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Innovative products and services feel magical to the user. To create that feeling, however, innovation teams must grind through lots (and lots) of work. Fortunately, we have a playbook.


The core insight embedded in Rogers Diffusion Curve is that the adoption of new ideas occurs in a specific order through a social system comprised of five distinct segments. See Post 004 (introducing diffusion curve); Post 007 (explaining adopter types). Rogers’ research eventually found its way to Silicon Valley and got relabeled the Technology Adoption Life Cycle. See Posts 024026. Along the way, technology marketer and consultant Geoffrey Moore added a key modification: a material gap, or “chasm”, between early adopters and the early majority. If a company can “cross the chasm”, commercial success becomes inevitable, as sales then occur largely through a social process of one peer imitating another.

To boil it down, Rogers proves out the science, while Moore provides the playbook. This one-two punch dramatically increases the odds of successful innovation adoption. But let’s keep it real: This is a lot more work–and deeper thinking–than law firms are used to.

One of Moore’s most useful adaptations to Diffusion Theory is the use of buyer personas to correspond with each adopter type. Moore’s book Crossing the Chasm is peppered with many detailed narratives about the trials and tribulations new product teams encounter in their efforts to sell to each persona/adopter type.  The persona approach is a profoundly powerful way to design a product or service offering that the target end-user finds irresistible.

Below is a summary of how to apply Moore’s buyer personas to the legal market.

1. The Early Markets, Where Things Often Go Swimmingly

In his discussions, Moore provides a practical description of a functional job each adopter type tends to perform in the diffusion process. This post draws heavily on Chapters 2 and 3 of Crossing the Chasm, but with particular emphasis on Early Adopters and the Early Majority.

Innovators / “Techies”

Techies often embrace the nuts and bolts of how stuff actually works. Over time, Techies tend to amass a wealth of technical knowledge through self-initiated and self-sustained study.

In its earliest days, an innovation needs social proof to validate not only its novelty but its objective superiority. Moore describes Techies as “the gatekeepers for any new technology… the ones everyone else deems competent to do the early evaluation” (p. 39).

Of all five adopter types, Techies have perhaps the most straightforward and unambiguous job: to curate and assess new technologies or methodologies and endorse those with true technical superiority over currently available alternatives.

Early Adopters / “Visionaries”

Visionaries have both the imagination to see the world as it could be rather than as it is and the ambition to try to make those possibilities the new reality. Curious and ambitious, they gravitate toward high-impact, high-visibility roles within organizations. Along the way, Visionaries often gain access to significant discretionary budgets earmarked loosely for “strategic initiatives.”

The innovation function of the Visionary is easily described but exceedingly difficult to perform. Visionaries match emerging technologies or new ideas with systemic opportunities to drastically reshape existing markets. In other words, they identify business opportunities for a strategic leap forward. This requires not only an already rare combination of innate traits (curiosity, risk tolerance, openness to new ideas) but also an asset acquired over some years of experience: deep domain expertise in a specific industry.

“Huge, if true”

In the parlance of renowned venture capitalist Marc Andreesen, the most ambitious and canny Visionaries find and bet on ideas that will be “huge, if true.” Their work looks and feels nebulous because it is.

Moore’s critical insight here is that Visionaries balance risk against reward: they must perceive reasonable potential for significant breakthroughs to justify the risks attendant in sponsoring new ideas. To the uninitiated, Visionaries are regularly seen signing irresponsibly large checks to sponsor the development of murky endeavors that are often nothing more than a doodle on a whiteboard. The gift of vision enables this group to see the possibility of what Moore calls “order-of-magnitude” returns in the competitive positioning of their business (p. 44).

Given the stakes, Visionaries present as the least price-sensitive adopter type, and money is usually not the type of capital that is top of mind for them.  Rather, they tend to hold their reputations and political capital at a higher premium. As a buyer group for new products or services, Visionaries like to structure deals into pilot projects, replete with milestones and other signifiers of measurable progress. The perception of smooth progress toward tangible “wins” is critical for Visionaries to maintain not only their social status but also their professional standing.

