Desirability, Feasibility, Viability: A Three-Part Test for Any Innovation Decision

When organizations try to innovate, one of the first challenges is separating an interesting idea from a real opportunity. A new product, a service, a technology, or a strategy may look promising at first, but innovation requires more than originality. It has to create value for someone, be possible to execute, and have a credible path to sustainability.

The same logic sits behind one of the most widely used ideas in design thinking, a structured approach to innovation that focuses on user needs, observation, and creativity applied to problem solving. Design thinking uses research and insights to inform design choices, and it treats innovation not merely as invention, but as the creation of something that is both novel and useful.

The second word matters. Novelty can make an idea interesting, but usefulness is what begins to turn an idea into an opportunity. Managerial research on how innovation actually happens in organizations highlights a similar tension. In The Innovator's DNA, Dyer, Gregersen, and Christensen find that the most productive innovators combine discovery behaviors (associating, questioning, observing, networking, and experimenting) with the delivery skills needed to execute and refine. Both capabilities matter, but they pull in different directions: discovery opens up possibilities, while delivery turns selected possibilities into operational reality. The risk is over-indexing on one side: endless ideation without execution, or rigid execution without questioning whether the idea still holds.

One way to keep both sides in balance before committing resources is to assess ideas through the desirability, feasibility, and viability (DFV) framework popularized by the global design and innovation firm IDEO. The DFV framework brings together what is desirable for people, what is feasible with technology, and what is viable for organizations.

1. Desirability. The first question is about the human dimension: Do people want or need this? Can consumers or users easily connect the innovation to their own needs, pain points, or aspirations? If the answer is no, the idea may be clever, but it solves a problem that nobody feels strongly enough to act on.
2. Feasibility. The second question is about execution: Can the organization produce or deliver it? Are the materials, technologies, capabilities, or processes available? Do laws and regulations allow it? An idea that users value but that cannot be built at acceptable quality or scale remains an idea.
3. Viability. The third question asks about endurance: Can we continue to produce or deliver this over time? Can we capture enough of the value we create to operate profitably or sustainably? Even desirable and feasible innovations need strong economics to persist and grow.

Together, these three characteristics form a screening system. Innovation teams use them to avoid three common traps: building something nobody asked for, chasing a vision that exceeds current capabilities, or creating a product that works but cannot survive financially.

DFV framework in therapeutic development

The development of new therapies is a clear setting where the DFV framework can be applied usefully. Unlike many innovation contexts, the path from scientific discovery to patient adoption is highly regulated, capital intensive, and evidence driven. A scientific idea may first appear as a target, mechanism, modality, platform, or therapeutic hypothesis, but that idea only becomes a real opportunity when unmet need, development execution, and long-term value can be considered together.

Alignment is never judged by one actor alone. A new therapy may involve patients, physicians, caregivers, regulators, payers, pharma partners, investors, clinical investigators, CROs, manufacturers, and sometimes diagnostic providers. The DFV framework gives biotech teams a practical way to organize those perspectives: desirability clarifies who needs the therapy and why; feasibility defines what evidence, capabilities, and regulatory path are required; viability tests whether the investment case can sustain the program over time.

Desirability: making therapeutic value visible

In the original DFV framework, desirability asks whether people want or need the innovation, whether users can connect an idea to their own needs, pain points, or aspirations.

The core desirability question in therapeutic development is whether the proposed intervention or concept addresses a problem that matters enough to patients, physicians, payers, regulators, partners, or investors.

Desirability is useful as an early strategic lens because it pushes teams to define the therapy in relation to the value it is expected to deliver. In drug development, many of those elements become more concrete when translated into a Target Product Profile (TPP), which connects the science behind the therapy with its intended clinical and strategic role: the unmet need, the target patient population, the current standard of care, the intended clinical use, the expected clinical benefit, the evidence requirements, the relevant adoption stakeholders, the reimbursement context, the conditions for access and uptake, and the therapy's differentiation and role in care.

