Do academics and practitioners believe they have much to learn from each other?  If we look for evidence of meaningful exchange — shared conferences, the prevalence of journals that appeal to both groups, or just the quantity and quality of listening that occurs when both are in the same room — the answer appears to be “not much.”  Why is that?

Part of the reason likely turns on status.  The academy and practice have different reward systems, with little reserved for plowing the middle ground. Yet, what happens when two groups of smart people working on the same problem set effectively tune each other out, not necessarily out of disrespect, but just so they can finish what they perceive as their real work?

This post (026) offers some insight into this question. Post 026 also completes a three-part series on “Crossing the Chasm” and the “Hype Cycle” (two well-known practitioner frameworks) and is the final post in Legal Evolution’s foundational series on diffusion theory (something likely perceived as academic).

Posts 024-026 are the final installment of Legal Evolution’s foundational series on diffusion theory. Readers seeking to influence innovation within the legal industry will be more successful if they obtain and apply this background knowledge. Care has been taken to make this information non-technical and accessible.

In Part I (024), I wrote that it is important to understand Crossing the Chasm “from the perspective of Moore and his audience — i.e., as practical business advice being dispensed to entrepreneurs.” Now it’s useful to explore the full origin of these ideas.

Origins of Crossing the Chasm

During the 1980s, Geoffrey Moore was a partner at Regis McKenna, Inc., a Silicon Valley marketing firm. In the 15 years prior to Moore’s arrival, the firm’s legendary founder, Regis McKenna, had provided counsel to an extraordinary roster of technology start-ups that went on to become industry giants (e.g., Apple, Compaq, Intel, Lotus, Microsoft, National Semiconductor, Silicon Graphics, and 3COM).

According to the account given by Moore in Crossing the Chasm, the dominant business framework relied upon by the Silicon Valley start-up crowd was the Technology Adoption Life Cycle (see top graphic above).  Although there’s no reason to doubt Moore when it comes to Silicon Valley terminology, the Technology Adoption Life Cycle is, in fact, the Rogers Diffusion Curve (see second graphic above).

Although Everett Rogers is not cited anywhere in the first edition of Crossing the Chasm (or in the third edition published in 2013), Moore apparently had some vague knowledge of the model’s origins.  In the first chapter, Moore writes, “People are usually amused to learn that the original research that gave rise to this model was done on the adoption of new strains of seed potatoes among American farmers.”  (The underlying research involved mostly corn farmers, see Rogers’ 1958 article.) Moore continues, “Despite these agrarian roots … the model has thoroughly transplanted itself into the soil of Silicon Valley” (p. 11).

Ironically, the core thesis of Moore’s book is that the Technology Adoption Life Cycle model (aka the Rogers Diffusion Curve) contains a serious flaw.  Moore writes, “The basic flaw in the [Technology Adoption Life Cycle] model … is that it implies a smooth and continuous progression across segments over the life of a product, where experience teaches us the opposite” (p. 56).  Hence, Moore’s insertion of the chasm to create the “The Revised Technology Adoption Life Cycle” model.  See figure below.

In making this change, Moore was not the slightest bit burdened by the decades of empirical research that backed up the original model. We know this to be true from the acknowledgements at the beginning of the first edition of Crossing the Chasm.  Moore, who has a PhD in English Literature, writes:

Prior to the world of high-tech, I was in English professor. One of the things I learned during this more scholarly period of my life was the importance of evidence and the necessity to document its sources. It chagrins me to have to say, therefore, that there are no documents or summary of evidence anywhere in the book that follows. Although I routinely cite numerous examples, I have no studies to back them up, no corroborating witnesses, nothing. [p. xv]

If Moore has no awareness of the original source material, how was Rogers’ work transmitted to Silicon Valley? In fact, the most likely route is a textbook example of Rogers own theory in action.

In 1975, Everett Rogers joined the faculty of Stanford University, where he stayed for approximately a decade. During this time, Roger became interested in how the distinctive high-tech culture shaped the region’s business and academic norms.  Thus, Silicon Valley got incorporated into Rogers’ research. See, e.g., Rogers & Larsen, Silicon Valley Fever: The Growth of the High-Technology Culture (1984); Rogers, The High Technology of Silicon Valley (1985).