Techies + Visionaries Make Unlikely 💖 Pairings That Make Perfect Sense

At first blush, Techies and Visionaries tend to look and sound quite different, and the collision of their two worlds often take casual observers by surprise.  Many Techies are self-proclaimed nerds who dig deep into their chosen area of interest. Visionaries tend to be well-connected individuals who travel far and wide, always in search of a new idea that will spark their next “initiative.”

But the natural affinity between these two types is quite easy to understand when viewed through the lens of shared values.  Both groups seek new things, though for purposes that are quite different in both behavior and motivation.

Techies and Visionaries each provide an invaluable service by performing key jobs that advance the goals of the other. Techies willingly volunteer their time, effort, and expertise to curate and test new offerings, but they often lack the social and professional standing to make things happen. Visionaries are big thinkers who share the Techies’ future-orientation, but with the upwardly mobile executive’s knack for imposing their goals onto the agendas and budgets of a well-resourced organization.

Thus, Techies and Visionaries tend to form symbiotic relationships that provide mutual benefit and fulfillment. Perhaps because of this unusual affinity, innovations that target Techies and Visionaries in the correct sequence are able to build impressive traction in early markets.

2. Into the Chasm, Where Things Get Dicey

When Bill first introduced the five adopter types, he had this advice to offer: “If you want your innovation to be adopted, don’t waste time trying to convert the early majority, late majority, or laggards. You only have one audience that matters – early adopters.” Post 007.

This is excellent advice. The work of taking innovations off the paper, out of the lab and into the real world requires the successful penetration of early markets.  In these early days, Visionaries are crucial to the innovation effort because they perform critical jobs for which they are uniquely equipped.

But why do so many innovation initiatives stall in the chasm, even with the support of the Early Adopter?

This is a critical question for our industry. See Post 051 (positing that the true bottleneck in legal innovation is a commercialization gap). The latest Altman Weil survey of law firm leaders reports that 38.3% of firms are actively engaged in creating special projects to test innovative ideas or methods – down from 50.4% in 2017.  While the decline is concentrated in smaller firms, the dip in experimentation suggests that the chasm threatens to dampen the overall pace of innovation in legal markets.

If you hope to scale innovation beyond experiments in the lab, understanding the psychographic (the “why”) and functional (the “how”) dynamics around the chasm is a must. An examination of the often fraught relationship between the Early Adopters and the Early Majority who bookend the chasm is particularly instructive.

Simply put, the chasm exists because the buying criteria and performance expectations of these two groups are so dramatically different. These very differences form the crux of why Early Adopters make poor reference clients for the Early Majority.

The perpetual tension between Visionary Early Adopters and the Pragmatist Early Majority stems from many dispositional differences, but there is one factor that we must always keep in mind. Despite the best of intentions and the best of efforts, the Visionaries’ bets do not always pay off. The hoped-for “order of magnitude” returns fail to materialize, and the new idea, product or service is found insufficient to catapult the innovation sponsor ahead of the competition.

In these unfortunate instances, it is often a Pragmatist, not the Visionary, who sounds a quiet death knell for the innovation experiment.

3. Pragmatists Hold the Keys to the Mainstream Markets

When David Cambria, the Director of Global Legal Operations at ADM, and Jeff Carr, the General Counsel of Univar, talk of “massive passive resistance,” or MPR, they are describing the attitudes of mainstream markets.

No single person or segment among the Early Majority, Late Majority, or Laggards holds nearly as much influence or prestige as the Techies or Visionaries who comprise the early markets.  All the same, the mainstream markets derive massive power from massive numbers – and their passivity actually makes them more intractable. They are hard to understand because they are not as vocal or as distinctive as the early markets, and markets that are not well understood are hard to penetrate.  Unfortunately, the failure to understand 85% of the target audience usually portends a slow but certain death for any new process, product or service.

Techies and Visionaries are united in their continual quest for new things, but mainstream markets are equally unified in the opposite direction.  The vast majority of B2B buyers do not care for novelty. Rather, mainstream markets generally seek proven, complete solutions to known problems. Lack of clarity on either side of the problem-solution equation usually translates to substantial costs to educate the market. Within each organization, change agents also must contend with the costly battle against legacy infrastructure and cultural antibodies reinforcing the status quo.