In biotech, desirability requires a careful interpretation because stakeholder value is not uniform. Patients may experience value through symptom relief, survival, convenience, access, or quality of life; physicians through clinical benefit, safety, workflow fit, evidence quality, and confidence in patient selection; payers through budget impact, avoided downstream costs, and comparative value; regulators through endpoints, benefit-risk, and the strength of the evidence package; and investors or pharma partners through differentiation, scalability, development risk, and strategic fit.

The result is a more layered form of desirability than in many consumer innovation contexts. A therapy may address a real need and still require work before its value is broadly recognized. In some cases, the barrier is economic: price may be high or reimbursement evidence may still be insufficient. In others, the barrier is practical: diagnosis may be immature, physicians may need time to change prescribing behavior, patients may need better access infrastructure, or regulators may need a more mature endpoint strategy.

In crowded therapeutic areas, value recognition becomes even more dependent on clear segmentation and visible differentiation: a program may address a real market, but still fail to become attractive if its clinical, evidentiary, or access wedge is not strong enough for stakeholders to recognize. Read more on entering crowded target spaces →

Such frictions do not necessarily mean that the therapy lacks desirability. They often mean that desirability is conditional. A good development strategy can increase desirability by making therapeutic value easier to see, adopt, reimburse, and scale. A high-cost therapy, for example, may become compelling when it avoids years of chronic treatment, hospitalization, or disease progression. In oncology, biomarker enrichment can make an intervention more attractive by identifying the subgroup where benefit is strongest. In rare disease, diagnosis, patient concentration, and endpoint selection can shape whether the value of a program becomes visible to the stakeholders who need to recognize it.

In this sense, desirability in biotech is partly discovered and partly built: discovered by understanding the real unmet need, stakeholder priorities, clinical practice, patient journey, treatment burden, competitive alternatives, and reimbursement context; and built by generating the right evidence, selecting the right indication, defining the right patient population, designing a credible access strategy, and communicating value in a way that each stakeholder can recognize.

The DFV framework gives teams a disciplined way to treat desirability as a strategic question rather than a superficial market question. It should be used to ask:

• Who needs this therapy?
• Which patient population is most relevant?
• Where would the therapy fit in the current standard of care?
• What clinical use case would make the therapy meaningful?
• What benefit would the therapy need to deliver?
• Who decides whether it is adopted?
• Who pays for it?
• Who must change behavior for it to reach patients?
• What evidence would make the value clear?
• What conditions would make adoption easier?
• What development choices could strengthen stakeholder recognition of value?

Because desirability asks whether value can be recognized by real stakeholders, it can easily be misunderstood as a conservative filter: a reason to reject anything that is not already obvious, easy to adopt, or fully defined. That would be the wrong use of the pillar. In biotech, desirability should not act as an innovation killer. It should work as a strategic helper to understand what must be clarified, evidenced, enabled, or designed for a scientific opportunity to become clinically relevant, recognizable to stakeholders, and adoptable within the healthcare system.

For therapeutic development, desirability explicitly bridges the gap between the initial scientific concept and genuine healthcare relevance.

Feasibility: moving science through development systems

In biotech, feasibility brings the idea into the development world by defining whether the scientific opportunity can move through the systems toward treatment development.

Feasibility extends far beyond the molecule itself. It asks whether the candidate can be manufactured, formulated, scaled, tested, and delivered under real conditions. This dimension includes the full chain that moves a candidate from the laboratory to the patient:

