When Customers Make You Smarter

We talk a lot about Customer Development, but there’s nothing like seeing it in action to understand its power. Here’s what happened when an extraordinary Digital Health team gained several critical insights about their business model. The first was reducing what they thought was a five-sided market to a simpler two-sided one.

But the big payoff came when their discussions with medical device customers revealed an entirely new way to think about pricing —potentially tripling their revenue.

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We’re into week 9 of teaching a Lean LaunchPad class for Life Sciences and Health Care (therapeutics, diagnostics, devices and digital health) at UCSF teaching with a team of veteran venture capitalists. The class has talked to ~2,200 customers to date. (Our final – not to be missed – Lessons Learned presentations are coming up December 10th.)

Among the 28 startups in the Digital Health cohort is Tidepool. They began the class believing they were selling an open data and software platform for people with Type 1 Diabetes into a multi-sided market comprised of patients, providers, device makers, app builders and researchers.

tidepool website

The Tidepool team members are:

  • Aaron Neinstein MD  Assistant Professor of Clinical Medicine, Endocrinology and Assistant Director of Informatics at UCSF. He’s an expert in the intersection between technological innovations and system improvement in healthcare. His goal is to make health information easier to access and understand.
  • Howard Look, CEO of Tidepool, was VP of Software and User Experience at TiVo. He was also VP of Software at Pixar, developing Pixar’s film-making system, and at Amazon where he ran a cloud services project. At Linden Lab, delivered the open-sourced Second Life Viewer 2.0 project. His teenage daughter has Type 1 diabetes.
  • Brandon Arbiter was a VP at FreshDirect where he built the company’s data management and analytics practices. He was diagnosed at age 27 with Type 1 Diabetes. He developed a new generation diabetes app, “nutshell,” that gives patients the information they need to make the right decisions about their dosing strategies.
  • Kent Quirk was director of engineering at Playdom and director of engineering at Linden Labs.

A Five-sided Market
In Week 1 the Tidepool team diagramed its customer segment relationships like this:

Tidepool ecosystem

Using the business model canvas they started with their value proposition hypotheses, articulating the products and services they offered for each of the five customer segments. Then they summarized what they thought would be the gain creators and pain relievers for each of these segments.

Tide pool value prop week 1

Next, they then did the same for the Customer Segment portion of the canvas. They listed the Customer Jobs to be done and the Pains and Gains they believed their Value Proposition would solve for each of their five customer segments.

Tide pool cust week 1

It’s Much Simpler
Having a multisided market with five segments is a pretty complicated business model. In some industries such as medical devices its just a fact of life. But after talking to dozens of customers by week 3, Tidepool discovered that in fact they had a much simpler business model – it was a two-sided market.

tidepool simplification

They discovered that the only thing that mattered in the first year or two of their business was building the patient-device maker relationship. Everything else was secondary. This dramatically simplified their value proposition and customer segment canvas.

So they came up with a New Week 3 Value Proposition Canvas:

Tide pool value prop week 3

And that simplified their New Week 3 Customer Segment Canvas

Tide pool cust week 3

Cost-based Pricing versus Value-based Pricing
While simplifying their customer segments was a pretty big payoff for 3 weeks into the class, the best was yet to come.

As part of the revenue streams portion of the business model canvas, each team has to diagram the payment flows.

Tide pool market pricing

The Tidepool team originally believed they were going charge their device partners “market prices” for access to their platform. They estimated their Average Revenue per User (ARPU) would be about $36 per year.

Tide pool market pricing ARPU

But by week 6 they had spoken to over 70 patients and device makers. And what they found raised their average revenue per user from $36 to $90.

When talking to device makers they learned how the device makers get, keep and grow their customers.  And they discovered that:

  • device makers were spending $500-$800 in Customer Acquisition Cost (CAC) to acquire a customer
  • device makers own customers would stay their customers for 10 years (i.e. the Customer Life Time (CLT))
  • and the Life Time Value (LTV) of one customer over those 10 years to a device maker is $10,000

Tide pool market pricing device cac

These customer conversations led the Tidepool team to further refine their understanding of the device makers’ economics.  They found out that the device makers sales and marketing teams were both spending money to acquire customers.  ($500 per sales rep per device + $800 marketing discounts offered to competitors’ customers.)

Tide pool device economics

Once they understood their device customers’ economics, they realized they could help these device companies reduce their marketing spend by moving some of those dollars to Tidepool. And they realized that the use of the Tidepool software could reduce the device companies’ customer churn rate by at least 1%.

