Why Selling a Medical Treatment is Hard

Note: this is a series on making a digital health startup.  The first post is here.

Last week we talked about the difficulties of selling B2B in general.  This week we’ll talk in a little more detail about selling treatments to insurers.  Sometimes you’re selling a piece of IT software to a hospital.  It’s technically digital health, because it’s software and it’s related to healthcare, but ultimately that’s is a traditional sales process, similar to that of a big oil company or consumer goods company.

But let’s say you have a new digital therapeutic or a new device, and you want insurance coverage.  What then?  I ended last week’s post with a quote from an insurer, so I’ll start there.

Having spent the last 15 years of my life as an entrepreneur, I know it’s a difficult and time-consuming process.  Now, as an insurer, I’ll demand lots of data and good RCT trials results, and I’ll make you squirm you in looking for data. You’ll have to prove the benefit of your product in a variety of ways, and it’s going to be an expensive and long road ahead. If it turns out really great, there can be some rewards…but trying to get there will take years.

On the one hand, I can see how people might read this and become angry at the insurers.  Insurance companies hate innovation!  Insurance companies focus more on money than on the health of their members (the industry term for “customers”)!

But I think that’s not entirely right.  Insurers are petitioned a dozen times a day to cover a new treatment or device; how should it decide?

We’ve put insurance companies in a really difficult place, and by way of illustration I’d like to use the example of England’s healthcare.  In England, where the argument is a little simpler, health coverage is nationalized.  Citizens pay fixed taxes to the government, and the government’s National Health Service (NHS) provides basic health care to all its citizens (“universal health care”).  More specifically, citizens pay ~£113 billion in taxes each year, so ~£113 billion is the budget for all the healthcare needs of the English population.  With this money, the government is responsible for every malady that a citizen might encounter, from the flu to ebola, birthing to hospice.  And every year, roughly all of the money is allocated out; there is minimal cushion for extra expenses.

This means a few things:

  • First, there isn’t just money waiting around to be spent.  If the NHS wants to spend £1 million on a new technology, it must, in general, decrease spending elsewhere by £1 million in order to keep a balanced budget.
  • Second, the relative benefit of each technology must therefore be compared against its cost.  Note: all facts below made up for illustrative purposes.  Let’s say there’s a new medical device that can save the lives of the 100 people in England with a rare form of deadly pancreatic cancer but costs £100 million per year…should the NHS cover it?  From one perspective, sure!  If you can save even one person, you should do it!  But from another perspective, that £100 million needs to be compared against what it can do elsewhere in the health world, as the NHS’s budget is more-or-less fixed.  £100 million might also mean 200,000 infant vaccinations or 100,000 HIV medicines — should the NHS cancel these programs in order to save the 100 cancer sufferers? And now it turns out the medication saves 80% of cancer patients but puts the other 20% in a coma.  What now?
  • Third, the way the NHS handles this issue of cost vs. benefit is by using, among other things, a calculation called a Quality Adjusted Life Year (QALY), essentially a calculation of the number of years of high-quality life a treatment can provide.  It then sets a specific value to a high-quality year and compares that to its cost.  Let’s say the cancer drug provides one extra year of fully-healthy life, and it costs £1 million per year.  And let’s say the UK has set the value of a QALY at £50,000.  According to this calculation, the drug would be too expensive to justify using it.  If the drug makers could lower their cost to £49,000, then it might be accepted.  But if not, then it wouldn’t be accepted.

This might seem like a cruel thing — let’s place a “value” on a human life, and let’s let some die because the cost to treat them is too high — but at the same time Britain has managed to provide a safety net of basic coverage for all its citizens, without going bankrupt.  And folks who wish to seek the most advanced (and risky and expensive) treatments who have the money to pay for them are free to go outside the government system and purchase these treatments on their own.

In the United States the system is way more complicated.  When folks are old or poor their health coverage resembles the example above, because two government agencies, Medicare and Medicaid, respectively, provide universal healthcare to these people, but for the rest of the population, they choose their own insurance plan.  Each plan provides different services and accepts different treatments.

So how do these insurance companies decide which treatments to accept and which to deny?  In the United States the QALY system is considered unpalatable / unethical (see: death panels), so it’s illegal, but as this article discusses, it’s also sometimes used (maybe — but not always — this is complicated!).  But again, with insurers there’s a fixed amount of money coming in (via monthly premiums) and a widely variable amount of money being spent (let’s say there’s an ebola outbreak and everyone’s getting quarantined — who pays for that?!), so their natural impetus is to deny coverage as much as possible, in an attempt to remain solvent.

So how, then, does an insurer agree to cover a treatment?

Sometimes the insurers are forced to cover a new treatment by Medicare; if Medicare agrees to cover a treatment, then insurers will generally follow along and agree to cover.  But sometimes comes from other sources.  For example, if a startup directly petitions an insurer sometimes the insurer will agree to cover a treatment.  But again, the insurer feels pressure to deny coverage as much as possible, so the request of a pesky startup probably won’t matter much, unless…

Sometimes an insurer will agree to cover a treatment if a bunch of patients petition for it, or if there’s a big media swell about the benefits of a particular treatment.  And sometimes if a doctor asks for approval for a specific treatment, the insurer will sometimes agree to cover it.  Insurers are only valuable if desirable doctors agree to accept their insurance.  And if a doctor leaves one plan for another, maybe the doctor’s patients will leave the plan, and then the insurer will lose lots of money.  So the insurers spend lots of time kow-towing to the most valuable doctors, and sometimes if these doctors demand coverage for a treatment they’ll agree to cover it.  But until recently the doctor would never know the price of a treatment.  In fact the cost of a treatment would be considered taboo for the doctor; from the doctor’s perspective, if s/he wanted a treatment, s/he didn’t care about the price, for the doctor only cared about providing better care without focus on price.

This then created its own issues, as medical salespeople had one decision maker (the doctor) and another payer (the insurer), similar to toy companies that advertise to children knowing that if the child asks for a special Sesame Street doll the parent will buy it.  And of course medical salespeople would want to make the issue of price taboo, preying on this awesome integrity of doctors, and medical startups would be able to command exorbitant prices for products with marginal incremental benefit.