1. Chemistry and biology. It means producing the candidate with the required purity, stability, and reproducibility. A compound that performs in vitro but cannot be synthesized with acceptable yield or formulated for human dosing may remain in discovery.
2. Manufacturing. Feasibility means scaling from micrograms to kilograms and eventually to commercial batches without unacceptable cost or risk. A biological process that succeeds at laboratory scale but cannot transfer to production scale changes the economics of the program.
3. Formulation and distribution. Feasibility means surviving real conditions including temperature ranges, shelf life, and compatibility with existing packaging and delivery systems. A therapy that requires complex logistics may be feasible only if the supply chain infrastructure exists or can be built affordably.
4. Clinical stages. It asks whether the intended patient population is sufficiently diagnosed and geographically accessible, the clinical sites can realistically recruit and retain participants with the required characteristics, and the biomarkers and endpoints can be measured with the required precision across the intended trial network.
5. Regulatory feasibility. It asks whether the preclinical safety package, the clinical trial design, the manufacturing documentation, and the overall evidence strategy will meet the standards of reviewing agencies. A development path that lacks clear regulatory precedent requires additional investment in dialogue and evidence to make the pathway predictable.

Across all five areas, feasibility is tested by the same practical question: can the candidate become a medicine under real operational constraints? An antibody with exceptional affinity becomes operationally challenging if its manufacturing process requires specialized equipment that no contract manufacturer can operate at the needed scale. A cell therapy becomes difficult to deploy if its dosing schedule depends on continuous hospital administration in a setting where bed capacity is limited.

The DFV framework is useful because it forces teams to make that chain visible early to identify which parts of the development path are already supported, which parts need stronger evidence, and which parts require specific technical, operational, regulatory, or manufacturing work.

For biotech teams, feasibility is not a static judgment made once at the beginning of a program; such a standard would leave very little room for real innovation, and many feasibility constraints are not permanent barriers. They are conditions that can be resolved with the right development choice or partnership. For example, a formulation challenge may be solved by changing the route of administration, or a patient recruitment constraint may be resolved by narrowing inclusion criteria to centers with established registries.

Other feasibility constraints depend less on a solvable development gap and more on timing. In some cases, the required materials, technologies, processes, or infrastructure are simply not available yet. This is especially relevant in emerging modalities, novel delivery systems, advanced manufacturing platforms, complex biologics, or technologies that depend on infrastructure still under development.

CRISPR is a clear example. Before programmable gene-editing tools became available, many gene-editing strategies were conceptually attractive but practically inaccessible. Once the technology matured, previously unrealistic therapeutic approaches became technically actionable.

Organoids and other New Approach Methodologies show a similar dynamic on the evidence side. As regulators become more open to human-relevant models such as organoids, organ-on-chip platforms, advanced in vitro assays, or computational models, programs that once depended almost entirely on animal studies may gain a more feasible evidence pathway for specific development questions.

When the missing condition is not yet available, the right decision may be to place the idea in a strategic parking lot: keeping it visible, periodically reviewed, and linked to specific triggers for reactivation, such as a new manufacturing capability or a validated analytical method.

Like desirability, feasibility is not only something a program either has or lacks. It can be assessed and built at the same time. Teams assess feasibility by mapping the technical, operational, regulatory, and manufacturing requirements that stand between the current state and the next decision point, and build it by reducing friction, eliminating single points of failure, and creating the capabilities, partnerships, or evidence pathways needed to advance.

Feasibility tests whether an innovation can survive contact with the execution systems that turn science into a treatment. When a gap appears, the useful response is to identify which condition is missing, whether it is fundamental or solvable, and what investment, partnership, design change, or timing trigger would close it. In some cases, the right decision is not to abandon the idea, but to keep it visible in a strategic parking lot until the missing condition becomes available.

Viability: connecting scientific progress to long-term value

In the original DFV framework, viability asks about endurance. Can we continue to produce or deliver this over time? Can we capture enough of the value we create to operate profitably or sustainably? Even innovations that users want and that teams can build need strong economics to persist and grow.

In drug development, viability is critical because the path from hypothesis to approval is extremely capital intensive, lengthy, and uncertain. A program can address a real need and clear technical hurdles but still fail if the economics do not hold. Viability asks whether the opportunity can sustain the cost required to reach the next inflection point, generate a return that justifies continued investment, and withstand competitive and reimbursement pressures once it reaches the market.

