by Douglas Romanoff
Eric Ries champions the Lean Start Up Methodology as a means for entrepreneurs to more efficiently manage financial and human resources while increasing their odds of success. At the root of his approach is the idea that entrepreneurs should measure progress in units of validated learning, rapidly iterating through build‐measure‐learn cycles designed to test hypotheses and refine business model elements. By avoiding excessive subjectivity, and instead gathering empirical and measurable evidence, the entrepreneur operates with less risk and more cost effectiveness.
Although Toyota’s management philosophy is credited as the inspiration for lean concepts, the true origins of the approach lie in a discipline outside the realm of business. The Scientific Method has served as the gold standard of systematic inquiry for chemists, biologists, and physicists over many centuries. According to its tenets, researchers should gradually refine elements of a scientific model through a series of structured experiments, obtaining measurable data to validate clearly articulated hypotheses. Sound familiar? The researcher’s scientific model is the entrepreneur’s business model; the researcher’s test tube, the entrepreneur’s Minimum Viable Product (MVP). So Eric Reis’s breakthrough is not in the creation of the Lean Start Up Methodology itself, but rather in borrowing the method from science and applying it to entrepreneurship, reframing its underlying concepts in the nomenclature of business. His insight is that both cutting edge entrepreneurship and cutting edge science are experimental endeavors, and can share techniques to investigate poorly understood phenomena, acquire new knowledge, and integrate that new knowledge to refine previously held beliefs.
If we agree that Lean Start Up Methodology originates in the techniques of science, there is irony in the notion that it does not apply to science‐driven businesses. In his blog, Union Square Ventures partner Fred Wilson argues that there is a growing cleavage in the venture capital industry between businesses such as software and businesses such as clean technology. Many students in Launching Tech Ventures would seem to agree, arguing in class that lean approaches do not apply to startups involving substantial technical risks and manufacturing assets. Fast product development cycles are not practical and customer feedback is less relevant for such business, they might add. In brief, the science of business does not appear to apply to the business of science.
I argue that this view is by and large misguided, though not altogether without its merits. The first fault in such a line of thinking is definitional. Cleantech is not a monolithic and uniform industry of its own, but rather an umbrella term that encompasses energy generation, transportation, telecommunications, and other verticals. Each of these verticals supports an array of business models with very different economics. In fact, there are subsectors and segments of the value chain in cleantech that are more similar to information technology, services, or electronics than not—consider OPower, SunRun, and Enphase. All lean concepts that apply in these more familiar industries apply to related spheres of cleantech. Comments about the applicability of the Lean Start Up Methodology to cleantech businesses therefore err by generalizing to broadly.
In keeping with the underlying spirit of such arguments, however, let’s focus on a subset of cleantech that is driven by science: energy storage. Battery manufacturing involves the technical risks and physical assets described earlier, and as a result does not lend itself to rapid iteration to the same extent as, say, developing brokerage software for real estate agents. Upon closer inspection, however, this line of thinking confuses cheapness with leanness by using an inappropriate benchmark for cleantech. The Lean Start Up Methodology does not promise to level the playing field between Aquion and RentJuice with regards to funding requirements. A new software application is in most cases cheaper (e.g., requires less capital) to develop than a new battery chemistry. Game over.
But being lean is not about being cheap—it’s about being efficient with resources. By applying the concepts of the Lean Start Up Methodology, Aquion has more efficiently used its resources while increasing its odds of success relative to other battery start ups operating under the status quo. Founders Jay Whitacre and Ted Wiley stage technology development through a series of MVPs (e.g., bare bones R&D solutions that are “good enough”) designed to validate key hypotheses (e.g., potential product performance and manufacturability) with the smallest set of product features (e.g., precision only to the degree that is necessary, and no more). The result is rapid iteration by battery development standards and greater capital efficiency relative to peers in the same industry.
Clean technology and leanness to are two concepts that seem to invite misunderstanding and misuse. By applying them both with greater precision, I believe we reveal more clearly where the one relates to the other.