We expect doctors to make fully rational decisions — they’re doctors after all, with the best interest of their patients in mind — but in one hospital I visited the medical salespeople hang out inside the operating room during surgery, and when a doctor is trying to decide which pacemaker to use and the Medtronic salesperson is standing right there, you better bet the doctor will feel peer pressure to use the Medtronic pacemaker!  (In fact there’s proof that these sales reps do influence doctor decision-making.)  And then, when the doctor is bribed (or asks to be bribed) as a quid pro quo for promoting a particular treatment…

Alright fine! Fine, you say – forget about these insurance companies, and forget about the doctors. Forget about this complicated system. Instead, I’ll go to the companies that insure their own employees. Instead of a big insurer, I’ll sell to these “self-insured employers.” These companies are smaller than an insurer, and their interests are aligned with their employees, and so if I can just convince a rational CEO that my product will improve health and lower costs, then it’s a slam dunk.

Wrong again. Many of the decisions related to healthcare at self-insured employers are handled by Human Resource departments, and these departments aren’t necessarily tasked with lowering costs. Maybe their only mandate is to keep employees happy. And now this new technology comes along, and it’ll be a hassle to integrate…well maybe it’s easier just not to go forward.

Direct quote from the CEO of a startup that’s sold to self-insured employers:

HR is where good ideas go to die. HR executives control $1.5 trillion healthcare spending, but they’re not passionate about health…I go talk to CEOs and they want to buy my product, and then the HR people put it in the graveyard.

In any case, the lesson for a startup is it’s probably less useful for you to go to an insurer and ask for coverage than it is for you to get either patients or doctors to do the asking on your behalf.  You’re just a salesperson, a vendor — a dreaded cost on their income statement — but these patients and doctors represent potential lost revenue, and if you can help an insurer keep a patient happy or prevent a doctor from leaving, or even get new patients, then you’re way more likely to get coverage.

The other lesson: this is very complicated!  And it’s really hard for a startup to get coverage for his/her product.  If you’re looking for someone to blame, well…one time a medical resident exclaimed to me, “All the problems in healthcare are from insurers!”  That’s not entirely true, although it’s not not the insurer’s fault.  It’s partially the insurer’s fault.  And it’s partially the hospital’s fault.  And it’s partially the doctor’s fault. And it’s partially the medical technology company’s fault.

Next week we’ll talk about situations where the deals happen quickly and smoothly, so you can start to design your sales cycles around them.

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Why B2B is Hard

Note: this is a series on making a digital health startup.  The first post is here.

Last week we talked about failure rates within startups.  This week we’ll shift to the business-to-business side of digital health, and we’ll talk about the difficulty of B2B.

Many startup CEOs are tantalized by selling to a large business (“B2B” or “enterprise”), such as a hospital or insurance company, for a few reasons.  First, with a very small number of sales, one can immediately reach massive scale.  If you get a contract with United Health, for example, you have the potential to reach millions of individuals across the US practically overnight.  Second, B2B sales sometimes feel more rational and economics-based than having to deal with the whims of the fickle consumer.  If you show your product works, the theory goes, an enterprise will buy…whereas the consumer cares about annoying things like branding and buzz, and how can anyone build a business based on such fragile things?  Third, consumers have not traditionally been direct purchasers of healthcare products for the past 50+ years (because generally folks buy insurance and then the individual products / services they consume are “covered” by the insurer), so there’s a general feeling that consumers are unwilling to pay for healthcare…which means startups must sell B2B if they want to be successful.  “Consumers don’t pay for healthcare” is a common refrain in the medical technology world.

All of these are true, but selling B2B also has its disadvantages.  The first major disadvantage is the length of a sales cycle.  The traditional sales cycle (the time from first contact to closed deal) can be as high as eight to 12 months, and rarely is it fewer than six, unless the company is small or the need is urgent.  Eight to 12 months can be a lifetime in startup years, so it’s difficult to rest one’s future success on a B2B contract.

Second, big companies tend to have numerous layers of management, and many of these layers need to support you in order for you to get a contract.  Further, these layers often disagree with each other, often by design.  For example, an innovation office might want to pilot a new app, but the financial office doesn’t want to pay for the pilot.  The call-center team might want to test a new software that improves efficiency, but the operations team doesn’t want to be responsible for integration.  The surgery team might want to experiment with a robot that does anesthesia automatically, but the anesthesia department doesn’t want to lose jobs, and the medical office is worried about lawsuits from botched robot-anesthesia.  And while most of these departments will need to support you in order for your technology to get approval, almost any can singlehandedly sink you.  See Regina Herzlinger’s brilliant Six Forces framework for more details.

Third, big companies in general don’t want your product.  In healthcare there’s sometimes an assumption that if a product functions, enterprise customers will buy it.  For example, let’s say someone’s invented a new stethoscope that’s internet-enabled and syncs with an iPhone.  From the perspective of the entrepreneur, it’s a slam dunk: the device can plug directly into a hospital’s EMR, and images can be saved and analyzed over time.  Eventually heart analysis can become automated, saving the healthcare system tremendous money and improving care.  It’s a win-win; why wouldn’t every hospital want it?

Well first of all, overworked MDs are probably happy with the stethoscopes they’re used to, and they likely won’t want to switch unless you give them a compelling reason, or force them, or both.  The operations department has to deal with another integration.  The legal division needs to make sure data is routed appropriately and that there aren’t HIPAA violations.  The financial office doesn’t want to pay the extra cost of the internet-enabled stethoscopes.  And the procurement office has an existing relationship with the current stethoscope vendor, and now they have to set up a new billing plan.  As an entrepreneur you think you’re making a product that will make the world better, but in fact you’re just creating a bunch of problems.

People are always trying to sell things to hospitals and insurance companies.  You think you’re the only internet-enabled stethoscope and so competition must be limited, but in fact you’re competing with every other product the procurement office sees that quarter, from new gauze to an improved fMRI machine.   A company has limited capacity for experimentation (because, for example, there are only so many operations people who can handle integrations), so you are fighting with all these other companies for one of these limited resources.

And then the Board of Directors meeting happens.  It turns out the Board is becoming impatient with these new pilots and experiments in the Research & Development division, and they state that they want to see financial results within two quarters.  Now the division chief evaluates every project according to its projected return-on-investment (ROI), and she abruptly cancels every project that can’t demonstrate its ability to general meaningful revenue increases or cost savings within six months.

But you’re an early stage company!  How can you demonstrate ROI within six months if your clinical trial needs 12?  We’re sorry, they say — we just can’t take on that level of risk at this moment.