This meant that Tidepool could price their product based on the $1,800 they were going to save their medical device customers.  Read the previous sentence again. This is a really big idea.

Tide pool value pricing big idea

The Tidepool team went from cost-based pricing to value-based pricing. Raising their average revenue per user from $36 to $90.

Tide pool value pricing $90 ARPU

There is no possible way that any team, regardless of how smart they are could figure this out from inside their building.

If you want to understand how Customer Discovery works and what it can do in the hands of a smart team, watch the video below. The team ruthlessly dissects their learning and builds value-pricing from what they learned.

This short video is a classic in Customer Discovery.

If you can’t see the video click here.

Lessons Learned

  • Most startups begin by pricing their product based on cost or competition
  • Smart startups price their product based on value to the customer
  • You can’t guess how your product is valued by customers
  • Customer Development allows you to discover the economics needed for value pricing your product

Listen to the podcast here [audio http://traffic.libsyn.com/albedrio/steveblank_clearshore_131202.mp3]

Download the podcast here

Lean LaunchPad for Life Sciences – Revenue Streams

We’re teaching a Lean LaunchPad class for Life Sciences and Health Care (therapeutics, diagnostics, devices and digital health) at UCSF with a team of veteran venture capitalists. The class has talked to 2,056 customers to date.

This post is an update of what we learned about life science revenue models.

Life Science/Health Care revenue streams differ by Category
For commercialization, the business model (Customers, Channel, Revenue Model, etc.) for therapeutics, diagnostics, devices, bioinformatics and digital health have very little in common.

This weeks topic was revenue streams – how much cash the company can generate from each customer segment. Revenue streams have two parts: the revenue strategy and the pricing tactics.

Figuring out revenue strategy starts by gaining a deep understanding of the target customer(s). Setting a revenue strategy starts with understanding the basics about the customer segments:

  • who’s the user, the recommender, buyer, and payer
  • How the target customer currently purchases goods and services and how much they currently pay for equivalent products
  • Their willingness to pay for value versus lowest cost?
  • How much budget they have for your type of product?

Revenue strategy asks questions like, “Should we offer cost-based or value-based pricing.  How about demand-based pricing? Freemium? Do we price based on hardware sales or do we offer hardware plus consumables (parts that need to be disposed or replaced regularly)? Do we sell a single software package or a subscription?  These strategy hypotheses are tested against the target customer segment(s).

Once you’ve established a revenue strategy the pricing tactics follow. Pricing is simply “how much can I charge for the product using the selected revenue strategy?”  Pricing may be as simple as setting a dollar value for hardware or software, or as complicated as setting a high price and skimming the market or setting a low price as a loss leader.

You can get a feel for how each of the cohorts address the Revenue Streams by looking at the Revenue lectures below – covering the therapeutics, diagnostics, devices and digital health cohorts.

At the end of the lectures you can see a “compare and contrast” video and a summary of the differences in distribution channels.

Diagnostics

Week 5 Todd Morrill Instructor 

If you can’t see the presentation above click here

Digital Health

Week 5 Abhas Gupta Instructor 

If you can’t see the presentation above click here

Devices

Week 5 Allan May Instructor 

If you can’t see the presentation above click here

Therapeutics

Week 5 Karl Handelsman Instructor 

If you can’t see the presentation above click here

Life Science and Health Care Differences in Revenue Streams
”
This weeks lecture and panel was on Revenue; how much cash the company can generate from each customer segment – and the strategy and tactics to do so. Therapeutics, diagnostics, devices and digital health use different Revenue Strategies and Pricing Tactics, in the video and the summary that follows the instructors compare and contrast how they differ.

If you can’t see the video above click here

Therapeutics (Starting at 0:30)

  • Therapeutics revenue is from drug companies not end users
  • 18 months to first revenue from a deal
  • Predicated on delivering quality data to a company
  • Deal can be front-end or back-end loaded
  • Quality of the data has to be extremely high for a deal

Diagnostics (Starting at 4:10)

  • Diagnostic revenue is from end users: a hospital or clinical lab
  • You need to figure out value of your product but…
  • Pricing is capped by your reimbursement (CPT) code limits
  • Reimbursement strategy is paramount, design to good codes avoid bad ones
  • Find a reimbursement code consultant
  • Don’t do cost-based pricing… go for value-based pricing

