Don't Get Confused About Crossing The Chasm

After speaking with several hundred business leaders we've observed there are extreme variations when we talk about Crossing The Chasm. In this article, we share the sources that are driving so much chasm-crossing confusion to help leaders avoid it.

Warren Schirtzinger

Strategy Lead

Chasm-Crossing Confusion: Why the Concept of a Gap in the Technology Adoption Lifecycle is so Widely Misunderstood

In my work with CEOs and their teams in high-tech and cleantech companies, I am constantly surprised by how many people misinterpret the concept of a chasm in the innovation-adoption curve.

And after speaking with several hundred business leaders, investors and product/marketing professionals across multiple industries, I find there are extreme variations when I ask what is required to “cross the chasm.”

As a result, I became convinced that something had gone wrong. So, I decided to find out why there was so much chasm crossing confusion.

Research Method

I started by analyzing 250 of the most-frequently visited websites that summarize Crossing the Chasm or talk about the chasm concept. This process allowed me to determine how accurately various writers, analysts, business experts and thought leaders understand the concept of a gap in the technology adoption lifecycle and what causes it.

Using a tool called Ubersuggest (by Neil Patel) I identified the 250 most popular websites/articles and then I read each one to evaluate the author's level of understanding, and rate the article's accuracy. As you will see below, the results are not good.

Sources of Mass Confusion

Before listing the six areas of greatest confusion, it is important to mention three things that have been working against the chasm concept for a long time.

Source of Confusion #1: Lack of support from Everett Rogers

One of main reasons, I believe, the misunderstanding of the chasm concept is so widespread is the various differences of opinion that have been expressed over the years regarding the validity of the chasm model.

For example, Everett Rogers, the author of Diffusion of Innovations -- and the reference point for all discussions about how innovations are adopted -- clearly stated that in his opinion there is no chasm.

Rogers is quoted as saying "Past research shows no support for this claim of a chasm between certain adopter categories. On the contrary, innovativeness, if measured properly, is a continuous variable and there are no sharp breaks or discontinuities between adjacent adopter categories (although there are important differences between them).”

Paula Gray, co-founder of the Association of International Product Marketing & Management (AIPMM), did an excellent job of summarizing Rogers' critique of the chasm concept in her article: It’s Not a Chasm; It’s a Continuum

When the original creator of the innovation-adoption curve (and the person who coined the term “early adopter”) says there is no such thing as a chasm, it creates a platform for confusion, uncertainty, doubt and misunderstanding.

Source of Confusion #2: A picture is worth a thousand mistakes

Another source of ongoing confusion is the common use of a diagram -- initially created in 1993 and in widespread use since 2009 -- that implies early adopters are on BOTH sides of the chasm.

When it was originally defined, the chasm concept described a gap in the innovation-adoption curve that is located between early adopters and the mainstream early majority. Yet the diagram below communicates a different structure, and also inflates the size of the early majority.

No alt text provided for this image
created by an unknown graphic designer in 1993

A reverse image search reveals this erroneous representation of the innovation-adoption curve (with early adopters on both sides of the chasm) is found on at least 279 different websites, with initial use dating back to 1993.

This incorrect image is also displayed on Wikipedia, where it creates confusion for anyone who might be looking for definitions related to Crossing the Chasm. [https://prnt.sc/sT1vSgkqHySQ]

If a picture is worth a thousand words, then this commonly-used diagram is causing confusion regarding the actual location of early adopters and the role that they play.

Source of Confusion #3: Let’s get disruptive

In 1997 Clayton Christensen published The Innovator's Dilemma, and the business world became obsessed with the concept of “disruption.”

Yet Christensen’s unique definition of a “disruptive innovation” created tremendous confusion…which ultimately fueled some of the misunderstanding I see when people speak about the chasm.

Christensen defined a “disruptive innovation” as a process by which a product or service takes root initially in simple applications at the bottom of a market and then moves up market, eventually displacing established competitors.

Christensen’s definition is in stark contrast to the definition of a “discontinuous innovation,” which is a new product, service or platform that requires new experience, understanding and learning to be able to be used properly, and in the process creates a chasm.

In the standard-definitions section of the Financial Times, it states that before Christensen’s book, discontinuous and disruptive meant exactly the same thing!!

But not anymore.

No alt text provided for this image
screenshot courtesy of The Financial Times

The problem with the term “disruptive innovation” is that it now has multiple meanings, and Christensen’s new definition is being applied incorrectly to the chasm concept.