Early Majority / “Pragmatists”

Pragmatists tend to gravitate toward roles of responsibility and stewardship in sizable corporations and in professional communities.  Hence, Pragmatists are often the de facto keepers of the core company budget as well as industry standards and best practices.

According to Moore, the “Fortune 2000 IT community, as a group, is led by people who are largely pragmatist in orientation” (p 55). We can easily envision how this type would dominate positions of authority across legal functions of the same companies, and the description fits reasonably well for practice group or industry group leadership roles across NLJ 500 law firms.

An Advanced Exercise in Empathy

As a buyer group, Pragmatists are practical, stringent and value-conscious for entirely rational and comprehensible reasons.  Early markets opt into their innovation roles, but Pragmatists have their responsibilities thrust upon them.  Pragmatists are the ones usually held internally accountable for building, integrating, testing, debugging, and maintaining a new reality but at realistic levels of cost and effort – all while supporting their entire organization as it is nudged and prodded through all the unpleasantness of learning a new way to work.

For the would-be entrepreneur or intrapreneur, the skeptical demands of Pragmatists throw cold water on all the dreams nurtured by early market success.  For that reason alone, an “extended exercise in commercial empathy” for this group’s point of view can feel very taxing.  We often find it easier to vilify Pragmatists as unimaginative, plodding, and ornery – for the simple reason that they stand towering like an impassable mountain range between us and all our innovation dreams.

(For an illuminating glimpse at the world through the viewpoint of a Pragmatist, set aside some time to at least skim through the narrative vignettes in “What is Code?” – an award-winning 38,000-word showpiece on Bloomberg Businessweek.)

Innovations Start Life As Hypotheses, and Hypotheses Need Testing

Visionaries craft many scenarios about what the future might look like, but it is the Pragmatists who ultimately decide what the future actually will be.  Pragmatists derive this considerable power not from glamorous positioning and self-promotion, but rather from the distinctly unglamorous work of safeguarding their organizations against catastrophic system failures and irresponsible budget leakages.

Along the way, Pragmatists provide an invaluable service not only to their own organizations but also to the innovation teams who listen with the intent to understand.  Visionaries deal in the murky realm of intuition and hunches, but Pragmatists are the keepers of cold hard truth.  And cold hard truth is what we need when we tackle one thorny question after another to validate the Visionary’s plausible theories:

  • Are we addressing a business problem that matters?
  • Does this problem matter to a market of sufficient size?
  • Have we built a complete product that solves enough of the problem?
  • Does our offering solve the problem more effectively than any other available option?
  • Can we deliver sufficient business value to justify not only our asking price but the total cost of adoption and use?
  • Does our offering actually work reliably and for real users in the real world?
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Asking and answering these questions in an evidence-based manner demands extraordinary emotional discipline. The interest of early markets, no matter how exciting, is necessary but insufficient proof. The true test of market viability is forged through the exacting requirements of Pragmatists.

Prior to crossing the chasm, the Pragmatist’s buying requirements present material barriers to further diffusion:

  • insistence on a whole product solution
  • reliance on peer references from other Pragmatists
  • penchant for backing the market-leading solution
  • attention to practical deployment levers (e.g. infrastructure compatibility)

However, the innovation teams able to meet these demands find themselves well positioned to capture market share quickly. And the innovations that survive these trials are often imbued with an invaluable attribute of mainstream success: scalability. Lastly, because Pragmatist are fiercely loyal once won, the innovation team can expect to enjoy a highly defensible competitive position.

4. Even In A World of No, There Are Lessons To Be Had

The Late Majority and Laggards do not feature as prominently in our narrative. Legal innovation is not yet mature enough to grapple seriously with the market extension opportunities offered by these adopter types, who are generally resistant to trying new things.

Still, we append a few remarks. Despite the best efforts of innovation teams to convert each of the adopter types in the prescribed order, the messy and chaotic nature of legal markets all but guarantees that we will encounter all adopter types in our quest for market entry.

Late Majority / “Conservatives”

Risk aversion, price sensitivity, and tendency to follow rather than lead are the identifying characteristics of Conservatives. Whereas Pragmatists seek demonstrable gain in a defensible cost-benefit analysis, Conservatives in legal ecosystems are more likely seek minimal pain in their individual buyer and user experiences. This has the benefit of forcing us to focus on convenience factors such as ease of purchase and use as well as performance reliability.