So selling into large companies is often a scary thing.  

Next week we’ll go into a little more detail about why selling medical treatments is hard.

The Scale of Failure

Note: this is a series on making a digital health startup.  The first post is here.

Last week we talked about using smoke tests to prove the awesomeness of your idea.  This week we’ll talk about the failure/success ratio.

A known fact about success and failure

It’s an oft-repeated theme that failure begets success.  For example: the New York Times Magazine cover story, “What if the Secret to Success Is Failure?”, the (now-controversial“10,000 Hour Rule” that Malcolm Gladwell popularized, and Thomas Edison, full of such things:

“I have not failed. I’ve just found 10,000 ways that won’t work.”

*   *   *

For the past few months I’ve been meeting with a friend, Jenny (name changed), who plans to start a startup.  She quit her job six months ago, took a course on basic coding, and attended relevant conferences.  She did all the right things.  And she remains stubborn that she intends to start a startup.

Nonetheless, to date she hasn’t started a startup.  She explains: “I need to find the thing I’m passionate about.”

*   *   *

To someone like Jenny, the advice buried in these essays is simple: If you want to get something, just start doing it.  You’ll probably mess up a bunch in the beginning, but in the process you’ll learn things and eventually you’ll succeed.

I bet Jenny has read these articles, and at the same time I suspect she hasn’t fully internalized the message.  Implicit in her search for her passion is, I think, an assumption that when she does find her passion, she’ll succeed at making a successful startup.  I think the evidence would suggest she’s wrong about that.  If success comes from failure, then the first startup Jenny tries will likely fail, as will her second, third and potentially 10th.

In fact, from that perspective she might not even want her first startup to be focused on her passion, as that startup will likely fail and then she will have let down the people she’s passionate about serving.

So what to do

Jenny isn’t unique; I speak with people who face similar issues every day.  They want to start a startup, or they want to get a job, but they’re in a sense paralyzed into inaction through a belief that they need to find the perfect job / perfect opportunity / perfect whatever.  I don’t think this situation is inherently a bad thing, per se — it’s awesome that people want to work on things they’re passionate about, and I think the world would be a better place if people spent more time thinking about what they want to do with the limited time they have.

Nonetheless I do have a few pieces of advice, as a life of thinking about one’s passion is way less fun than a life pursuing said passion.

First, this is a quote from Neil DeGrasse Tyson, via The Listserve:

“The problem, often not discovered until late in life, is that when you look for things in life like love, meaning, motivation, it implies they are sitting behind a tree or under a rock. The most successful people in life recognize, that in life they create their own love, they manufacture their own meaning, they generate their own motivation…”

In other words, the idea of finding a passion is a fundamentally flawed thing.  There is no “passion” out there, fully formed, ready for you to take.  Your input is a necessary ingredient in that passion, and so it’d be impossible to find it since it doesn’t exist until you put your energy into it.  Instead, start doing something, and eventually you’ll manufacture your own passion.

Second, I wanted to put some numbers behind the success/failure ratio, so people have a sense of the length of the path they’re embarking upon.  To a person suffering from optimism bias (i.e., almost everyone), the idea of failure leading to success might mean one or two attempts…but then success.  To a job seeker, this means applying to one or two jobs…and then an employment offer.

The reality is your odds are way lower.  Here are a few examples from my life:

  • When I was a senior in college I applied to 30 jobs before I got one employment offer. (1/30 = 3% success rate)
  • Before I started Podimetrics I had seen approximately 200 startup pitches in person, via things like hackathons, demo fairs, and business plan competitions.  (1/200 = 0.5% success rate)
    • Note: hackathons are a great way to see a bunch of startup ideas quickly, as the opening day often has elevator pitches from 20 or 50 entrepreneurs in rapid-fire format.
  • The startup I started before Podimetrics was called MatchLend, and it failed.  I worked on it almost-full-time for over a year, and it went through four complete iterations (like: in one iteration I was going to be a bank, and in another I was going to make a website) before I finally shut it down.  Before MatchLend, I worked on two other failed startup ideas.

Here are a few examples from other startups/artists:

  • In this brilliant speech, artist Darius Kazemi talks about the value of luck in making a successful project.  At 17:00 he puts up a list of 125 projects he has worked on in the past two years.  Each represents between one and 200 hours of work.  He then puts circles around the projects that have gotten “significant press recognition,” and the number of circles is 8.  (8/125 = 6.4% success rate)

Note: Darius’s general point is that success is basically luck:

“…beyond a certain level of effort, there’s basically no correlation between the amount of work you put into something and how successful it is.”

I generally agree with him, and I’ll add a corollary that one can make one’s own luck by increasing the volume of shots-on-goal.  As Thomas Jefferson says,

“I’m a great believer in luck, and I find the harder I work the more I have of it.”

  • I recently attended a speech by Clint Phillips, the founder of 2nd.md where he mentioned completely changing his business model multiple times before coming upon a successful one.
  • Max Levchin, the founder of Paypal, believed his startup would succeed by focusing on the Palm Pilot, a failed precursor the iPhone.  When a new business model appeared (the one that would end up making Paypal a multi-billion-dollar company), Max not only didn’t embrace it but at first he tried to stop it.  He explains,

“So for a while we were fighting, tooth and nail, crazy eBay people: “Go away, we don’t want you.”

In summary, these low success rates suggest you’ll have to work on many things that fail before you have any chance at succeeding.  Perhaps the best thing is simply to focus on volume.  Make a commitment to work on 10 projects that occupy at least one hour in the next month.  Apply to 20 jobs.  Run 15 surveys.  Forget about finding your passion, and instead focus on hitting a pre-determined number of projects…and eventually success (and finding your passion) may come.

Next week we’ll switch to business-to-business (B2B) sales.

Using a Smoke Test

Note: this is a series on making a digital health startup.  The first post is here.

Last week we talked about things that don’t matter in starting a startup.  Today we’ll discuss a quick method to find out whether people really like your idea.

In the past we’ve discussed the benefits of surveys in testing your idea.  A well-designed survey can help you know what people care about, and it can give you a decent insight into the respondent’s desire for your product.  You can ask a bunch of questions relatively efficiently, and you can adjust them over time to really understand your population.