Showing posts with label Science-based businesses. Show all posts
Showing posts with label Science-based businesses. Show all posts
Learnings from Applying “Lean Startup” to a Science-Based Business
by Arun Agarwal (Twitter: @arun_agarwal)
Recently I had the opportunity to take Launching Technology Ventures with Tom Eisenmann at the Harvard Business School, and learn the latest and greatest about the process for building capital efficient startups using the “lean methodology.” Lean is a movement started by Eric Ries that encourages entrepreneurs to design cheap experiments to test their products and positioning in the marketplace and get real data, rather than relying on the founder’s grand vision which can often lead to building a business that is 10, 90, or 180 degrees off from actual market needs.
My project for the course involved a “science-based” hardware business. I worked with a university professor in Switzerland to spin a fundamental technology out if his lab that we believe could revolutionize on-chip and off-chip digital communications. Tools and techniques that lean methodology suggests using include highly agile product development cycles, launching early, building “dummy features” to see if users interact with them, A/B testing, and watching customers actually use your product. As such my initial reaction was that lean had no place in the business I was working on, where our customers will in many case be large semiconductor or hardware manufacturers (not a group that can easily be used in a beta test), and our product development cycles are long (since we’re doing fundamental research in a lab and fabricating something physical vs. writing application code in an Amazon EC2 cloud).
What I learned however, was that even though lean will need to develop a different set of tactical recommendations about how to run a product development or marketing process in such businesses, the underlying framework is still very useful for entrepreneurs in this space:
This helped us understand that we couldn’t simply solve the problem of hitting market at what we believed was the right time by doubling the number of engineers or capital, but that it was a long pole external item. From there we could ask the next set of questions such as, “how would we go about finding the person we need to get on board to get the deal done in 4 or 5 months?” (a new hypothesis that such a person must exist). This iterative process helps us systematically remove risk from the business without spending a lot of money.
I encourage people who are passionate about the lean methodology to develop more specific techniques for deep technology entrepreneurs so that everyone doesn’t have to design their own experiments from scratch. While I have great belief in the future of Internet businesses with strong network effects to both change the world and return well for their investors and operators, I feel it’s undeniable that revolutions in clean technology, biotechnology, and data infrastructure have a critical and unique role to play in the sustained growth of entrepreneurship and United States GDP.
Recently I had the opportunity to take Launching Technology Ventures with Tom Eisenmann at the Harvard Business School, and learn the latest and greatest about the process for building capital efficient startups using the “lean methodology.” Lean is a movement started by Eric Ries that encourages entrepreneurs to design cheap experiments to test their products and positioning in the marketplace and get real data, rather than relying on the founder’s grand vision which can often lead to building a business that is 10, 90, or 180 degrees off from actual market needs.
My project for the course involved a “science-based” hardware business. I worked with a university professor in Switzerland to spin a fundamental technology out if his lab that we believe could revolutionize on-chip and off-chip digital communications. Tools and techniques that lean methodology suggests using include highly agile product development cycles, launching early, building “dummy features” to see if users interact with them, A/B testing, and watching customers actually use your product. As such my initial reaction was that lean had no place in the business I was working on, where our customers will in many case be large semiconductor or hardware manufacturers (not a group that can easily be used in a beta test), and our product development cycles are long (since we’re doing fundamental research in a lab and fabricating something physical vs. writing application code in an Amazon EC2 cloud).
What I learned however, was that even though lean will need to develop a different set of tactical recommendations about how to run a product development or marketing process in such businesses, the underlying framework is still very useful for entrepreneurs in this space:
- Develop a hypothesis for what you believe the right answer will be.
- Design a cheap experiment that serves as a falsifiable test to see if your hypothesis can be disproven.
- If the answer is “it can be disproven,” then reform the hypothesis and re-test it. Otherwise, form a new set of hypotheses that further your understanding.
The key here is appropriately designing the falsifiable test so with some degree of certainty you can challenge your hypothesis, rather than just “gathering data” through market research to give yourself a better hunch. This guidance helped me and my colleagues ask specific questions of market experts such as “is there anything that would make it impossible for 5 engineers and a $4M capital base to develop XYZ product for ABC market in 2 years?” The response we heard was “well before you could start development, you would need cross-licensing IP agreements with either company D, E, or F, and such an agreement typically takes at least 10 months to put in place.”