Conservative buyers reward innovation teams for attention to human factors, optimized product design, and streamlined sales operations. However, none of this matters without the requisite social proof and peer pressure from Pragmatists and other Conservatives. For this reason, premature focus on these factors generally bodes ill for innovation teams, particularly in B2B markets. Making something more usable before verifying that it is actually useful to a sufficient number of paying customers is usually an expensive exercise.

Laggards / “Skeptics”

Skeptics are as likely as not to avoid adoption to the bitter end. As hostile as Skeptics may be to any innovation endeavor, engaging them in good faith whenever they are encountered can deliver at least one important benefit.

Skeptics tend to draw attention to specific gaps between product promises and actual performance. (This rarely feels beneficial or benign to innovation teams grappling with concept models and prototype.) Still, innovation teams who are open to engaging with this challenging segment gain precious opportunities to achieve greater user understanding, client empathy & client orientation. Particularly if the spotlighted performance gaps lead to specific insights about customer failures – e.g. critical breakdowns in business processes or the user journey – we can gain a much deeper understanding of the customer’s work context, business problems and use constraints.

5. Innovation Is Really Hard

All of this is much easier said than done. It is an inordinate amount of work and most of it cannot be done sitting at a desk. If we intend to put a dent in the universe, we cannot expect to coddle our creations in a pristine but sterile lab. Instead, we have to venture out into the messy and chaotic world that we hope to change.

Effectuating meaningful change is also hard because it demands, early and often, productive collisions with many people who will disagree with us. That work involves lots (and lots and lots) of dismissal, criticism and outright rejection.

To survive this bruising onslaught, innovators and change agents need to develop not only relevant expertise and skill sets but also habits of mind. Chief among these is a habit of thinking deeply and constructively about the viewpoint of the customer.

Much like a fledgling magician without an audience, an innovator without a customer is just another person with a quirky hobby.

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What’s Next? See ULX Partners: UnitedLex develops solution to law firm innovation risk (053)

When David Cambria sat down with Eric Elfman to discuss his willingness to try Onit software, he stated that if ADM in-house lawyers were required to engage “in a single unnatural act,” the implementation would fail.

Cambria elaborates, “Why are we all so comfortable with Word, Excel, and Outlook? Because these tools don’t have an opinion about how we do our work. Enterprise software, however, always has an opinion.”

Hardened by 25 years of work experience in consulting and legal operations, David communicated his need for workflow tools that did not require his lawyers to change. Further, he needed significant productivity gains and a steady stream of clean, reliable data to better manage the department. A high bar for success.  Yet, according to David, Onit managed to deliver.

Cambria, Global Director of Legal Operations at ADM, recounts this story during Week 6 of “How Innovation Diffuses in the Legal Industry.”  Eric Elfman, Founder & CEO of Onit, was also present, giving his own entertaining version of a project that went on to win a 2017 ACC Value Challenge Award.

By inviting Cambria and Elfman to class, I hoped students would get a glimpse into the type of buyer-supplier relationship that enables a legaltech company to successfully “cross the chasm.” See Posts 024026 (discussing chasm framework, its connection to diffusion theory, and its applicability to the legal industry).


For a summary of Week 2 guest lectures (Pangea3, Practical Law Company, Hotshot), see Post 032. For week 3 (consultative sales at Thomson Reuters), see Post 034. For Week 4 (a deep dive into Axiom), see Post 036. For Week 5 (law firm examples of intrapreneurship), see Post 039.


Crossing the Chasm

I knew I hit pay dirt when Elfman came to class with a dog-eared copy of Crossing the Chasm.  Naturally, I had to ask, “Have you ever crossed the chasm?”  With an enormous grin, Eric replies, “Twice.”

The first time was with Datacert, an e-billing company Eric founded in 1998 with $1,000 of his own money.  The timing and concept were right, as Elfman quickly landed five Fortune 500 clients, making it relatively easy to attract investor money to build out the product and scale. When Eric left the Datacert in 2008, it was valued at $60 million. In 2014, Wolters Kluwer acquired Datacert for $290 million, merging it with TyMetrix to create what is now known as Wolters Kluwer ELM Solutions.  (The acronym “ELM” stands for enterprise legal management.)