Medical Devices (Starting at 8:23)

  • There really is no such thing as a perfect First Generation Medical Device
    • So Medical Device companies often start with a Volkswagen product and then build to the Ferrari product
  • Revenue models are typically direct product sales
  • Don’t do cost-based pricing… go for value-based pricing, especially where your device lowers the treatment costs of the patient
  • In most cases, pricing is capped by your reimbursement (CPT) code limits
    • Or pricing can be capped by what competitors offer, unless you can demonstrate superior cost savings
    • In a new market there is no reimbursement code but if you show high cost-savings you can get a high reimbursement rate
  • A risk in device hardware is getting trapped in low-volume manufacturing with low margins and run out of cash

Digital Health (Starting at 10:35)

  • Digital Health revenue models are often subscription models to a company per month across a large number of users
    • Intermediation fees – where you broker a transaction – are another source of revenue (i.e. HealthTap)
    • Advertising is another digital health revenue model, but requires at least 10 million users to have a meaningful model, but can be lower if you have higher value uses like specialist physicians because  you can charge dollars not cents
  • Don’t do cost-based pricing… go for value-based pricing
    • Value-based pricing is based on the needs you’ve learned from the customer segment and the strength of your product/market fit
      • the sum of customer needs + product/market fit = the pricing you can achieve

Lessons Learned

  • Each of these Life Science domains has a unique revenue strategy and pricing tactic
  • In therapeutics revenue comes in lump milestone payments from drug companies based on quality data
  • Diagnostics revenue comes value pricing to hospital or clinical lab
    • capped by reimbursement (CPT) code limits
  • Device pricing starts by offering an initial value-priced base product and then following up with a fully featured product
    • capped by reimbursement (CPT) code limits
  • Digital health products use subscription value pricing. Alternatively may use advertising revenue model

Listen to the podcast here [audio http://traffic.libsyn.com/albedrio/steveblank_clearshore_131118.mp3]

Download the podcast here

Well They “Should” be Our Customers

When scientists and engineers who’ve been working in the lab for years try to commercialize their technology they often get trapped by their own beliefs  – including who the customers are, what features are important, pricing etc.

 

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One the key tenets of the Lean LaunchPad class is that every week each team gets out of the building and talks to 10+ customers/partners to validate a new part of their business model.  Back in class they present their findings to their peers and teaching team in a 10 minute Lessons Learned presentation. One of the benefits of the class is that the teams get immediate unvarnished feedback on their strategy.

For researchers and clinicians who’ve been working on a project in the lab for years, getting out of the building and talking to customers at times creates cognitive dissonance.  While they’ve been in the lab they had a target customer in mind. However when they leave the building and start talking to these  supposed customers there’s almost always a surprise when the customer is not interested in the product.

Often when they consistently hear that their expected customers aren’t interested the first reaction is “the customers just don’t get it yet.”  Rather than testing a new customer segment they keep on calling on the same group – somehow thinking that “we just need to explain it better.”

Some times it takes a nudge from the teaching team to suggest that perhaps looking at another customer segment might be in order.

They Should be Our Customers
The Mira Medicine Team is trying to accelerate the path to the right treatment for each patient in complex Central Nervous System diseases. They spent years building their first tool MS Bioscreen, which was developed for the physicians at the UCSF Dept of Neurology. So they naturally believed that their first customers would be neurologists.

This was a very smart team who ran into the same problem almost every smart researcher attempting to commercialize science faces.  Here’s what happened.

If you can’t see the video click here.

Listen for:

0:35 “Our primary customer we built this app for was neurologists…

1:00 “(but neurologists have told us) your prototype is interesting… and probably some features are nice to haves…

2:26 “What’s special about neurology?  Doesn’t cardiology and oncology have problems like this?

3:00 “Is neurology a key component of what you’re trying to do?

3:15 “I’ve worked on this for two years…”

3:24 “You’ve already done too much prototyping work. You’re hung up on the prototype.”

3:29 “You have a square peg you’er trying to jam in a round hole…”

3:43 “Don’t be afraid to think laterally”

Postscript: 70 customers later they no longer talking to neurologists.

Lessons Learned

  • Don’t get trapped by your own beliefs
  • When reality outside the building doesn’t match your hypotheses – test alternate hypotheses
  • Most of the time your vision is just a hallucination

Listen to the podcast here [audio http://traffic.libsyn.com/albedrio/steveblank_clearshore_131113.mp3]

Download the podcast here

Lean LaunchPad for Life Sciences – Distribution Channels

We’re teaching a Lean LaunchPad class for Life Sciences and Health Care (therapeutics, diagnostics, devices and digital health) at UCSF with a team of veteran venture capitalists. The class has talked to 1,780 customers to date.