This helped us understand that we couldn’t simply solve the problem of hitting market at what we believed was the right time by doubling the number of engineers or capital, but that it was a long pole external item. From there we could ask the next set of questions such as, “how would we go about finding the person we need to get on board to get the deal done in 4 or 5 months?” (a new hypothesis that such a person must exist). This iterative process helps us systematically remove risk from the business without spending a lot of money.
I encourage people who are passionate about the lean methodology to develop more specific techniques for deep technology entrepreneurs so that everyone doesn’t have to design their own experiments from scratch. While I have great belief in the future of Internet businesses with strong network effects to both change the world and return well for their investors and operators, I feel it’s undeniable that revolutions in clean technology, biotechnology, and data infrastructure have a critical and unique role to play in the sustained growth of entrepreneurship and United States GDP.
Signing Up for a High-Maintenance Boyfriend: Growing Pains in a Lean Biotech Startup
8:03 AM
Science-based businesses
by Joyce Chan
My experience in biotech has taught me one thing: this business is complicated! Believe it or not, figuring out the science behind the function of a molecule or chemical pathway is the “easy” part. Though it involves countless hours and the dedicate talent of brilliant scientists, the research portion is methodical, rational, organized. Monetizing a drug or diagnostic involves the buy in of a dizzying number of decision makers (investors, payors, providers, regulators, etc), each with their own assumptions, expectations, and opinions. Much like a high maintenance boyfriend, a lean biotech startup needs the nurturing care of an understanding and patient partner that is willing to guide and put up with the drama in hopes that one day, he’ll pay off.
Changing Him Is Hard and Takes A Lot of Time
Most lean startups are flexible. We see iterations of the new product within months of customer feedback. Facebook has continuously iterated on its interface to give the user a more dynamic system that would enhance the online social experience. In the last 2 years, I can think of dozens of changes that have been made to the website. Some changes have revolutionized my experience (e.g. the introduction of detailed privacy controls) and others I barely noticed (e.g. slight modifications in color scheme). However, in a similar 2 year period, Predictive Biosciences did not pivot their business once and didn’t seek customer feedback for 3 years. The key difference here being that the product either works or it doesn’t. There is little any “user” can tell you that will help you fundamentally change the product. Like a patient girlfriend, the entrepreneur must be patient and wait for the product to reach those key milestones and sometimes this wait can last for years.
He Is Insecure, Demanding and Needy
Healthcare is filled with stubborn, big egos. Because everyone is so highly educated, every decision maker naturally assumes that he is right; it can’t be possible that a company no one’s ever heard of could understand more about the intricate dynamic of genomic sequencing than a prestigious M.D. PhD. It’s hard not to go through a period of doubt if you’re an employee, investor, or partner in such an industry. The entrepreneur needs to expend vast amounts of energy calming the internal insecurity. Creating a reality distortion field is particularly helpful to her. It’s her job to keep moral high internally and win over key opinion leaders who will help her sway the rest of the medical community. She will have to charm the world into loving her boyfriend just as much as she does.
The demanding nature of the biotech startup isn’t just limited to getting physician buy in. Regulators will either believe in the product’s efficacy or they won’t. Even if the product is scientifically viable, there little an entrepreneur can do once FDA has made a decision. If the FDA thinks that it is right… there’s no changing its mind. Like a demanding boyfriend, the FDA requires that you prove your product to them in what seems like an endless approval process before you can take your product to market.
Developing a new drug is extremely expensive and can cost tens of millions of dollars. The biopharmaceutical industry spent $65.2 billion in 2008 on R&D. Amplifying cost is the complex value chain. Educating each key player that this new product adds value is pricey and doing this step poorly could cost you the success you’ve been striving for. It is estimated to cost $1.7 billion dollars to bring a new drug to market in the U.S. The on-going cost of capital is high. Like a needy boyfriend, biotech startups need a lot of resources to be successful; make sure you put those resources to work in the most efficient way possible.