The second crossing was with Onit, a business process automation company Elfman founded in 2010. This time, Eric put $1 million of his own money followed by four rounds of outside investment (a mix of debt and equity) totaling $16.4 million.  Eric stated that the company crossed the chasm approximately a year ago when operating income could more than cover ongoing R&D and sales efforts.  “That is not to say we won’t raise more money,” added Elfman. “Simplicity is extremely expensive to create. You also need to have high quality products when customers want to buy them.”

Onit’s core product is configurable software that can be deployed relatively cheaply and pointed at a wide range of legal department needs.  Established applications include legal spend management, matter management, contract management, legal holds, legal service requests, NDAs, and virtually any type of work flow involving knowledge workers.

Onits’ major competitors are enterprise software providers that serve corporate legal departments. However, most competitor offerings are built around a single problem. This means that legal departments tend to have several enterprise systems that can’t talk to each other very well. As discussed in more detail below, legal departments are perennially underwhelmed with their enterprise software incumbents (my observation, not Elfman’s).

Onit currently has 105 employees in the US, UK and India, and $10 million in annual revenue. According to Elfman, for the last three years, the company has been growing at a 50% annual rate.

Corporate legal departments as a target niche market

As I listen to Cambria and Elfman share their experiences, I am surprised by how well the narrative fits the crossing-the-chasm framework.

To refresh readers’ understanding, a company starts life with a generic product that likely impresses technology enthusiasts but lacks the features needed for broad mainstream adoption. Thus, to cross the chasm and achieve commercial success, a company must (a) target a niche market that could benefit from the innovation, (b) identify its biggest pain points, and (c) work backwards to build a “whole product solution” that becomes the “the only reasonable buying proposition” for the target market customer.  Moore, Crossing the Chasm (1st ed. 1991) at p. 110; see also Post 024 (summarizing basic framework).

This is Moore’s “big fish, small pond” strategy, which is designed to create focus on the narrow set of clients and conserve the bandwidth of key personnel.  See Post 025. If executed properly, the post-chasm company has successful commercial relationships with “pragmatist” mainstream customers. This sets off a word-of-mouth campaign that dramatically reduces the cost of sales. Further, once inside the mainstream market, the company is well-positioned to develop and sell future products and services.

In short, crossing the chasm is a one-time event that changes everything for the better. See graphic below:

Well, what is Onit’s target niche market (or small pond)?  Here I get an important lesson in framing.

Virtually all legaltech companies target a discrete problem or complex task that exists within a legal department. These problems or tasks include e-billing, matter management, document management, e-discovery, contract analytics, etc.  When evaluating this market structure, the natural capitalist impulse is to integrate these disparate systems into a single enterprise solution, thus achieving economies of scope and scale. Indeed, this is the logic behind many legaltech acquisitions, including the Datacert-Tymetrix tie-up. Framed in this way (which is the way most legal insiders see legaltech), the small pond is one or two significant problems or tasks inside a legal department.

But that is not Onit’s strategy.  Onit is a business process automation company where legal departments are viewed as a small but influential beachhead that can provide access to rest of the corporation. Thus, the addressable market is not all corporate legal departments (which might be $3-5 billion), but corporate knowledge workers struggling to collaborate effectively within and across business units (probably 100x bigger). Framed in this manner, the small pond is legal department operations.

Few tech entrepreneurs would be anxious to have legal as their initial target market. The field is highly technical; the clientele are demanding; and the financial upside is limited. But Elfman sees things differently.  “The lawyers are the laggards. They are the Department of No. If we can win them over, the rest of the corporation is a lot easier.”

I am inclined to take Elfman seriously because he and his team are obsessively focused on delivering a whole product solution. To fully grasp what this means, we need to understand Onit as compared to its primary competition.

Compared to what?

In Crossing the Chasm, Geoffrey Moore makes the point that prospective clients are unwilling to strain their attention span to hear your pitch. Thus, a product needs to be positioned against what is familiar and established, thus enabling target clients to quickly categorize your product.  Yet, to generate curiosity and interest, the product also needs to be different in a way that delivers a substantial benefit. See pp. 159-61.

