Accelerating Medical Innovation Adoption Across the Curve

The life sciences sector faces a unique set of challenges that distinguish it from other industries. While the clinical value of an innovation is undoubtedly important, the market's acceptance hinges on a broader set of criteria. The evidence indicates that success requires a strategic approach that explicitly addresses the systemic, financial, and behavioral complexities inherent in the healthcare ecosystem. This means that proving if the technology works clinically is only one part of the equation; equally vital is demonstrating how it integrates into existing workflows, provides tangible and justifiable economic benefits, and secures the buy-in from a diverse array of stakeholders. The overarching challenge for life science companies is fundamentally one of market integration and value realization, extending far beyond mere product development. By understanding the unique motivations and barriers of each adopter segment, life science companies can optimize resource allocation, build trust, and establish their innovations as the new standard of care, ensuring enduring market success.

Before going further, let us define the term adoption. For the purposes of this paper, we define adoption as the psychosocial process by which individuals or organizations accept, learn, adapt to, and use novel technologies. We talk about adoption as unique from market share. Adoption refers to a category, share is comprised by the brands purchased or consumed within the category. Everett Rogers describes several product attributes influential in the process of adoption:

1. Relative advantage over existing technologies: if an innovation is not meaningfully superior to existing technologies in use there is no reason to make a change.

2. Complexity: the more complex the innovation is, the more difficult it will be to gain market traction. Optimally, the innovation will simplify an already complex process.

3. Compatibility with current practices: the more the innovation fits into existing workflows and practices the easier it is for individuals to adopt.

4. Trialability: How long will it take for me to see the results of trying the innovation? The quicker I can evaluate the results, the faster I can decide whether to adopt.

5. Observability: Social contagion effects are accelerated to the degree that there is high visibility of other individuals who have adopted an innovation.

Rogers goes on to describe five personas that comprise the individuals adopting a given innovation through time:

Innovators tend to think “outside the box”, embrace new ideas, and have a high risk tolerance

Early adopters tend to be aware of the need for change and are comfortable adopting new ideas

The early majority tend to be thoughtful and deliberate, adopting after they see the success of others

Late majority tend to adopt as a function of social influence (contagion)

Skeptics (he calls this category as “laggards”, but I like this term better) tend to be suspicious of innovations, have very low risk tolerance and tend to rely on traditional products or methods until they are no longer available

Each of these personas are “at play” to differing degrees through time, as depicted in Figure 1.

The key to accelerating adoption lies in the strategic imperative of addressing each of these personas at the right time with the right product and the right messaging. The interplay between product factors and human factors create each innovation’s adoption “signature”.

While there are many authors in the technology adoption space, another is worth mentioning here. In his book, “Crossing the Chasm”, Geoffrey A. Moore argues that marketing strategies that are effective in driving adoption in the early market are likely to fail when trying to attract the mainstream market. He defines the chasm as the gap between visionary early adopters and the more pragmatic market majority (see Figure 2). He says marketers must:

1. Target an initial niche market

2. Provide a complete solution to the needs of that niche market

3. Clearly position your product relative to competing products

4. Build a strong supply chain

5. Message consistent with a more pragmatic, less innovation driven audience

Figure 2: Moore's Chasm

In his seminal work, Frank Bass describes a mathematical model of new product adoption, often (but not always) depicted as an s-shaped cumulative curve. The parameters driving the equation are maximum adoption (in the full realization of time), the percentage of individuals who will adopt as a function of direct marketing, and the percentage of individuals who will adopt as a function of social contagion. It is an excellent fit for quantifying the phenomenon described by Rogers and Moore. Modeling adoption against different strategies for product fit, timing to market, and various persona-focused activities (along with their respective budgets) can be a powerful tool in optimizing strategic direction and articulating value. Coupled with risk analysis and advanced analytics modeling is one of the more powerful tools in the strategic marketer’s chest. I will address the more technical aspects of modeling adoption in a separate work meant for the builders of market models.

Strategic Considerations Across the Curve

I’ll focus the rest of the discussion on strategies to address the unique characteristics of adopting groups through time.

Innovators: innovators tend to keep apprised of new technologies and developments. You may very well engage these individuals in the pre-commercial stages of development through publications and updates. They may even participate in product design or clinical trial administration and become “pre-commercial adopters”. Innovators are often thought of as key opinion leaders (KOL’s) who may be engaged to speak at conferences and professional society meetings regarding the innovation. Innovators can be catalysts to prime the pump for the early adopters.

Early adopters: early adopters tend to be aware of unmet needs and shortcomings of existing technologies. While the product attributes described above apply throughout the adoption process, messaging around meeting the unmet needs and relative advantages over existing technologies will entice this group to try the innovation to see if the “promise” is realized. To the degree that they do perceive value, they accelerate the process of social contagion.

Early majority: these individuals are hearing about the success (or not) of their early adopting peers. Reaching this group requires visibility of the experience of early adopters, who may be engaged for presentations and poster displays at conferences and professional societies. Presenting case studies focused on improved clinical outcomes and/or process efficiencies as evidence of the product performing as described may be very useful here.

Late majority: This group is highly influenced by prior adopters and is driven mostly by social contagion factors. Messaging here should involve comparative advantages to existing technologies, the high satisfaction of prior adopters and case histories to illuminate the advantages, clinically, procedurally and financially. These individuals will adopt as a function of reduced perceived risk in these areas due to the evidence produced by the earlier adopters.

Skeptics: these individuals will be the last to adopt due to a “if it’s not broken, why fix it” thought process. They have had a long commitment to “tried and true” technologies and historical gold standard treatments. Messaging to these individuals should focus on the novel technology becoming the standard of care, supplanting prior art.

While this is not intended to be a comprehensive coverage of the topic, it does address the notion that strategic marketers will benefit from understanding the product attributes and adopter attitudes toward innovations are the underlying force behind the all-familiar adoption curve.

At Applied Data Sciences, Inc. we are a strategic advisory for market analysis, market modeling & simulation, strategic planning, value articulation and funding. Please reach out if you would like to learn more.

Michael Kubica is President of Applied Data Sciences, Inc. He is a specialist in strategic planning, risk analysis, market modeling and valuation for novel medical technologies. He has over 20 years experience in helping organizations set strategy, articulate value and get funded. Feel free to connect for more content like this article: linkedin.com/in/makubica

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