Better than a survey

But now let’s say you’ve run a few surveys, decided what you want to make, know your features, and know the language you want to use.  Now you want to know: will people buy this exact product?

In a previous survey you’ve probably already described the product you want to make, and you’ve probably asked if people would buy it if it were available.  But during a survey people sometimes suspend disbelief, and you can’t always trust their responses.  My friend Tivan, an expert in surveys, says he reduces survey results by a factor of three to estimate a product’s real demand.  If 60% of people say they’ll buy your product, reduce that 60% to 20% for real life, he says.

This is a good, conservative approach, but why not get a real number? For these cases, Tivan suggests running a smoke test.  Smoke tests are actual websites, with actual products, and actual prices, and an actual “Buy Now” button.  The only difference is, at the end of the “Buy Now” option you don’t end up with a product but a pop-up that says, “Thank you so much!  Our product is still being tested, but we’ll let you know when it’s ready to be sold.”

If someone sees a description of your product, a photo, and a price, and she still decides to click “Buy Now,” that’s a pretty good estimation that they actually want your product.  Of course it’s not the same as cash, but it’s a level higher in accuracy than a survey, and it should provide further comfort that you’re making a product people care about.

Building and doing a smoke test

So how do you make a test like this?  Making this test is just like making the survey you built earlier, but now instead of 20 questions, there’s only one question (the “question” is the product’s description, and the “next” button is “buy now.”)  There are many sites that can help, but my recommendation is Typeform (or another web-based form builder, but really Typeform is best).

Typeform allows for beautiful product pages with zero coding.  Make a simple, one question survey, and make sure the button says “buy now.”  Here’s one example I built in 90 seconds:

Screen Shot 2014-10-31 at 8.46.58 AM

If someone visits this site and clicks the “buy now” button, I guess she could be lying, but it makes me feel pretty confident she wants the product.

Steps I took:

  1. Started a new typeform
  2. Clicked on the “Welcome screen” question on the left
  3. Found an image of a toothbrush on Google, saved image to my desktop, uploaded it to the question
  4. Wrote a description of the toothbrush and added a price
  5. Changed the text of the button to “buy now”
  6. Saved this question
  7. Added a “thank you” screen via the “statement” button on the left, added a “thank you” screen via the “thank you” button on the left

That’s it.  Obviously there are ways to make this more complicated:  You can use a better image rather than one from Google (but why?  Surely you can find an image that’s a decent approximation of the thing you’re making, even if it’s an app).  You can add a payment form within Typeform and actually sell the product (but then you need a PRO plan on Typeform and anyway then you have to deal with receiving cash and the potential ethical implications).

Or you can make a fancier description.  But why bother?  You’re just trying to use a quick & dirty approach to determine whether people want your product…and if you can build a website in 90 seconds why do anything else?

Product description

You might think your product has a million features and needs a long description — and how could anyone possibly decide to buy your product without a feature-by-feature breakdown — but I suspect you can find a short description for your product.  “Brevity is the soul of wit,” they say.  Focus on just the most important things, the most important 20 words.

Or if you cannot possibly limit to 20 words, switch the text of your “buy now” button to “learn more”, and then use another question to provide the full description before you ask them to buy.  But again, probably overkill.  If you’re making something awesome, write out the most awesome feature in a single, declarative sentence, and put it out there. You can always adjust the sentence in a future test if the results of version 1 aren’t positive.

Choosing your survey respondents

There are lots of approaches to take in terms of your survey population, and each is biased, so your best bet is probably to do the test a few times, with different populations.  Let’s say you’re making a product for a general population.  Here’s one approach to take:

  • First, post to your friends on Facebook.  This is a nice broad sample (and obviously very easy to execute), but it’s likely biased towards people with some similarity to you.  I would recommend starting here because it’s easy, and then you can use the results from this survey to adjust your next one.
  • Next, email your 5 closest friends and ask them to post on their Facebook walls.  Again, similar potential biases, but this time you’re going out with a broader sample so theoretically the bias is lower.
  • Finally, use google adwords.  This is potentially a more random sample, but then you have to pay to set up adwords (adds another hour at least to your experiment setup time).  So only do this once you’ve done the other approaches.

But sometimes you don’t want a random sample.  If you’re making a product exclusively for PhD electrical engineers, then polling your entire facebook wall is probably not a great idea.  But is there a facebook group for PhD EEs?  A mailing list?  Maybe start there.  Start with the people who are most likely to want your product and establish demand there, and then you can move out to a more broad sample.

In summary, use a form builder to build a simple, single question smoke test.  Design your test quickly, and run your survey quickly.

Next week we’ll talk about the volume of tests you should expect to run before you come upon an idea worthy of your energy.

Things That Don’t Matter

Note: this is a series on making a digital health startup.  The first post is here.

Last week we talked about writing effective survey questions.  This week we’ll discuss the things that don’t matter in the beginning of a startup.

As I mentioned earlier, there are a million potential things your startup needs at first: “legal advice, patent protection, a team, press, mentors, office space, incubation, customers, champions, business cards, a logo, a website, tee shirts, a ping pong table, and a mission statement.”  One of the problems is figuring out how to allocate the little time you have.  You don’t have much extra energy to work on this new germ of an idea you’ve been developing!

Last week I met Zoe, an entrepreneur who was working on an import business for hospital supplies (name and details changed).  Zoe mentioned how busy she was: she had to get a domain name, design a logo, make arrangements with an overseas manufacturer, file a provisional patent on her website’s factory matching system, and register in Delaware.  She mentioned she needed $300,000 for her initial phase of the project, and did I know an appropriate funding source.  She asked: should she be a C-corp or an LLC?

I said I’d be happy to help her with those issues but first wanted to know a little about her business.  How did she get the idea?  Which supplies were she starting with?  What hospital was she piloting with?

She responded: “Oh, I haven’t spoken with any hospitals yet.”  I asked her why not, and she responded, “Well I want to make sure everything is in place before I go out there.”

I told her I didn’t think this was a great idea.  How can she choose a factory until she knows which supplies the hospitals want?  Is it small ones, like gauze, or large ones, like MRI machines, or something else?  And what quality-assurance procedures will she be required to follow?  There are thousands of factories worldwide, and it’d be hard to know which ones to choose until she had a better sense of which supplies she needed to source.