As previously noted, Onit’s primary competitors are enterprise software companies that offer solutions to one or more legal department needs, such as e-billing, matter management, contract automation, or data analytics. In my travels to various industry events involving legal technology, I often hear the refrain, “Everybody hates their e-billing vendor.”  The same tends to be true for document and matter management. To date, no company has emerged as the obvious first choice.

Most of these companies got their foothold many years ago when legal departments were growing rapidly and general counsel and their lieutenants felt vulnerable regarding the lack of basic systems and controls. For example, without enormous manual effort, the department could not answer basic questions related to outside counsel spending; or the department couldn’t generate a useful status report on pending litigation; or lawyers struggled to locate prior work product. In each case, there was an enterprise software solution or platform designed to make that problem go away.

Indeed, Elfman tells the story of how he got the idea for Datacert. After completing his MBA at Rice in 1995, he went to work for a litigation consulting firm that specialized in forensic accounting.  While working on an engagement for Exxon, Eric asked the head of litigation about the size of his total annual spend. The AGC responded, “I’m not sure.  Somewhere between $200 and $400 million.”

Elfman describes this exchange as “the moment that changed my life.”  The business opportunity was large and obvious: use technology to apply basic accounting discipline to corporate legal spending.

Datacert and Elfman were extremely successful making sales to a lot of large corporations. Eventually, Datacert would land 130 companies in the Fortune 500, including #1, #2, #3, and #5.  Yet, Datacert also became part of the large cadre of enterprise software companies that legal departments complain about (this observation is based on my own industry knowledge, not any comments made by Elfman regarding his former company).

Root cause

As I listen to David Cambria and Eric Elfman discuss their collaboration, a deeper understanding of the problem comes into focus.

As David points out, when enterprise software is pointed at a specific problem, it develops a strong opinion about how the work should be done. Invariably, that opinion adds steps to the workflow, often without delivering any immediate or tangible returns to the worker trying to do their job. Naturally, people being people, they find ways of minimizing their interaction with the system. Thus, the resulting incomplete and uneven usage undermines the value of the enterprise solution. It also limits — possibly to zero — the amount of usable data the system produces.

In theory, management can fix this problem by mandating usage.  They can fire people. They can reduce or withhold bonuses.  Political capital, however, is limited.  Few bosses want the troops grumbling about how a six-figure software mistake is hindering their ability to do their jobs. So the natural equilibrium becomes enterprise software that is half used. This is usually a modest improvement over the prior state of affairs, but well short of expectations when the licensing agreement was signed.

This recurring cycle explains why David Cambria has such disdain for business solutions that require unnatural acts. Likewise, this is why Eric Elfman was ready to leave Datacert after ten years at CEO.  This was a game he could not win.

What problem is Onit trying to solve?

Eric Elfman left Datacert in 2008.  Two years later, he started Onit with Eric Smith, Datacert’s longtime CTO.  Yet it wasn’t until 2011 that Elfman and Smith came up with the core idea for Onit, which is “collaborative process automation for knowledge workers.”

Not very intuitive, right?

To Geoffrey Moore’s point, it is very difficult to understand an innovation without one or two familiar reference points. This is particularly true with something as abstract as software. Thus, the graphic below proved to be enormously useful to the class.

On the left side (in green) is enterprise software, which attempts to solve problems through top-down controls.  Although these solutions tend to be complex (requiring IT support) and expensive (big up-front fees and implementation), they hold out the promise of permanently eradicating a serious problem. The implicit assumption is that workers will use the system as designed — an assumption that, experience shows, is often unjustified and unrealistic.

On the right side (in orange) are Enterprise 2.0 tools (like Slack, Zoom, or Yammer). Individual users and work teams like these tools because they increase the velocity of employee communication.  Corporations are happy to support Enterprise 2.0 tools because they are cheap and low risk. But they also don’t produce any structured data that senior managers need to assess and improve organizational performance.

Despite billions of dollars spent on enterprise software and the hype and popularity of Enterprise 2.0, Elfman observes that “virtually all knowledge work and processes are executed outside of these systems.” Instead, in most organizations, workers try to do everything with familiar Microsoft tools:

  • Email is the intake and “collaboration” platform, within and across business units
  • Word documents are the “forms” solution
  • Excel is used for tracking and reporting
  • Sharepoint is used as a document repository

Virtually all legal operations professionals will acknowledge that these tools are breaking down as solutions. They are just not fit for purpose.

