and gynecology. And eventually, they drove the adoption over time, but they also had to change the hypothesis.

Their new hypothesis was that robotic assistance can deliver superior outcomes in a broad range of minimally invasive surgeries. So they removed cardiology out of it.

And the original metrics were patient recovery time, surgical precision, and complication rates, and adoption by cardiologists. They took that and they changed the measurement when they did the testing to say, "Okay what is the growth rate or growth volume for robotic surgeries?" That was their new metric. And what was the surgeon adoption rate and training feedback.

So they made it more generic, removed cardiology out of it, and from a patient outcome, they basically said it was to reduce blood loss and to have shorter hospital stays, which worked for them. So again, it was a slight tweak, but they were eventually able to get to where they wanted to go and penetrate cardiologists—it just took them a longer route. They had a broader market. That's a win-win story.

Lessons from the Trenches

Pivoting is not an overhaul. Sometimes it's just very small and sometimes it just happens. And I'm going to tell you about Althea, which is one of the companies I have. We were focused on the self-funded employer market with our SaaS product. And obviously with the economy, with all of the distractions, the sales cycles are so long. We had Medicare new codes come out last year with care management codes. It opened up certain markets.

So our product was always designed for any risk bearing entity. It could be sold to provider systems, it could be sold to payers, self-funded employer groups, because at the end of the day, it was a B2B2C solution. We'd always thought of going to care management companies, but we didn't expect the first customer to be a care management company—first paying customer. But that's how it ended up happening.

And it all happened because the market situation was such that we were focused on cost savings and better outcomes. And now we're like, "Oh, well, for providers and care management, this is revenue generating. They have new codes and we enable them to be able to have access to them."

Pivot. But it's not a magical fix. Sometimes it's easy to do that pivot because overall our core strategy, our core product, none of that changed. Our pricing strategy—nothing changed. It's just that our customer segment changed. The first target customer changed. So sometimes it's just a small pivot.

Building the Right Culture

And we all know that most companies that actually succeed pivot at least once. And some pivot more. So the only thing I'll leave you with is you have to have the culture of resilience to be able to succeed. And that whole collaborative learning kind of mode where you're listening to the team, your customers and the curiosity to say, "Okay, is it working or do I need to learn something about this and make a change?" So that adaptability and all that growth mindset that we've heard about, talked about, you need to embody them, not only in yourself, but in the culture of the company. And that's when you can make pivoting successful.

It's nice to have a slide to remind you that even if you're scaling, it doesn't matter where you are, in which stage you are, you should always be using that agile method to say, "Does something need to change? What needs to improve?" And that could result in a pivot. It could not, but having that mindset may help.

So here's a little cheat sheet you guys can use, to always keep in mind that pivoting isn't about making a huge change. It could be just small changes, but having that growth mindset to be able to constantly look at things and say, "Okay, what can I do better?"

And then the other tool is the five top reasons why startups fail. And this is just a quick de-risking sheet to ask yourself within these categories, questions to help prompt that you've done these. Or if you need help, talk to somebody.

Q&A

John: How do you start a conversation with somebody within your organization about, "Hey, are you seeing signals that show that we need to pivot?" How do you bring up that topic? How often do you have it inside of your organization?

Do you do that in a one-on-one or in a team meeting? What's your approach to that? Because it seems like you really have to have lots of input, a great handle on all the data and things happening.

Jolly: Yeah. A lot depends on the culture and the discipline that you have within the company, the cadences that you follow. In cases where I've seen this work really well is that they are having regular meetings. And they are coming together not just as a founding team, but as a whole team that's working on the product. And they've got the communication channels in place.

So the information is flowing freely, and they are having discussions of, "Okay, this is not working." It's more about having those discussions, framing that as collaborative discussions. And you're looking to just get advice or find a new way to make it work. And through that conversation, there's a point in time where you've spent enough time looking at the data and you have to ask, "Okay, we've tried X, Y, Z. What haven't we tried?"

And is it time? And the data is usually there. It tells you what you need to pivot to. During COVID, a lot of people pivoted to diagnostics or protective gear and all of that. It was the market basically telling us what to do. So sometimes it's as simple as listening to the market. Sometimes it's as simple as speaking internally.

And sometimes it's a product feature that you thought was just a feature, but that's the only feature that your customer actually wants. All of the other things that you thought they wanted, you get feedback that's not why they bought the product. There's just different ways that the data can come to you, and then you just have to have that open discussion and collaborative discussion of, "Okay, based on that, what do we do?"

John: Yeah. It seems like you have to have a real culture of psychological safety though, to bring up these topics because I can't imagine the conversation at Conceptus. Like we're going to do the opposite of what we set out to do and I'm sure there were some people who may not have been comfortable with that.

Jolly: Yeah. Like I said, it was a hundred and eighty degree pivot that's hard because most people joined you because they believed in your exact mission that you were on, and you even started it because of that mission. And now I'm going to go this way.

John: It takes courage.

Jolly: Yes, hats off. That's why only 10 to 20% of startups actually make it. I hope we're all in that category that make it.

John: Me too.