This post is an update of what we learned about life science distribution channels.

Life Science/Health Care distribution channels differ by Category
It turns out that for commercialization, the business model (Customers, Channel, Revenue Model, etc.) for therapeutics, diagnostics, devices, bioinformatics and digital health have very little in common.

This weeks topic was distribution channels; how your product gets from your company to your potential customer segments. You can get a feel for how each of the cohorts address the channel by looking at the distribution channel lectures below – covering the therapeutics, diagnostics, devices and digital health cohorts.

At the end of the lectures you can see a “compare and contrast” video and a summary of the differences in distribution channels.

Diagnostics

Week 3 Todd Morrill Instructor 

If you can’t see the presentation above click here

Digital Health

Week 3 Abhas Gupta Instructor 

If you can’t see the presentation above click here

Devices

Week 3 Allan May Instructor 

If you can’t see the presentation above click here

Therapeutics

Week 3 Karl Handelsman Instructor 

If you can’t see the presentation above click here

Life Science and Health Care Differences in Distribution Channels
This weeks lecture and panel was on distribution channels; how your product gets from your company to your potential customer segments. Therapeutics, diagnostics, devices and digital health use different different channels, in the video and the summary that follows the instructors compare and contrast how they differ.

If you can’t see the video above click here

Medical Devices (Starting at 0:50)

  • Medical Device Distribution Channels in general are a sales team hired directly by the company.
    • A sales team typically includes a sales person and clinical applications specialists.
    •  The specialists help train and educate physician users. They assist with the sale and work with marketing to create demand.
  • Some device industries are controlled by distributors (indirect sales.)
    • Distributors tend to resell commodity products from multiple suppliers.
  • Channel Cost =  $350-400,000 per sales team. On average there’s 1 clinical applications specialist to 2 salespeople.  A lean rollout for a startup would be 4-5 sales people plus 2-3 clinical applications specialists at a cost of ~$2.5 million/year
    • Increasing the number of sales people much past 4-5 for a rollout does not proportionally increase revenue in most cases, because you are on the front end of early adopters and wrestling to overcome and reduce the sales learning curve
    • Travel and Entertainment is a big part of the sales budget since they are all flying weekly to cover accounts
  • 90-180 days for salespeople to become effective
  • Expect little or no revenue for 2- 3 quarters after they start
  • Major reason for failure = hiring sales and marketing staff too quickly
  • Generally an Educational Sale – Hire sales and clinical people first to help early adopters, such as Key Opinion Leaders (KOL’s), master the learning curve with your device so they can write and present papers to influence their peers 

Diagnostics (Starting at 5:16)

  • Diagnostic Channels = Direct sales in the US, with limited Distributor options
    • Many Distributors in Europe and in Asia
    • Sold to hospital laboratories, reference laboratories, or performed in CLIA labs
  • Channel Cost = $350,000+ per supported salesperson
  • Direct to consumer is a (rapidly) growing channel

Digital Health (Starting at 7:25)

  • Digital Health Channels = Direct Sales but you’re selling software to both end users and enterprises
  • Can use existing tech channels and new emerging channels such as Wellness platforms. (Audax Health, Humana Vitality, ShapeUp, Redbrick Health, Limeade)
  • Cloud-based Electronic Medical Records (EMR) are quickly becoming another distribution platform
  • App Stores, and Box are also channels for consumers and enterprise customers, respectively

Therapeutics (Starting at 10:17)

  • Therapeutics Channel = what you’re selling in the early stage is data and Intellectual Property to the pharmaceutical and biotech companies
  • Complicated Sales process – takes 18 months
  • Led by the CEO with a dedicated business development person and your science team
  • You need to define the data they need – this is influenced by how they view their pipeline, and how your technology can fill gaps in their pipeline
  • Pharmaceutical and biotech companies have therapeutics heads, technology scouts and business development people all searching for technology deals to fill their pipeline
  • This is a bound problem – there’s probably 80 people you need to know that make up your channel

