Hat tip to the source.
A major pillar of Lean Startups is their use of Minimum Viable Products (MVPs) to test the validity of a product within a marketplace. By definition, a MVP has the minimal number of features that is required to test a given market hypothesis. A MVP allows the originating startup to gather invaluable feedback from customers, which in turn accelerates the feedback cycles around every aspect of development. Put differently, the use of an MVP avoids spending extensive time and resources building a finished product before validating the product concept with customers. When used in the context of validated learning, MVPs are a valuable tool for identifying product-market fit.
MVPs have been discussed extensively elsewhere (see related links below), usually in the context of information technology (IT) companies. The success of the MVP model has been validated in the IT industry, and a common operating procedure for IT product deployment is now early launch followed by rapid product iteration. Software based products, and specifically consumer web products are amenable to such rapid development, as the engineering challenges are well-defined even when significant. In contrast to most software / web based products however, products rooted in the hard sciences like the biotechnology or bioengineering sectors (and yes we lump all sciences together where progress is “hard” to come by), have an appreciable level of technical risk in addition to the market risk that MVPs are designed to address. To successfully map the MVP model onto the hard sciences, such technical risks need to be considered in the context of the large upfront capital and time investments required to abrogate them.
Re-framing the MVP model to include mitigation around the technical risk as well as the market risk is both appropriate as well as imminently necessary. We believe that MVP concepts can and indeed should be applied to fundamental research driven industries like biotech. Having entrepreneurs in these fields use MVPs and validate learning will lead to more capital efficient commercialization of technologies. This will benefit the entrepreneurs, founders and employees, as well as the funding organizations involved, be they VCs, foundations or the government. Because of the different set of starting assumptions inherent to these industries mentioned, we suggest the following three steps to adapt MVP concepts to these industries.
- Test product concepts to identify product/market fit.
- Conduct MVP-focused research.
- Explore adjacent marketplaces for the technology.
Test product concepts to identify product/market fit.
MVPs are used to evaluate the product/market fit. This concept can and has to be rigorously applied to the hard sciences. Too often researchers have an “if we build it they will buy it [come]” mentality, only to later find the developed technology lacks commercial relevance. As such, the first requirement of developing a technology for commercialization is to identify markets you think can be impacted by the technology, and then use an MVP to test the validity of the product within these markets. In the context of research intensive products, testing market need before demonstrating technical feasibility may seem premature and one may receive pushback from the researchers involved. However, to turn a scientific project into a commercial success, one needs to investigate the fit with greatest prejudice, and do that across multiple markets. This means talking to the end users early on. As compared with months of technical R&D that might be misdirected at worst or undirected at best, gaining a detailed view of multiple potential product-market fit scenarios is a high return-on investment effort.
Due to the constraints placed on the commercialization by the time/capital-investment function, entrepreneurs need to pursue clever ways to test product concepts in the marketplace prior to achieving technical proof. One important test is to create the appropriate product profile and socialize this to potential customers within the field. For example, for therapeutics this will involve identifying key stakeholders for a given indication and present to them a product profile of the anticipated active drug, including how it will be administered, dosage regimes, interaction with other drugs that are co-administered and potential side effects, etc. For example, if you’re developing a cancer drug, it will be critical to speak with oncologists, cancer patients, survivors, and payors. Understanding how your therapeutic could be adopted in the context of the current treatment regime is critical and most often clinical decisions are made on factors other than what molecular target is being drugged. This effort will illuminate the opportunities and point to the key challenges that need answering at the earliest stages of technology development. A crucial mistake many startups make is failure to take the current process into account. Never just assume that if you can successfully develop a product the customer will change his use pattern to accommodate you.
Conduct MVP-focused research
Research is often perceived to be a necessarily meandering path. However, as the development effort moves toward the application of the technology in the marketplace, applied research has to be efficiently guided. This requires an R&D process be in place and a significant amount of discipline from everyone involved to ensure that experiments are designed from the bottom up to really answer the important questions about the MVP product. For anyone aiming to develop any successful product, rigorous focus and capital efficient behavior is needed. It’s challenging and very difficult to implement a culture of laser-focused research effort, but fundamentally, a small biotech startup or commercially focused research lab has no choice if it wants to develop a product in times where raising capital on promising research alone is not a winning pitch. It should be noted that if the goal is to develop strong IP based on novel and early-stage science the parameters are different and we will cover those aspects in a following post.
Explore adjacent marketplaces for your technology
Last but certainly not least, early-stage research can and does create technologies that can have many applications – many startups are founded on the premise of a platform technology (technology push). This is often referred to as the “hammer looking for a nail” syndrome, and in many cases the most interesting nails are outside of the entrepreneurs domain of expertise. There are many examples of adjacent markets where products met their ultimate success. For instance, discovery of a drug target that impacted unexpected indications (e.g. Viagra was originally a cardiac drug), applied physics developments used in biotech applications (e.g. Pacific Biosciences optical waveguide technology used in sequencing), genetic engineering used in many industrial biology applications (eg. Genencor’s industrial enzyme production), and bioinformatics analysis technologies generally applied to the big data industry (eg. GNS’ foray into financial and systems analysis).
In summary, using an MVP based on a product profile enables the entrepreneur to be able to nimbly test product concepts in adjacent markets and generate invaluable feedback for further iterations of the MVP and final product. Additional posts will dig deeper into MVPs for different types of biotechnologies.
Here are some links to related content:
Four Steps to the Epiphany, by Steve Blank.