Further, did she really need that matching system?  Maybe on day-one she could do the matching herself.  “Well that’s inefficient and wouldn’t work well with a thousand hospitals,” she responded.  You don’t have any customers yet, and you don’t know which factories you’ll need to work with.  You don’t know whether the interface should be an app, or a website, or something else.

Further, who cares if it’s inefficient in the beginning?  It’d take dozens of hours to make an algorithm and website; that’s a huge time-sink before you really know what you need.  “Do things that don’t scale,” I told her.

But more fundamentally: how did she know that she was making a service people cared out?  She answered: “The idea sells itself.  I can find cheaper supplies than the brand names, so why wouldn’t the hospitals want it?”

I remembered back to my early days with Podimetrics.  I had spent weeks cold-emailing hospitals until I found a first pilot customer.  By no means did the idea sell itself, even as a product that promised to save lives and improve quality of life.

I said this to her, and I suggested she focus her energy on speaking with hospital administrators and establishing that people wanted her service, before she spent time with factories and other things.  Further, emailing hospital admins costs zero dollars, so she wouldn’t need to raise any investment dollars, and since she wasn’t raising funds she also didn’t need to register as a company.  And because she was going to postpone work on her matching system, she could also hold off on filing a patent, registering a domain and making her logo.  All she needed was a powerpoint presentation.

I got an email from Zoe last week: “I spoke with the hospital director, and we have a follow-up meeting this week!”

In summary, the beginning phase of a startup might feel overwhelming, but if you can ignore the distractions, it’s easier to get to manage.  Things that matter: believing in your idea, confirming that people want your product (or searching until you find something people do want).  Things that don’t matter: logos, company formation, patents, funding, websites — basically, everything else.

And when you’re in the beginning, you can often squeak by with little more than a powerpoint presentation.  Forget about money or other resources; if you have the will to make an idea, you can get it going.

Next week we’ll discuss a quick and accurate way to determine whether people want your product.

Good Survey Questions

Note: this is a series on making a digital health startup.  The first post is here.

Last week we talked about deciphering what people really think when they give you feedback on your startup idea.

This week we’ll talk about asking good survey questions.  As I mentioned earlier, a well-designed survey is a good way to find out the extent to which people like your idea.

Does Someone Want Your Product?

There are many potential goals of a survey.  In my opinion, the most important goal is to find out whether someone wants your product.  I’ve found it’s best to be direct, descriptive, and action-oriented.  A good question is: “We are developing an app for cancer patients.  It provides information on treatment, a chatting service for you and your physician, and an automatic prescription reminder service.  It costs $2.99.  If this product were available today, would you go on the Apple App Store today, buy it, and agree to use it for two weeks?”

Why is this a good question?

  • First, it’s direct.  Instead of saying, “We are considering making…” or “We’re thinking of making…”, it puts the survey respondent in the frame of mind of a real product that will exist, and hopefully the respondent will be more likely to give a truthful response.
  • Second, it’s descriptive.  If you describe your product in vague terms, it’s hard to know whether the product will be useful.
  • Third, it has a specific action item.  Asking someone to download an app, pay for it, and then use it for two weeks is a lot of work.  Only if someone really likes your idea will s/he agree to such demands.

But still this isn’t perfect.  People who say they’d say yes sometimes don’t actually follow through.  A friend of mine divides the results of responses like this by three; in other words, if 60% of people respond “yes,” he interprets that result as 20% will ultimately buy.

One way to counteract this is to use a survey service that allows credit card ordering (such as the wonderful Typeform (note: you should probably go visit Typeform right now just to see their homepage)) and let people place an order.  Let them join the “special early order group” for a 10% discount, and take their pre-order cash.  This way there is zero ambiguity about the intentions of someone who has already pre-ordered your product.

After you ask this question, you might want to ask a question about features.  “Why do you like this product?”  “Given this list of features, which one do you like most?”  “If the first version of this product had only this feature, would you still buy it?”  These questions help you establish your product feature roadmap, and they help you figure out what people really care about.  Is it one feature, or is it the price, or is it the combination of things that matters?  Understanding these nuances will help as you begin making the product.

Note: You might be worried about the ethical implications of telling people you’re actively building something that is (at the moment) just an idea.  I think a good way to address this is to get folks’ email addresses during the survey, and to send regular emails.  If you decide not to go forward with the concept, send an email explaining why.  If you’ve accepted pre-order money, refund it (with interest, if possible).  As long as you’re prompt and transparent, it’s hard to be faulted.  You can also offer to give the source code to anyone who’s interested in pushing forward with the idea, and you can list other places people can go to get similar services.  But really, it’s not a huge deal; people generally understand that sometimes popular projects are shelved, and in the mean time, you’ve gathered really useful data about your product.

Other Survey Questions

Another goal of surveys is demographic information; it’s important to understand the category of person you’re dealing with, for the purposes of qualifying the relevance of a person’s response.  Let’s say you’re making an app for cancer patients and you run a survey, and 100% of people say they love your idea.  Is that idea going to succeed?  Maybe, but it helps to know whether the survey respondents are cancer patients…or whether it’s your ten best friends filling out the form because they’re trying to be supportive.  For example, I recently ran a survey on a product for nursing moms, so I began the survey with the question: “Are you, or have you been, a nursing mom?”  It was interesting to see how the responses among both categories.

It’s also important to know demographic data so you can develop personas of your customers.  Maybe 100 people like your idea, but for 3 different reasons.  Using demographic data helps you divide those people into categories, to help you customize products to each group.

Another potential goal of a survey is quantifying the size or magnitude of the “problem.”  In the survey I ran for nursing moms, the problem we were seeking to address was mastitis, or painful inflammation of breast tissue.  We were thinking of designing a product to address mastitis, so we wanted to know the extent to which mastitis affected these moms.

In a different example, I wanted to know the biggest pain points involved in biking.  So I ran a quick survey.  The first was a demographic question, designed to qualify the respondent (I wanted to make sure the respondent was actually a semi-frequent cyclist).  Then I asked six questions with a 1-to-10 scale, one being “not an issue” and 10 being “bothers me all the time”.  “For the following questions, please tell us how much each bike commuting issue bothers you.”  1: I’m worried about my bike being stolen, 2: I hate biking in cold or rainy weather, etc.  I then put in a freeform answer at the end, to capture anything I might have missed.  “Is there another bike-commuting issue that’s really annoying for you?”  And then I asked 30 people to fill it out (you need enough people to fill out the survey that you feel comfortable that the results are real).