Lessons Learned

  • Each of these Life Science domains has a unique distribution channel
  • In Devices innovative products require hiring direct sales people
    • but for commodity device products you may use a distributor
  • Diagnostics requires a direct sales force in the U.S.
    • Distributors in Europe and in Asia
  • In Digital Health direct sales is a possible channel, as are traditional software channels (App Stores, Box, etc.)
    • other DHealth channels such as Wellness Platforms, and cloud-based EMR’s are also emerging
  • In therapeutics it’s a direct sale of data and Intellectual property
    • led by the CEO with a dedicated business development person and your science team

Listen to the podcast here [audio http://traffic.libsyn.com/albedrio/steveblank_clearshore_131111.mp3]

Download the podcast here

Lean LaunchPad for Life Sciences – Value Proposition and Customers

We’re deep into teaching a Lean LaunchPad class for Life Sciences and Health Care (therapeutics, diagnostics, devices and digital health) at UCSF with a team of veteran venture capitalists. (The class has talked to 1,440 customers to date.)

One of the objectives of the class was to become a Life Science Center of Excellence for the National Science Foundation Innovation Corps. This meant capturing domain specific commercialization expertise for therapeutics, diagnostics, devices and digital health so others can teach this.

Part 1 of this post described the issues in the therapeutics drug discovery pipeline. Part 2 covered medical devices and digital health. Part 3 described what we’re going to do about it.  Part 4 gave a snapshot of what one our teams found the first week outside the building.

This is an update of our progress.

It Takes A Village
We’re teaching 110 students in 28 teams across therapeutics, diagnostics, devices and digital health. Teams are made up of clinicians, researchers, and post docs, (some of the team members include the Chief of  UCSF General Surgery, the inventor of Fetal Surgery, etc.)

Each of the four cohorts is taught by an experienced life science venture capitalist. Alan May for devices, Karl Handelsman for therapeutics Abhas Gupta for digital health and Todd Morrill for diagnostics.

Jerry Engel and Jim Hornthal, both who taught the National Science Foundation I-Corps classes, are the senior instructors. The UCSF Office of Innovation and Technology (Erik Lium and Stephanie Marrus) is the reason the program exists.

Each of the teams is assigned a mentor to match their domainv(Head of device R&D of Phillips, Genetech, Crescendo, CTO of UCSF, venture capitalists from Sofinnova, Burrill, Lightstone, M34, etc.)

Class Organization – Lots of Moving Parts
Our class meets weekly. We first meet as one group and then we break out the therapeutics, diagnostics, devices and digital health into their own cohorts. The teams present what they learned talking to 10-15 customer/week, and get comments, suggestions and critiques from their teaching team.  The instructor then presents  a cohort specific lecture explaining how the business model for their area (therapeutics, diagnostics, devices and digital health) builds on and/or differs from the canonical business model in the online Udacity lectures (which the students had to watch as homework.)

We get back together as one group and the instructors share what they learned as they compare and contrast the differences between therapeutics, diagnostics, devices and digital health.  We’ve recorded these panels for each part of the business model canvas.

The framework of the class looks like this:

Lean LaunchPad for Life Sciences

Life Science/Health Care is not a single Category
One of the reasons I teach is because of how much I learn. One of early surprises of this class for me is finding out that the broad category of “Life Sciences” fails to provide the important nuances of each category to entrepreneurs, investors, educators, policy makers, etc. It turns out that for commercialization, the business model (Customers, Channel, Revenue Model, etc.) for therapeutics, diagnostics, devices, bioinformatics and digital health have very little in common.

You can get a feel for how different by looking at the first two weeks of lectures – covering value proposition and customer segment – from each of the therapeutics, diagnostics, devices and digital health cohorts.

Then at the end of the lectures you can see a “compare and contrast” video and a summary of the differences.

Diagnostics

Week 1 Todd Morrill Instructor 

If you can’t see the presentation above click here

Week 2 Todd Morrill Instructor

If you can’t see the presentation above click here

Digital Health

Week 1 Abhas Gupta Instructor 

If you can’t see the presentation above click here

Week 2 Abhas Gupta Instructor

If you can’t see the presentation above click here

Devices

Week 1 Allan May Instructor 

If you can’t see the presentation above click here

Week 2 Allan May Instructor

If you can’t see the presentation above click here

Therapeutics

Week 1 Karl Handelsman Instructor 

If you can’t see the presentation above click here

Week 2 Karl Handelsman Instructor

If you can’t see the presentation above click here

Life Science and Health Care Differences

Once we realized that the four cohorts of therapeutics, diagnostics, devices and digital health were so different we decided to have the instructors compare and contrast how they’re different for each part of the business model. We’ll be posting these “compare and contrast” videos for every week of the class.