The assessment requires looking beyond the theoretical prevalence of a disease. The total addressable market on paper is not the same as the number of patients who will be diagnosed, eligible for the therapy, and covered by reimbursement at a price that supports the development cost. Viability requires an honest assessment of the practical market, the pace of adoption, and the barriers that limit access in real clinical practice.

It also requires an understanding of pricing power within the specific therapeutic area. A therapy may be scientifically differentiated, but if the reimbursement ceiling is low or if the pricing advantage is temporary, the program may never recover its investment.

Consider psoriasis, where the global market exceeds $21 billion and is projected to approach $40 billion by 2030. IL-17 and IL-23 inhibitors now dominate the standard of care, commanding annual per-patient costs of roughly $8,000 to $10,000 and growing rapidly. Yet this apparent revenue pool is under simultaneous compression: biosimilars have already demonstrated they can capture the majority of a reference product's volume within months of launch, and historical price drops in this class range from 20% to 40% once competition enters. In parallel, the average forecast peak sales for late-stage assets are only about $510 million. For a novel biologic entering psoriasis today without a target, mechanism, or efficacy profile that meaningfully exceeds the current IL-23/IL-17 standard, the gap between high risk-adjusted development costs and an attainable revenue ceiling becomes a structural viability constraint that operates before the product ever reaches a formulary committee.

Viability also depends on development economics. Even when the practical market and pricing logic appear attractive, the cost of late-stage clinical trials must be weighed against the probability of success at each phase, adjusted for the indication, modality, patient population, competitive intensity, and available regulatory incentives. A phase III program in a broad indication can consume capital and years of development while still facing uncertain approval, intense competition, and limited pricing power. By contrast, a phase II program in an orphan indication may offer a stronger economic profile than its small population suggests. Smaller trials, regulatory incentives, potential tax advantages, protocol support, market exclusivity, higher penetration, and premium pricing can reduce development burden and expand the profit window. The path requires confidence that the indication is truly orphan and that the premium will hold against future competition or policy changes.

Viability also includes competitive durability and timing. Patents provide a limited window of protection, and the competitive landscape can shift while an asset is still in development. A scientifically and clinically sound program may face economic failure if market dynamics change before launch, if a faster competitor captures the intended positioning, or if the remaining exclusivity window is too short.

As with desirability and feasibility, viability is not only assessed; it can also be constructed. Teams assess viability by mapping development cost, realistic revenue potential, reimbursement environment, timing, competitive durability, and remaining value window. They build viability through strategic choices that improve the economic profile of the program: narrowing the label, selecting an accelerated pathway, generating pharmacoeconomic evidence early, partnering at the right point, or redesigning the trial to reduce cost or time.

When viability reveals a gap, the practical response is to identify which economic assumption is failing and which strategic lever could change it, before defaulting to continuation or abandonment.

For therapeutic development, viability is the link between scientific and clinical progress and the long-term value needed to sustain the program.

Applying DFV as a biotech decision architecture

The value of the DFV framework is strongest when desirability, feasibility, and viability are assessed in parallel.

A biotech program can be scientifically compelling and still need a clearer clinical use case, a stronger execution path, or a more credible route to value. Looking at the three dimensions in parallel helps teams identify those needs early, while there is still room to adapt the development strategy.

When only two of the three pillars hold, the gap is rarely a reason to stop. It points to a specific strategic pivot, summarized below.

Before advancing a program into a major value-inflection stage, teams can use a simple test:

1. Desirability: Who will value this therapy, and why?
2. Feasibility: What must be produced, validated, scaled, documented, or operationalized to develop it?
3. Viability: What strategic, financial, or commercial logic supports continued investment?

The strength of a program depends on how clearly each answer can be supported by evidence. For biotech, desirability, feasibility, and viability become a practical decision architecture for connecting science, development, stakeholder needs, and long-term value.