In this way I was able to see which issues were most painful.   Also, given two options, one with a higher average pain but bell distribution, and the other with a lower average pain but spiked distribution at the 8 or the 9, I’d prefer the second, because it means there is a core of people who feel strongly about an issue, and those can be the early adopters.

Other General Tips

  • Try to keep respondents un-biased as long as possible.  Keep the title of the survey generic, so people don’t unconsciously tailor their responses to what they think you want.
  • Keep it short.  Every question is another opportunity for people to give up.  Only ask what’s absolutely necessary.
  • Know what you want to get out of every question.  Before you ask a question, write out on a sheet of paper the thesis you’re trying to test.
  • Use free-form answers when you want a broad number of responses, and then switch to structure multiple-choice when you want to analyze the data quantitatively.
  • Show the survey to a few buddies before you release it, to work out the mistakes and unclear language you’ve probably accidentally included.
  • Continually tweak the survey as you learn things.  If no one likes your product at $10, lower the price to $5 and see what new people think.  If everyone likes it at $10, raise it to $15 and see if your percentages decrease.
  • End the survey with a, “Is there anything else you want to tell us,” because often people will write brilliant things you’d never think to ask.
  • See this blog post for further information, from a guy who’s had two successful Kickstarter campaigns.

Check out this survey I ran for nursing moms to get a sense of some potential techniques you can use.

Next week we’ll talk about things that don’t matter when starting a digital health startup.

Finding Out What People Really Think

Note: this is a series on making a digital health startup.  The first post is here.

Two weeks ago we discussed the propensity of friends and experts to lie to you about your concept.

This week we’ll explore a method for capturing valuable information through the lies.

I want to make it clear that I don’t think people intend to lie or confuse you. The problem is they’re too well meaning; they don’t want to hurt your feelings, and they doubt their own expertise, so they sort of tell white lies that make it hard for you to know that they’ll never use your product and think it’s rubbish.

But wait! All is not lost; there are ways to uncover someone’s real opinion, even if the words are largely positive and noncommittal.

For example, here are two conversations I’ve actually had (emphasis added):

CONVERSATION A

Me: Ok so that’s my product; what do you think?
Venture capitalist: What an interesting idea! I wonder how this would impact the future of finance if it were rolled out worldwide. Such an intellectually fascinating concept. I love it; can’t wait to hear how it turns out. Let’s plan to talk again when you have some data to show.

CONVERSATION B

Me: Yeah so the way it works is you get a package every month with a bunch of makeup samples in it.
Friend: Oh cool, and how does the…
Friend, not part of conversation, but overheard my description: OHMYGOD I want this. (Pulls out phone) What is their website I’m going on my phone and signing up right now.

Both conversations are positive, and both might sound like good concepts. But A is my old failed startup MatchLend, and B is Birchbox, the startup that created an entire new category of startups.

The way you can tell is by following closely the language. The MatchLend conversation is intellectual and passive. “Wouldn’t it be cool…” The Birchbox conversation is emotional and active. “I want…” If the conversations about your idea are passive, and if they remain in high level academic discourse, you’re not making something people care about. It’s when people make a public display of their desire for your product that you know you’re onto something.

Again, this doesn’t mean you have a bad idea, only that the person you’re speaking with doesn’t think it’s a good one. By no means am I suggesting you give up on your concept when you get MatchLended once; you should go out and talk to ten or 20 more people before you decide it’s a trend. It only takes one good investor, or one good customer, to get you started. And there are millions of people out there.

In fact if you have a really good idea, it’s likely that most people won’t get it anyway. More I want to you decipher the coding in the language, so you can really know what they mean.

But if you talk to the smartest people in your industry niche, and even they say no, then I might suggest you consider moving on, or at least tweaking your idea a little.

Next week we’ll talk about asking good survey questions.

Step 2.1: Tiny Experiments

Note: this is a series on making a digital health startup.  The first post is here.

In last week’s post, I talked about the tendency of experts to provide well-meaning-but-un-helpful feedback when you pitch your idea.  This week, I’ll talk about a technique for finding out whether people really like your idea: tiny experimentation.

Tiny Experiments

Tiny experiments are a great way to find out if you’re building something useful. If you set your criteria beforehand, it becomes easier to avoid bias, and you’re more likely to get a result that approximates reality.

So what do I mean by tiny experiments?  A tiny experiment is anything that helps you answer a specific question confidentially, as quickly and easily as possible.  For example:

Let’s say you want to make a new lunch restaurant.  It’d be cumbersome and expensive to get a license, rent space, buy equipment, hire staff, plan menus, and open, all before you know whether people actually like your food.

So why not just stand on the street offering samples, and for anyone who seems interested, offer them a coupon to pre-order $10 worth of food for $5.  If they really like your food they’ll do the pre-order, and if they don’t, they won’t.  If you stand on a busy street during rush hour you might interact with 30 or 40 people, and you’ll have a decent sense for your food’s demand.

Let’s say you want to build a new breast pump for nursing moms.  It’d be cumbersome and expensive to design the pump, build it, test it, and get FDA approval, all before you know whether moms want your product.

So why not design a quick 5 minute survey and send it to a few moms?  Describe the pump and then ask a question like: “If this breast pump were available today, and it were free, would you agree to use it for three days in a row?”  Moms are very busy, and they’re only likely to use a new product if it’s something they really want.  If you frame the question in terms of their willingness to experience a mild inconvenience in exchange for the new product, then you’ll find out whether people like it.

This technique, asking if people would use your product if it were free, comes from Steve Blank, a legend in the startup world.  In his essay about the topic Steve discusses the technique for a business-to-business IT product, but really it can be applied almost anywhere.

The key to a good “tiny experiment” is to make it simple and quick, and precise.  Ideally you should get your answer within five or ten hours of designing the experiment.

The Goal of a Tiny Experiment

At a high level the goal is to find out whether people want your product in exchange for some inconvenience. For example: use my product, but pay me X dollars. Use my product, but go through the hassle of integration with your tech team. Use my product, but get your MD to sign on.

Simply asking people, “do you like my product,” is difficult because it’s so abstract. Do I like it? Sure — in some cases. But getting people to make a specific tradeoff in exchange for your product gets you to a more precise knowledge of their desire. And if people still want to use your product, even with the inconvenience, then you’re making something people want!