If you can’t see the video above click here

Therapeutics (Starting at 0:30)

  • Therapeutics customer = pharma and biotech companies
  • Therapeutics Pain & gain = be better than what these companies have in their own drug development pipeline
  • Therapeutics Validation =  18 months to a first deal with a potential customer – well before FDA trials, and even before preclinical stage

Digital Health (Starting at 2:40)

  • Digital Health Customer = typically consumer end users
  • Digital Health Pain & gain = product/market fit needs to be a need, and the value proposition must address it.  “Nice to have’s” do not equal a customer need.
  • Digital Health Validation = large scale adoption

Medical Devices (Starting at 6:00)

  • Medical Device customers = short term: physicians in private practice and hospital, long term: medical device companies
  • Medical Device Customer Goal – figure out the Minimal Viable Product.  No such thing as a perfect first generation product that targets a specific physician/customer segment.
  • Medical Device Validation= 95% of device startups are acquired by a medical device company, 5% build a large standalone company

Diagnostics (Starting at 10:45)

  • Diagnostic Customers = short term In vitro diagnostics are sold to a hospital laboratory or standalone lab, long-term you’ll be bought by Abbott, Roche, etc.

Lessons Learned

  • Each of these Life Science domains has a unique business model
  • Commercialization of therapeutics, diagnostics, devices and digital health all require the Principal Investigators / founders outside their building talking to customers, partners, regulators
  • Only the Principal Investigators / founders have the authority and insight to pivot when their hypotheses are incorrect
  • The Lean Startup process and the Lean LaunchPad class can save years in commercialization in these domains
  • This can be taught

Listen to the podcast here

Download the podcast here

This Will Save Us Years – Lean LaunchPad for Life Science

We’re deep into week 2 of teaching a Lean LaunchPad class for Life Sciences and Health Care (therapeutics, diagnostics, devices and digital health) this October at UCSF with a team of veteran venture capitalists.

Part 1 of this post described the issues in the drug discovery. Part 2 covered medical devices and digital health. Part 3  described what we’re going to do about it.

This is post is a brief snapshot of our progress.

Vitruvian is one of the 28 teams in the class. The team members are:

  • Dr. Hobart Harris  Chief of  General Surgery, Vice-Chair of the Department of Surgery, and a Professor of Surgery at  UCSF. Dr. Harris is also a Principal Investigator in the UCSF Surgical Research Laboratory at San Francisco General Hospital.
  • Dr. David Young,  Professor of Plastic Surgery at UCSF. His area of expertise includes wound healing, microsurgery, and reconstruction after burns and trauma. His research interests include the molecular mechanisms of wound healing and the epidemiology and treatment of soft tissue infections.
  • Sarah Seegal is at One Medical Sarah is interested in increasing the quality and accessibility of healthcare services. Sarah worked with Breakthrough.com to connect individuals with professional therapists for online sessions.
  • Cindy Chang is a Enzymologist investigating novel enzymes involved in biofuel and chemical synthesis in microbes at LS9

Vitruvian’s first product, MyoSeal, promotes wound repair via biocompatible microparticles plus a fibrin tissue sealant that has been shown to prevent incisional hernias through enhanced wound healing.  The team believed that surgeons would embrace the product and pay thousands to use it.  In week 2 of the class 14 of their potential customers (surgeons) told the team otherwise.

Watch this 90 second clip and find out how the Lean LaunchPad class saved them years.

(If you can’t see the clip above click here.)

Lessons Learned

  • Get out of the building

Listen to the post here
Download the post here

Reinventing Life Science Startups – Evidence-based Entrepreneurship

What if we could increase productivity and stave the capital flight by helping Life Sciences startups build their companies more efficiently?

We’re going to test this hypothesis by teaching a Lean LaunchPad class for Life Sciences and Health Care (therapeutics, diagnostics, devices and digital health) this October at UCSF with a team of veteran venture capitalists.

Part 1 of this post described the issues in the drug discovery. Part 2 covered medical devices and digital health. This post describes what we’re going to do about it.  And why you ought to take this class.

——

When I wrote Four Steps to the Epiphany and the Startup Owners Manual, I believed that Life Sciences startups didn’t need Customer Discovery. Heck how hard could it be?  You invent a cure for cancer and then figure out where to put the bags of money. (In fact, for oncology, with a successful clinical trial, this is the case.)