The Top Six Areas of Chasm-Related Confusion

Sadly, this research project reveals that 90% of the top-ranked, chasm-focused articles, blog posts, essays and book reviews on the Internet contain at least one of the errors or mistakes listed below. And most of these popular sites contain multiple errors.

I’ve also attempted to get everyone back to a basic level of understanding by explaining each mistake and correcting them.

1. Mischaracterizing an innovation

Many articles incorrectly state "every innovative product starts as a great idea that attracts innovators and early adopters." In reality the starting point of an innovation is determined by the category of the new product, idea, method or concept.

And there is a big difference between a novel innovation (i.e. something no one has ever seen before) and a simple refinement. In fact, the majority of all new products are refinements, which implies they are already in the mainstream, and there is no chasm.

This issue was made even worse when the phrase “disruptive innovation” arrived on the scene in 1997. (see Source of Confusion #3 above)

2. Believing the chasm only applies to startups

The chasm concept offers decision-making guidelines for investors, engineers, enterprise executives, business managers and entrepreneurs throughout the high-tech community.

It isn’t just for startups. Established companies or “incumbents” are able to develop novel innovations too.

The question to ask is: does a new product or innovation require a new experience, new understanding or new learning to be able to be used properly? If the answer is “yes” then there is a chasm and it doesn’t matter who created it.

3. Thinking that applications and technologies are the same thing

The innovation-adoption curve (with or without a chasm) only applies to applications, and NOT to technologies.

This mistake is spread by many sources, not just websites and articles. You’ve probably seen a headline that says “XYZ research company reports that AI is considered mainstream technology in most companies.” This is a full-scale misinterpretation of the innovation-adoption process.

Mainstream adoption is only valid if it is tied to a specific category or application. For example, if a majority of hospitals in a geographical area use remote patient monitoring (RPM) for diabetes patients, it does NOT mean that RPM has crossed the chasm. It means that only one application of RPM has crossed the chasm. Other applications of RPM must be evaluated individually.

Keep in mind that Diffusion of Innovations and the original innovation-adoption curve were based on a specific application: the “use of hybrid seed corn by farmers in Iowa.”

4. Assuming psychographics are static or people stay in one category

Perhaps the most persistent mistake is that authors describe psychographic profiles based on a single application. In reality, people do not stay in the same category of adoption.

Just ask my neighbor. He is an early adopter of electric vehicles, but a laggard when it comes to a biological innovation called the COVID vaccine (which he refuses to accept).

This misunderstanding might come from the trendy, over-hyped use of “personas” that has plagued the high-tech sector for years. But there is no such thing as a person who is an early adopter of all new innovations. People self-select their adopter category for each new product or innovation they encounter.

Labeling a person or an organization as a known early adopter is a recipe for failure. Because it is always situation specific.

5. Applying chasm theory to low-cost consumer products

Chasm theory was originally developed to address the needs of emerging high-tech companies. And more specifically, it was created for high-risk or high cost technology-based products that require new learning or a change in behavior.

Any mention of low-cost consumer items crossing the chasm indicates substantial confusion and misunderstanding.

6. Assuming chasm theory applies equally well in all industries

Chasm principles are more difficult to apply in certain industries, such as renewable energy and cleantech. The psychographic sequence that is the foundation of the chasm concept (innovator - early adopter - early majority - late majority - laggard) can be substantially skewed by government or utility programs designed to encourage or accelerate adoption.

And in some cases, government subsidies or programs completely overwhelm the innovation-adoption process. A comprehensive, subsidized program can reduce the perception of risk to such a degree that mainstream customers adopt before they normally would in a purely commercial setting or market.

On top of the inherent difficulties of measuring localized, psychographic behavior, you must factor in the effect of public policy and incentives, which act to completely alter market dynamics.

Conclusion

What we have today is an epidemic of misunderstanding. And the six areas identified above create the greatest amount of confusion.

It’s disappointing to hear so many “experts” interpret basic chasm concepts incorrectly. These errors propagate through thousands of unsuspecting executives, managers, founders and entrepreneurs.

When business leaders and executives decide to use a model or framework for strategic guidance, the model needs to be crystal clear. Any ambiguity can lead to serious loss or delay of revenue. And the lack of understanding identified in this research project may explain why B2B tech companies often take a decade or more to build a profitable revenue stream.

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