What seems likely is that the basics of diffusion theory, including the diffusion curve, were shared with some of Rogers’ research subjects and other professional acquaintances.  In turn, some — likely the innovators and early adopters —  applied Rogers’ ideas to the problems of high-tech marketing.  Because the diffusion curve proved to be quite useful, it was shared throughout Silicon Valley’s “social system” as the Technology Adoption Life Cycle, a title that fit its purpose.

Several years later, Moore, reflecting upon his experience and desiring to communicate a strategy that (a) his clients could understand, and (b) would cause them to avoid financial ruin, came upon the chasm as a better description of his clients’ core dilemma.  Ironically, this adaption of Rogers’ own ideas is what diffusion researchers call “re-invention.”  See Diffusion of Innovations 180 (5th ed. 2013) (defining re-invention as “the degree to which an innovation is changed or modified by a user in the process of its adoption or implementation”).

Eventually Moore’s re-invention came to Roger’s attention. In the fifth edition of Diffusion of Innovations, Rogers writes:

The five adopter categories … are ideal types, conceptions based on observations of reality that are designed to make comparisons possible. … Pronounced breaks in the innovativeness continuum do not occur between each of the five categories, although some scholars claim that a discontinuity exists between the innovators and early adopters versus the early majority, late majority, and laggards (Moore, 1991). 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[.] (p. 282).

As an academic, I understand that the chasm is not supported by data.  Yet, as someone who spent several years in a data analytics start-up company, I know there is a second question worth asking–is there benefit in having the team believe there is a chasm so, in an effort to avoid it, we adopt a laser-like focus on endusers very different than us?  The answer, of course, is yes. See Parts I-II (024025).

Theory and Practice

As I describe the origins of the Technology Adoption Life Cycle and the chasm framework, I hope it is obvious that I am not passing judgment on Geoffrey Moore or his Silicon Valley peers. In fact, the opposite is true.

Crossing the Chasm has sold 300,000+ copies because it addresses an important problem — generating sufficient sales before start-up funds are exhausted — in a lucid, non-technical way that is loaded with industry context.  It is noteworthy that solving important problems in a simple, culturally compatible way is the precise advice that flows from Roger’s empirical work. See Post 008 (listing high relative advantage, low complexity, and cultural compatibility as key factors in rate of adoption). In fact, the guidance provided by Crossing the Chasm is remarkably consistent with Diffusion of Innovations.  This is a testament to Moore’s powers of observation and his effectiveness as a business counselor.

Yet, does Moore’s example prove that practitioners have little to learn from academics? Or, stated another way, that the most valuable lessons have to be learned in the trenches and communicated as business lore? I am skeptical of this claim, particularly as it applies to lawyers.  If the slow pace of innovation is now threatening the viability of our organizations and the legal profession as a whole, we don’t have time to sort out whose “more practical” ideas to follow or, for that matter, whether any of them really work.  Instead, we need to seek out valid, reliable data.

The attenuated connection between Rogers (a university academic specializing in applied research) and Moore (a marketing practitioner) illustrates a tension experienced by those of us “in the field” doing either applied research or working as change agents.  Applied research is generally not esteemed by university colleagues, primarily because it’s viewed as problem-solving (what practitioners do).  University professors are supposed to create knowledge.  See Post 001.  Yet, among practitioners, the work of applied researchers is often perceived as too academic and a distraction from keeping a paying client happy. As a result, the middle ground tends to be pretty barren.

It’s a long journey from pure university research to innovations that can be packaged and sold to demanding private sector clients at a profit. That journey is made longer, however, because people in different camps are reluctant to invest the time to listen to one another, as it takes effort to overcome communication and cultural gaps. See Post 020 (discussing challenges of change agents).  The great psychologist Amos Tversky once quipped, “The secret to doing good research is always to be a little underemployed. You waste years by not being able to waste hours.” Michael Lewis, The Undoing Project (2016) (quoting Tversky).