Pivots in life sciences companies

But I’ve learned that’s not how it really works. For the last two and a half years, we’ve taught hundreds of teams how to commercialize their science with a version of the Lean LaunchPad class called the National Science Foundation Innovation Corps.  Quite a few of the teams were building biotech, devices or digital health products.  What we found is that during the class almost all of them pivoted – making substantive changes to one or more of their business model canvas components.

In the real world a big pivot in life sciences far down the road of development is a very bad sign due to huge sunk costs.  But pivoting early, before you raise and spend millions or tens of millions means potential disaster avoided.

Some of these pivots included changing their product/service once the team had a better of understanding of customer needs or changing their position in the value chain (became an OEM supplier to hospital suppliers rather than selling to doctors directly.) Other pivots involved moving from a platform technology to become a product supplier, moving from a therapeutic drug to a diagnostic or moving from a device that required a PMA to one that required a 510(k).

Some of these teams made even more radical changes.  For example when one team found the right customer, they changed the core technology (the basis of their original idea!) used to serve those customers. Another team reordered their device’s feature set based on customer needs.

These findings convinced me that the class could transform how we thought about building life science startups.  But there was one more piece of data that blew me away.

Control versus Experiment – 18% versus 60%
For the last two and a half years, the teams that were part of the National Science Foundation Innovation Corps were those who wanted to learn how to commercialize their science, applied to join the program, fought to get in and went through a grueling three month program.  Other scientists attempting to commercialize their science were free to pursue their startups without having to take the class.

Both of these groups, those who took the Innovation Corps class and those who didn’t, applied for government peer-reviewed funding through the SBIR program. The teams that skipped the class and pursued traditional methods of starting a company had an 18% success rate in receiving SBIR Phase I funding.

The teams that took the Lean Launchpad class  – get ready for this – had a 60% success rate. And yes, while funding does not equal a successful company, it does mean these teams knew something about building a business the other teams did not.

The 3-person teams consisted of Principal Investigators (PI’s), mostly tenured professors (average age of 45,) whose NSF research the project was based on. The PI’s in turn selected one of their graduate students (average age of 30,) as the entrepreneurial lead. The PI and Entrepreneurial Lead were supported by a mentor (average age of 50,) with industry/startup experience.

This was most definitely not the hoodie and flip-flop crowd.

Obviously there’s lots of bias built into the data – those who volunteered might be the better teams, the peer reviewers might be selecting for what we taught, funding is no metric for successful science let alone successful companies, etc.  – but the difference in funding success is over 300%.

The funding criteria for these new ventures wasn’t solely whether they had a innovative technology. It was whether the teams understood how to take that idea/invention/patent and transform it into a company. It was whether after meeting with partners and regulators, they had a plan to deal with the intensifying regulatory environment. It was whether after talking to manufacturing partners and clinicians, they understood how they were going to reduce technology risk. And It was after they talked to patients, providers and payers whether they understood the customer segments to reduce market risk by having found product/market fit.

Scientists and researchers have spent their careers testing hypotheses inside their labs. This class teaches them how to test the critical hypotheses that turn their idea into a business as they deal with the real world of regulation, customers and funding.

So after the team at UCSF said they’d like to prototype a class for Life Sciences, I agreed.

Here’s what we’re going to offer.

The Lean LaunchPad Life Sciences and Health Care class

The goal of the Lean LaunchPad Life Sciences class at UCSF is to teach researchers how to move their technology from an academic lab into the commercial world.UCSF Logo

We’re going to help teams:

  • assess regulatory risk before they design and build
  • gather data essential to customer purchases before doing the science
  • define clinical utility now, before spending millions of dollars
  • identify financing vehicles before you need them

We’ve segmented the class into four cohorts: therapeutics, diagnostics, devices and digital health.  And we recruited a team of world class Venture Capitalists and entrepreneurs to teach and mentor the class including Alan May, Karl Handelsman, Abhas Gupta, and Todd Morrill.

The course is free to UCSF, Berkeley, and Stanford students; $100 for pre-revenue startups; and $300 for industry. – See more here

The syllabus is here.

Class starts Oct 1st and runs through Dec 10th.

Download the all three parts of the Life Science series here.

Listen to the podcast here [audio http://traffic.libsyn.com/albedrio/steveblank_clearshore_130821.mp3]

Download the podcast here

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