A variation on this approach, suggested to be my the legendary Doug Ranalli, is to present two different potential products and to ask the customer which idea s/he likes more. Again people often find it hard to say whether they like something in the abstract, but comparisons are way easier. Do I like this telemedicine app concept? Sure. But do I like it more than the medical tourism idea? Now that’s useful information.

Put together a list of 15 or 20 product ideas, and just go out and start comparing 1 to 2. After a while you’ll notice the trend that 2 is more popular than 1, so cross off 1 and now compare 2 to 3. Maybe 3 beats 2, so do 3 vs. 4. Eventually you’ll find a product that beats out the others, and that’s the one you stick with.

Designing Experiments

Ok you know you want to do a tiny experiment – now what?  It’s hard to think of your idea in these terms and to simplify your startup concept into something that can be figured out in a short experiment.

So how do you get started?  Just get started!  Your startup probably has a million implicit assumptions in it; try to write down five of them, and then think of a quick way to prove or disprove the most tenuous assumption.

For example, you’re thinking of making a telemedicine app.  There are probably dozens of implicit assumptions in there, but these are some big ones:

  • Customers want a doctor on their phone.
  • Doctors are willing to speak with customers remotely.
  • You have legal permission to do telemedicine.
  • You can charge a price that makes you profitable.
  • You have the technical feasibility to build the app.
  • etc. and etc.

Here are some quick experiments you can run to test each of these assumptions:

  • Customers want a doctor on their phone.
    • Run a survey of 10 friends; ask them whether they’d be willing to use your app for six months as their exclusive first point of contact with doctors.
  • Doctors are willing to speak with customers remotely.
    • Speak with 5 doctors and ask if they’d be willing to sign up for your “Doctors on Call” list (that you just made up).
  • You have legal permission to do telemedicine.
    • Do a quick google search; surely someone has asked this question before.
  • You can charge a price that makes you profitable.
    • Run another survey of friends, and this time ask if they’d be willing to pre-order two consultations for the price of one.
  • You have the technical feasibility to build the app.
    • Set up a five hour time-boxed Saturday afternoon, and see how much you get built.
  • etc. and etc.

Once you get into the mindset of experiments, you’ll start thinking of them for almost anything.  Where should we throw our birthday party?  Go to five places and see what has the best vibe!  Should I launch a new app for medication adherence?  Make a PPT mockup and ask 5 friends if they’d agree to use it for a week!

The key is just getting started.  Start with a silly experiment, and try it out.  The next will be a little better, a little smaller, or a little more precise.  And eventually you’ll be an expert!

Next week we’ll talk about deciphering the language in a customer feedback interview.

Step 2: Make something useful

This is a blog series about starting a digital health startup. Last week’s post was here.

Last week’s post was about Step 1, believing in your idea.  This week begins a few posts about Step 2, what to make.

The second major step to making a startup is to make something useful. Make something people want. This is classic Paul Graham, and he’s a genius. You need to make something people want, because if no one wants your product eventually it will fail, and you might as well learn as quickly as possible whether you’re making anything useful. Most inventors are blind to the indifference of the world to their idea. They have faith in the utility of their idea (see last week’s post), and they will not be deterred by even obvious signs of failure.

The problem is it’s hard to know if you’re making something useful, because most of the “experts” you tell the idea to will lie to you.  If you’re working on a new idea, the natural thing will be to find a venture capitalist or industry participant and pitch the idea, and unfortunately in my experience the data I get back from those conversations tends to be pretty bad.

The rest of this post will talk about why these conversations are usually so useless, and next week’s will describe an approach I like to use to really find out what people feel.

Why People Lie

It’s unfortunate that it’s way easier to be nice and encouraging than to be honest. It’s hard to tell someone you don’t like their idea and much more palatable to lie. I first noticed this phenomenon as I pitched venture capitalists for MatchLend, a failed startup I worked on a few years ago. Save one or two exceptions-to-the-rule, every VC told me s/he liked my idea. Everyone told me to keep working on it, and to come back in six months. “You’ve got something.” “There’s something there.” “It’s so interesting.” “I love it.”

This was 2010, and the economy was still reeling from the housing crisis. I needed a job, and I needed proof that this startup was going to become a salary for me. Luckily, the venture capitalists liked my idea, and so it was going to work. What a shock, then, when I approached these same folks for investment and everyone turned me down. Not a single one of these people, who in phone conversations and coffee meetings expressed their substantial support for my project, not a single one wanted to invest.

Wow! I couldn’t understand what happened. Had I incorrectly heard the words of these folks? No — I looked back over my notes and the words had been there. Had I spoken with the wrong people? No — these were venture capitalists in my sub-sector. So what then?

I spoke with a venture capitalist a few years later, and she explained why VCs lie.

  • First, she said, it feels bad to tell the truth. It’s not fun to tell someone you don’t like their idea.
  • Second, I could be wrong, and in six months you might be a major success. Why would I burn the bridge today.
  • Third, you’re an entrepreneur and you’re stubborn, so you probably won’t even listen to my feedback.

This third piece of advice deserves a bit more digging. What did she mean, I asked. Well, she explained, most times when I try to give advice to a startup it becomes an argument. I’ve told you why I don’t like your idea, and you try to tell my why I’m stupid or wrong. You’ll leave the meeting angry, and you won’t even incorporate my (generally wise) advice. After this happens a few times, it just starts to get tiresome to give honest feedback. I love your idea, come back in six months — it becomes the standard “no” for the industry.

I’m an entrepreneur, and I hate when people lie to me, and even I’m guilty of doing it. I think your idea is silly, but I don’t say so, because maybe I’m wrong, and what’s the point, especially if the person I’m speaking with sounds crazy or unwilling to listen? So I tell them I love their idea, but it needs more testing. Or come back after you’ve run an experiment or two.

I don’t think this is a bad thing, per se. It might be difficult to receive honest feedback all the time. Maybe this desire to please, to shield others from criticism, is a deep seeded human survival mechanism. It’s a little like procrastination; I’m not unhappy about the underlying thing, but I do have a few pieces of advice for counteracting it. First, listen. You need to get good at listening to the meaning that underlies the words people say. People feel things, and they use words to try to explain (or, as we see above, to try NOT to explain) those feelings. But these words are not necessarily reasonable proxies for the underlying feelings. You need to listen, to gently probe, to really empathize, in order to understand those underlying feelings.