Innovation is advanced when disparate social systems–like Rogers’ and Moore’s respective professional networks–remain connected with one another. Although the information exchanges will tend to be more cognitively taxing than exchanges with peers, the resulting insights justify the effort. See Post 020 (noting that innovation travels through “weak ties” on the social system’s periphery with innovators and early adapters serving as connectors). In the case of Rogers and Moore, the contact was incidental rather than planned. Nonetheless, the power of the underlying ideas was sufficiently great to leave an indelible mark on the high-tech industry.

Nothing left to chance

As this is the last post in Legal Evolution’s foundational series, I’ll reinforce what I hope is an obvious point–in the year 2017, none of this needs to be left to chance. There is a well-developed science of innovation diffusion. As we struggle with the many problems created by lagging legal productivity, see, e.g., Post 006 (discussing  how lagging legal productivity is affecting court systems and the demand for law grads), we can use diffusion theory — and Geoffrey Moore’s brilliant metaphorical conceits — to accelerate the adoption of innovation. Further, we can do it at a lower cost and with significantly less risk.

The price of admission is investing the time to learn a seeming academic theory. Many of your colleagues will think this is a dumb and impractical use of their time, albeit they don’t see the world through the eyes of an innovator or early adopter. As a result, these difficult problems / opportunities fall to people like you.

Back to the Hype Cycle

I’d like to end the foundational series by looking at emerging technology not from the perspective of an entrepreneur trying to turn a technology into a successful business, but as a buyer evaluating a confusing landscape of emerging technology and trying to sort out what is strategic (potentially affects my company’s survival) versus operational (potentially affects my bonus). This is what IBM used to call the FUD factor — the fear, uncertainty, and doubt that surround high-stakes decisions on relatively new and unproven technology.

Managers and executives struggling with the FUD factor have long looked to Gartner’s annual Hype Cycle of emerging technologies.  See Part I (024).  As shown in the figure to the right, the Hype cycle is divided into five stages, which Gartner describe as follows:

  1. Innovation Trigger: A potential technology breakthrough kicks things off. Early proof-of-concept stories and media interest trigger significant publicity. Often no usable products exist and commercial viability is unproven.
  2. Peak of Inflated Expectations: Early publicity produces a number of success stories — often accompanied by scores of failures. Some companies take action; many do not.
  3. Trough of Disillusionment: Interest wanes as experiments and implementations fail to deliver. Producers of the technology shake out or fail. Investments continue only if the surviving providers improve their products to the satisfaction of early adopters.
  4. Slope of Enlightenment: More instances of how the technology can benefit the enterprise start to crystallize and become more widely understood. Second- and third-generation products appear from technology providers. More enterprises fund pilots; conservative companies remain cautious.
  5. Plateau of Productivity: Mainstream adoption starts to take off. Criteria for assessing provider viability are more clearly defined. The technology’s broad market applicability and relevance are clearly paying off.

What makes the Hype Cycle so tricky for law firms is that some of the technology coming online is not operational IT that can be safely put off until stage 5. Rather, it’s “discontinuous innovation” that has the potential to fundamentally change how legal problems are solved–hence the growth in the number of legal start-ups and NewLaw companies who see the opportunity. This suggests that there are real consequences to arriving late to the party.  These dynamics move law firms closer to their clients in terms of needing to continuously innovate. See, e.g., Fragomen to Launch Unique Tech Development Center in Pittsburgh, Corp. Counsel, July 3, 2017 (quoting legal industry expert, “Every company is going to become a tech company in some capacity. That ultimately is going to be true of professional service firms and law firms as well.”). This is a sea change that is steadily gathering force.

This is the end of Legal Evolution’s foundational series on diffusion theory.  I hope you have found it a valuable use of your time.  Going forward, Legal Evolution’s commentary will be much more focused on examples.  To the extent we need theory, we’ll have these foundational posts to refer back to.

Bill Henderson, Editor, Sept 2017

What’s next?  See A Successful Legal Change Management Story (027)