Prognosis: Make Sure He’s Worth the Effort Before You Commit
Starting a biotech company requires a lot of commitment than the standard lean startup. It makes more time, cost more money, and has a slower feedback loop. Stiff regulatory requirements and a complex value chain make the investment significantly riskier.
However, like a high maintenance boyfriend, sometimes it’s worth the risk. Payoffs on successful drugs are astounding. Socially, you have brought a new product on to the market that will save/improve the lives of people around the world. Financially, you have a steady and undisputed (depending on patent law) income stream for years. Rituxan has been on the market since 1997 and continues to bring in $2.6 billion in revenue for Genentech annually. Furthermore, the patent is not set to expire until 2015. If you commit yourself to the right drug and properly nurture it through the start development and go to market process, you will reap incredible benefits.
Biotech lean startups are a different animal. Though some lean principles apply, biotech startups are a lot more drama that most have the stomach for. The upside is great, but be ready to be completely heartbroken if your relationship doesn’t work out.
Cleantech Entrepreneurship: Surviving a Long, Cold Long Winter
3:57 AM
Science-based businesses
by Richard Zhu
We had a very interesting cleantech case in HBS Launching Tech Ventures course this week – Aquion Energy: a novel energy storage firm using lean start-up techniques despite its long product development cycle. So different from consumer internet business, Cleantech companies don’t have much chance to pivot; they don’t have many opportunities to test their product with users; product development is so science and engineering driven that it is very time and capital-demanding. Compared to the cases we had on internet, especially social networks, starting-up in cleantech is like a long cold winter: you really need to figure out how to survive this brutal weather before embracing beautiful spring and summer. (Yeah, that’s what HBS can teach you by locating at Boston!)
Couples of thoughts on how to survive:
Polar bear or tree frog: who is born to survive the winter?
We talked a lot about founder-product fit in the past cases. The right experience, skill, and knowledge are universally critical for founders to get the start-ups right. Here in cleantech, another scale needs to be further considered: time duration. Given the limited possibility to make it in 2 or 3 years, entrepreneurs need to be really prepared for a longer journey. Who has the superior gene to win out the winter? In this case I saw the founder of Aquion Energy. Being a University Professor definitely gave him a great advantage: Working on technologies in the school’s lab, spun out a company when ready, asked for lower academia load to allow more time on the company… Even though we can not change who we are, but in case you get good starting positions like that, at least you know you are ahead of others.
Energy conservation: lean start-up.
Aquion Energy did great on lowering their burn rate: using second hand research equipments, adopting cheap production line even after receiving millions of dollars of funding. Reasons being simple and persuasive: protect founders and early investors’ equity from dilution.
Take free resources, and avoid unnecessary trap!
There really are ‘free’ money for cleantech: DOE want to stimulate this technology, go and take it! I got a friend doing solar air-conditioning without a single cent of VC money but progressing fast: he is really using the government grants well, together with the research facilities while he is working in school’s lab. There are always rules on how the research could become the property of government or school, but in a lot of cases, these are not obligatory. Understanding these resources and rules may give the start-up lots of tail wind.
Pick the food available while chasing the big!
In a lot of cases, we see a huge final reward for clean technologies: general lighting for LED, portable nuclear electricity generator, distributed power/heat/cooling system for solar, plug-in pure Electronic Vehicle and utility-level storage in this case. The challenge would be how many years can a start-up run without generating a sustainable profit? LED has been around for half an century before coming to $10 range. So it’s always good to chase big, but don’t ignore the chances to pick decent rewards along the journey.
Find a advantageous location.
Evergreen Solar is a solar technology company that aims to significantly reduce the production cost of solar panels. Their pilot plant was set up at Devens of Massachusetts. This year, they are shutting it down, since the labor price in this area made their advantage in cost reduction less attractive. (Welcome to New England, recall the textile industry!) By building a factory in China, the economics would work better. Without any doubt, the large amount of solar manufacturers in China would crave licensing their technologies when ready.
Thinking about by-passing rough weather?
Cleantech is not always dark and cold. You still can win with innovative business models: think about OPOWER! I was so amazed about how well-organized consumer engagement can do. They can improve energy efficiency without installing a smart meter!
So glad to have cleantech stuff in the course. Looking forward to more!
