From Bench top to Marketplace, and Back Again

It is variously estimated that startups fail at an alarmingly high rate, and without trying to pinpoint the precise number, it’s fair to say that its highly likely to be the clear majority, 70% or more. Failure here is defined as the loss of the original investment, either in whole or in part. Point being, the capital invested did not result in a multiple of return capital to the investors, but rather a total loss or cents-on-the-dollar return. And if that rate is even close to 70%, it indicates the need to identify critical early risks, deploy better milestone-driven accountability and delivery, and make hard decisions about whether an entity should proceed or not. And that, of course, if fraught with psychological, emotional and political challenges. So, the questions this article poses and attempts to address are as follows; firstly, what constitutes a best-in-class approach to technology de-risk and development and how can it be quantified? Secondly, how can technology and market readiness levels be best determined? Thirdly, what’s a well-tested and rational approach to breaking free of the bench top into the marketplace, limiting risk and exposure, securing initial revenues and market adoption. Finally, how can you use that initial market adoption to drive the next developments and refine the existing for improved adoption and price/value maintenance?

1.     Applying a Systematic Methodology to Chaos

Technology development isn't clean, clear and precise. It’s very often messy, convoluted and frustrating. If you are in the realm of ‘unknown, unknown’s’, you really have a science project on your hand. Unless you are willing to take that level of risk, and the commensurate time (and potential high reward) it may take, consider leaving the technology to evolve and develop into some more well-defined ‘known, unknowns’, or even better, and firmly into the territory of development, known, knowns (thanks to Mr. Rumsfeld for the terminology here). If you have left the technology for 12 months and the former category remains unchanged, and the latter just isn't emerging, that doesn't cast aspersions on the technology per se or of the team developing it. It does say a lot about the fundamental technology readiness level (TRL). There are exceptions to this rule – but generally they follow the principle that early technology that is being defined and developed hasn't yet attained a clarity, foundation and degree of understanding so that it could be more precisely developed into a tangible application in the real world - achieving a viable economic exchange. Ask yourself this question; am I still asking really basic and fundamental questions about this technology, or have I defined a technology envelope that I know the technology fits within (in my vernacular that would have transitioned it from ‘unknown, unknowns’, to ‘known, unknowns’. It’s useful and reasonably practical here to apply a systematic, stage-gate, metrics-driven, quantification approach here, and apply it judiciously, so that you don’t kill the possibility of the very transition you seek. If you can identify, rank, prioritize, assess, put a time frame and budget to the 10 things you have known with higher than 50% certainty you need to address to make the technology viable and usable, it might be argued that you have indeed made the transition.

2.     It’s a superb technology; without any home

History is replete of examples of highly innovative technologies that either did not or may not have a home in the market, being used by people daily to enrich their lives, experiences, improve health, longevity, overall happiness, productivity and wellbeing. Let’s restrict our discussion here to the authors realm of deepest experience, the broad life science sectors. A clinical diagnostic test that offers improved sensitivity, specificity, speed and price seems like a fait accompli in terms of market adoption. Who wouldn't want to use such a test? A health care system focused on the downstream consequences of that test, it’s fit within existing clinical workflows, its ability to add significant clinical diagnostic utility (PPV, NPV) and lead to improved clinical outcomes – which is the majority of global healthcare systems out there. The TRL may not jive with the market readiness level (MRL), and it’s the latter which will determine ongoing success of the entity that develops and manufactures the test. Assessing workflow fit is not easy. I’d argue here that in fact its just as complex and challenging as technology development, and in many cases much more so. Defining how a technology works is usually quantifiable and relatively precise. Defining a clinical workflow, decision handoffs, reimbursement flows, patient stratification, political climate, funding cycles, industry, KOL and advocacy body resonance are less precise. Yet, without their alignment, technology adoption will be slow, complex, challenged and may even fail altogether. How can MRL best be assessed then? One well-tested approach is to begin with a detailed understanding of the range, variability and nuances of a clinical workflow – the end to end analysis of initial patient presentation, incidence-prevalence assessments (who and how many present where, how, why and in what way…), what diagnostic or symptomology tests are performed (and what can be gleaned from them), what is the next step in the workflow for the patient (and the doctor, and payors, and the facility, and clinical staff…) and so on. In assessing any given technology – even if it can bring superior diagnostic or prognostic value – will be adopted, needs firstly to assess if it can be adopted, and if so, precisely how. Having a value proposition by constituency is also a good means of making the assessment. What's in it for everyone who is touched by it?

3.     Market Push meets Market Pull

Perhaps one of the best examples of the need to assess, seek, attain and ensure alignment within the healthcare landscape into which a technology is adopted, would be the medical device world. Why? Because it’s a highly regulated market, the clinical approach is to do no harm first, making it a conservative market, it’s a ‘hard-evidence’ based segment and even though vast sums of money are spent in healthcare, reimbursement is always a question. The demonstration that a technology provides an improved clinical outcome – itself challenging to achieve – needs to be assessed in the context of whether, once that clinical outcome evidence has been obtained (and caveat emptor for investors on the ever-increasing costs of attaining viable clinical outcome data in [large] clinical trials) – is also the question of the degree of resonance of that clinical outcome data (and all other factors – price, utility, work flow, mode of operation, format of results…) with the critical ‘market pull’ constituencies (payors, providers, clinicians, patient advocacy, industry bodies, etc.). It’s challenging for anyone to hold more than say a handful of factors in their minds at one time, yet the process of commercialization necessitates that all these factors be assessed, ranked, aligned, understood and often, fully in parallel. The more you can bring the clinical workflow, continuum of care, decision points etc. back into earlier productization of your technology, the more likely it will be that you will make critical product/service attribute decisions reflective of the landscape you are entering and user needs– rather than driving productization from a what’s ‘technologically attainable’ direction. Market ‘push’, without aligned market ‘pull’ requires deep pockets and patience from your backers. Not impossible, but important to be aware of the dynamics of slow adoption – one recent example being breast cancer gene expression profiling tests - in some cases taking up to 8 to 10 years of concerted effort and the concomitant funding required, to attain solid market acceptance and adoption.

4.     The Follow-on Technology is Often Better

Startup companies can be so laser-focused on ensuring their very survival – and having lived in this world for some time, the CEO’s number one concern really ought to be running out of capital, all other entity existential questions, development issues and commercialization challenges being secondary to this – that once the test or technology gets into the market, there can be a ‘mission accomplished’ attitude. But, if you have done a good job of assessing the healthcare and clinical landscape to the degree sufficient to ensure your technology is adopted, it’s a hugely valuable data set to both improve your existing technology, and very likely for product/service adjacencies and add-ons and further value creation potentials. This last piece of the feedback loop back to developers, engineers and scientists is sadly too-often overlooked. Well-run, innovative companies formalize this mechanism via formal market research feedback, and the innovation engine can be stoked yet again – this time with better, clearer, more nuanced, better validated market information, expediting the innovation life cycle, which ought to please CEO’s, developers, customers and investors.