Two Common Business Model Misconceptions

This blog post highlights two common misconceptions that bioscience startups often have with respect to their new venture’s business models. These misconceptions can lead to poor decisions that result, at best, in resource-wasting delays before a self-sustaining enterprise is established, and at worst, in their venture’s premature demise.

We will start with a quick recap of what we mean by a “business model”. And then delve into the two common misconceptions:

  1. Business Model = Commercial Model.
  2. Business Model is Fixed Early On.

What is a Business Model?

Your Business Model explains the essence of how your business “works” i.e. how your business is set up and operates to create value for your customers, your shareholders, your team members and (increasingly for many social ventures and B corporations) society at large. At its simplest level, any business model must encompass three fundamental overlapping concepts, namely:

  1. Customer Proposition.
  2. Commercial Model.
  3. Operating Model.

Your customer proposition articulates what problems you solve for your customers and/or what jobs you perform for your customers. And how you provide a solution. This proposition needs to be compelling enough for your target customers to proactively choose you rather than select a competitor or do it themselves.

Your commercial model comprises:

  • Mechanisms for capturing revenue from your customers including the corresponding pricing structures.
  • How you segment your market i.e. which specific categories or groups of potential customers are you focused on.
  • The channels through which you reach your customers.

Your operating model comprises the business and scientific/technical processes you use to deliver your customer proposition. These processes comprise a network of activities conducted by your own resources and those of your partners, coordinated and combined to deliver customer value. Your operating model needs to be efficient and scalable in order to generate an acceptable economic return for your investors and your team members. Underlying your operating model will be some key resources and key external partners.

Misconception 1: Business Model = Commercial Model

Many bioscience startups think that once they have figured out the commercial model to generate revenue (e.g. technology licensing, service fees or product sales), they are all set. But a common pitfall is having a superficial understanding of the customer proposition. You believe your science or technology is so unique or “just so much better” that it will be blindingly obvious why customers want to pay you lots of money for it.

In practice, your customer proposition needs to be compelling enough for customers to break their behavioural momentum to spend time and money switching to your offering. This necessitates overcoming a much higher threshold than just having something that prospective customers say is attractive. For example, in a typical business-to-business (B2B) scenario, some role in the buying organisation (other than your offering’s immediate user) may lose budget, influence or status, creating a natural blocker to the sale. A common warning sign is when lots of prospective customers say nice things about your offering, some of them even happy to sign non-binding letters of intent, but when “the rubber hits the road”, few are willing to hand over real money in a binding commitment.

You typically need to work a lot more on your customer proposition than you think. Questions you need to ask include:

  • For which customers (including multiple roles in B2B scenarios) will we create the most impact and what is the precise nature that impact?
  • Is my impact substantial enough to change entrenched customer buying and usage behaviour?
  • How do we articulate that impact convincingly and cost-effectively?

Another common pitfall is not giving enough thought early enough to the operating model. You cannot ignore the other half of the business equation i.e. you need (eventually) to make a profit by incurring costs that are less than your revenues. Hence your operating model must be cost-efficient when scaled up. In healthcare therapeutics, diagnostics and devices, the cost and complexity of full-scale manufacturing and logistics to regulatory standards dwarfs the lab-scale process you might currently be using to create your prototypes or clinical trial candidates.

Even worse (because it is not obvious early on), an internally-efficient operating model that forces your customer to spend additional time and money to adopt your offering is doomed to failure unless you create the right incentives. The impact on the customer’s process on the demand side of your operating model is just as important as what you are doing on the supply side. For example, in dermatology, shifting from a prescribed skin cream formulation to a laser therapy procedure represents a costly shift in what dermatologists have to do with their patients, not just in terms of clinician time but also in physical facilities. In this specific case, you need to engineer appropriate payer reimbursement for the procedure as part of your overall offering – the product itself is only part of your overall proposition.

Misconception 2: Business Model is Fixed Early On

Many bioscience startups see their business model as an important but one-time decision made quite early on. Founders feel under pressure early in their venture’s life cycle to select a business model that prospective investors can relate to and to which they can point to successful analogies in other companies. But the very definition of a startup (at least according to modern thinking) is an “organisation formed to search for a repeatable and scalable business model”. A classic mistake is to adopt an investor-friendly well-known business model without thinking through your own unique situation.

While there are “standard” business models that you might copy, you can gain added advantage by tweaking an established model to leverage some unique capability or intellectual property that only you have, your “unfair advantage” as some authors term it. For example, the traditional model for commercialising skills at evaluating drug efficacy is the contract research organisation (CRO) i.e. a fee-for-service provider. However, if your skills can create some tangible advantage for your customers, you can enter into value-added drug discovery partnerships where you share in the higher value created.

Furthermore, for many emerging life science technologies, there are no obvious historical models to copy wholesale. It may make more sense to implement a distinctive model of your own, while no doubt taking inspiration for some of your business model components from what other companies have done. It surprises me how many startups with technology platforms in say machine learning or molecular characterisation (genomics, proteomics, microbiome, etc.) default to being either a CRO, a software licensor or a drug discovery house. While these are well-known business models, I suspect in many cases the underlying technology platform is best commercialised with an optimal risk profile by doing something different, perhaps a hybrid of traditional models.

Your business model can and will evolve over time, as you improve your technology and operating model, take on board new customer insights, penetrate new customer segments and respond to competitors. You need to anticipate and drive this evolution. At the outset, given the initial state of your technology, delivery capabilities, financial balance sheet and early adopter customers, there may only be certain business model elements open to you. But as things evolve, and as you learn more about how your offering really affects customers’ buying and operating processes, you can and should adapt your business model proactively.

The process of dynamically evolving and honing your business model is well-documented in the software as a service (SaaS) sector, and even has a specific moniker, “customer development”, so-named in contrast to the more usual technical product development. In a bioscience domain such as new therapeutic discovery, the iterative development and refinement of an evolving business model is similar, although you will need to take into account additional scientific complexities such as determining the appropriate sequence of medical indications that your therapeutic candidate is developed for, as well as the more commercial aspects such as revenue from biopharma co-discovery partnerships. You will also need to consider what hard scientific evidence you might need to generate for customer decision-making and for the regulatory authorities.

The evolutionary deployment of a hybrid business model is aptly illustrated by the corporate development of the three most successful European antibody companies, Ablynx, Genmab and MorphoSys over the past 15 to 20 years. Each of these companies started as a technology licensing and service provider, then moving into drug discovery partnerships where they negotiated a increasing proportion of the ensuing therapeutic product revenue, eventually starting their own proprietary drug discovery programmes, and most recently beginning to develop their commercial capabilities for marketing therapeutics. In their journeys to become companies with multi-billion enterprise valuations, they proactively managed over time their balance of all these types of activity to optimise cash flow generation and risk exposure.


To summarise, your business model is not just about the commercial model. You also need to work concurrently on your customer proposition and your operating model, integrating all three aspects. And your business model is not just a static concept. You need to proactively evolve and adapt it over time to ensure sustained success.

An earlier version of this article was posted on Panacea Innovation’s Medium publication

Cover Picture by Arek Socha from Pixabay