Second, those conversations are really useful if you can pull out the relevant criticism. Someone has told you a reason s/he doesn’t like your idea. Ok what’s the underlying root cause? If you can use the criticism to improve your product, then you’re a step closer to making something useful!

So if asking people about your idea isn’t a good way to know if you’re making something useful, then what is?  Next week we’ll talk about experimentation, my favorite technique for figuring it out.

Step 1: Believe in your idea

This is a blog series about starting a digital health startup.  The first post was here.

The first thing, and it sounds obvious, but the first thing is being willing to work on your idea.

You are a busy person, and you have many activities fighting for your attention. The first question, then, is: are you willing to devote a portion of your time to this idea? Many people have ideas, but they’re busy, and they never get to working on their idea. Adding a log to an existing fire takes work, yes, but rubbing two sticks together to start a fire takes a lot of work. Keeping a locomotive moving requires energy, but getting a stopped locomotive to move its first inch takes a lot of energy. These two analogies approximate the ratio of work you’ll be undertaking compared to working for an established organization, so step one is deciding whether you’re interested in starting down that path.

And in the beginning it’s often just you, anyway. If you’re lucky, you met your future teammates at school, or at work, or at a hackathon. But even if you do have teammates, the work remains solitary. You are probably (I hope!) the only one with a particular skill or ability, and you’re doing the work yourself. And even if the others on your team are as motivated as you are, you still have to find that inner drive (the “intrinsic motivation”) to work on a project with minimal chance of your work becoming anything beyond a series of slide decks that no one reads. You have to believe that you’re going to succeed, trust that what you’re doing has a possibility of becoming worthwhile. Because if you don’t, you won’t do the work, and your idea won’t go beyond the idea.

In one of his (many) brilliant essays, Paul Graham uses the analogy of caring for a baby to describe the early stages of starting a startup. I love that analogy, but I’d take it a step further: what if you didn’t know the baby would turn into an adult? With a baby, in general if you care for it eventually the baby will grow into a toddler, a middle schooler, and an adult. The early stages are difficult, but the result is reasonably predictable.

With a startup, however, there are a few problems. First, you don’t know what to do. A newborn baby just wants to eat, sleep, or excrete. A newborn startup needs a product, a market, money, legal advice, patent protection, a team, press, mentors, office space, incubation, customers, champions, business cards, a logo, a website, tee shirts, a ping pong table, and a mission statement. Where do you even begin?

Second, a newborn startup is likely to die. I’ve heard that 90 percent of startups fail. What if your baby had a nine in ten chances of dying within a year? How would that change how you approached parenthood?

So for these reasons, and more, it takes a lot of intrinsic motivation to devote energy to your idea. And again, in the beginning it’s only you. You’re the one who writes the description to pitch at the hackathon, and you’re the one who emails a potential mentor to ask for coffee. The startup is just the germ of an idea, and it’s fragile, and you’re alone.

You have to be willing — eager — to do the first bit of work. If you won’t do it, if you aren’t sufficiently enthusiastic about your idea to devote your time to a first draft of a slide deck or a first blog post or a first recipe, the likelihood is no one else will be, either. You have to have…conviction…in your idea, and you have to act on that conviction.

A word on first steps: it’s really hard to get something going. Even now I find myself procrastinating at tasks I don’t want to do. I check email, browse Boing Boing, eat a snack. We all do this, and I think the urge to procrastinate lives deep within all of us. Maybe it’s a deep-seeded survival mechanism or something. I won’t try to kill that urge, but I will offer two pieces of advice.

First, just start. Literally begin writing words, any words. Open a blank TextEdit or PPT file, and begin to type. Just start doing…something. It almost doesn’t matter, as long as it’s active. Checking email and browsing news articles are passive tasks; you’re absorbing something someone else has done. To create something new requires activity, and the hardest part is often overcoming that initial inertia. So overcome it by just beginning to do something, anything, that requires you to type / write / shape / move.

Second, forget about perfection. Eventually your product will be perfect. On day one it’ll be terrible. In general you have to be bad at something before you can be good at it. The first five people who read your business plan / try your app will likely not get what you’re doing. Your work will be seriously flawed, and the people to whom you present will not be able to help themselves from rolling their eyes at you.

You cannot do anything about this. In the beginning you don’t know how to be good, so you’ll necessarily be bad. The only thing you can do is have the confidence to make a second version. Version 1 was bad, and version 2 will also be bad. But it’s a little less bad, because some of the things you’ve messed up in v1 you’ve fixed. Of course there are new problems, and some of the old ones haven’t been fixed. But there are a few fewer problems. By version 3 you’re even better, and by version 6 you have something good. But version 1 was terrible, and your friends literally told you you were stupid and offensive. “How can you think people want this thing?” “You obviously don’t understand how people think.” “I just can’t believe this is a problem for most people.” I’ve heard it all, all in the past two days. Get used to it.

Listen to the reasons for the criticism. Try to uncover what it is they don’t like. Is it your pitch, or your tone, or your underlying assumptions? Do they dislike how your idea makes them feel? Do they think you’re naive?

I’m reminded of a quote (sent to me by my friend Michael) after one such evening.

Too many of us think of ideas as being singular, as if they float on the ether, fully formed and independent of the people who wrestle with them. Ideas, though, are not singular. They are forged through tens of thousands of decisions, often made by dozens of people.  –Ed Catmull

Take their feedback. Don’t be discouraged from continuing to work on your idea, but also don’t ignore their criticism. They’re right, in a way. If they don’t like your idea, there’s a reason for it. Figure out that reason, and then decide if it’s something you want to do something about. Sometimes you intentionally ignore your critics, but often the best thing to do is to incorporate their criticism, and to find a solution to fix it.

Your job as an entrepreneur is primarily problem solving. When a friend tells you she doesn’t like your idea, the “problem” is probably buried in her explanation. It’s your job to find the problem and to find a solution.

So the first thing, and for all intents and purpose the only thing in the beginning, is your conviction and willingness to work on your idea. Really no one will help you to the extent you need help, even your best friend or spouse, and in the beginning most people won’t even really understand what you’re doing, so they won’t believe you. And if people don’t understand your vision, they will always underestimate it, and they will (unintentionally, mostly) knock you down.

Next week we’ll look closely at the next step, making something useful.