Onit (in blue) is trying to fill in the middle ground between Enterprise (green) and Enterprise 2.0 (orange). The key innovation of Onit is that it enables a business process owner to work backwards from how people work (people-centric) rather than backwards from an acute organizational pain point (problem-centric) and thereafter expecting workers to get onboard.

“Bring the work to the people”

When Cambria signed on with Onit, he had a vision to “bring the work to the people.” Where are the people in ADM’s legal department? Probably somewhere near a device where they read their email.

Onit is behind a wide range of automated workflows at ADM, including: (1) matter intake and routing, (2) early case assessments, (3) liability reserves, (4) invoice review and approvals, (5) settlement authority requests, (6) recording of matter disposition, and (7) on-demand NDAs. Yet, for most ADM lawyers, Onit is barely visible:  it’s all point-and-click tasks and hyperlinks embedded inside emails — highly natural acts for lawyers. Cf. Post 040 (per “lawyer theory of value,” lawyers have a strong preference to be left alone to do legal work).

Cambria or a member of his staff are usually the “business process owner” for each of these processes.  Onit is simple and flexible enough for them to do a fair amount of programming on their own — no need to involve corporate or department IT. This is ideal because the legal ops team is close enough to the work to gauge what the workforce is willing to accept. And If they are wrong, adjustments can be made cheaply and quickly.

Nudges and the Onit backend

One way that Cambria drives the broader agenda of the department is to include “nudges” in the Onit workflow.  A nudge makes it modestly more difficult for lawyers to override an established playbook solution. For example, if an ADM in-house lawyer wants to retain a law firm that is not on ADM’s preferred panel list (ADM winnowed 700 law firms down to a preferred provider list of 20, see “How ADM Cut Its Outside Counsel Rosters By 680 Law Firms,” Law360, June 8, 2016), a text box appears that requires a written explanation.  Because this choice requires additional work and invites scrutiny from the boss, it is chosen less often.  Explains Cambria, “I’m always mixing the peas in with the mashed potatoes.”

Although Onit is largely invisible to a substantial portion of the ADM legal department, the Onit applications demo-ed in class — i.e., the backend where David and his staff configure workflows and dashboards — is surprising clean and simple.

David shows us the main dashboard he uses monitor the legal department (16 tiles of information).  He also shows one of the dashboards he built for Cam Findlay, ADM’s general counsel, which provides real-time information likely of interest and value to the C-suite.  Some of the tiles use Tableau to display the information graphically (other data visualization programs can be used).  All of these graphics are generated from data captured by Onit workflow systems.  The data are high quality because Cambria has ruthlessly reduced the number of unnatural acts required by his lawyers.

Diffusion theory wrap-up

Eric Elfman readily admits that Onit targeted Cambria as an early adopter and opinion leader.  Cf. Post 020 (discussing the crucial role of opinion leaders in accelerating innovation adoption).  Eric comments, “David got a whole lot of software for very little money. But we wanted him as a reference client.  And frankly, it’s been worth it.”

Cambria was drawn to Onit because it offered him the possibility of improving the performance of ADM’s legal department without requiring this lawyers to learn new technology or do data entry. This is the novel perspective of a true “visionary” customer as defined in Crossing the Chasm.

These are interesting anecdotes. However, if we want deep learning from this case study, it is important to tie what we see back to the empirically validated principles of diffusion theory.

As discussed in foundational posts 008 and 011, innovation adoption — whether it happens at all, and if so, at what rate — is primarily a function of five innovation attributes. See graphic to right.

In addition, software for managing complexity requires us to evaluate these attributes from two perspectives:

  1. Managers making the purchase decision. These are folks with a serious business problem and a limited amount of time and technical expertise, at least with software.
  2. Workers asked to use a new software solution. These are busy professionals who just want to get their work done.

Arguably, legal departments have historically made the mistake of focusing too much on (1) and underestimating (2). This explains their perennial disappointment with enterprise software.

The table below scores Onit from both perspectives using the simple scoring system developed in Post 011 (fast versus slow innovations):

  • Positive numbers (+1  to +3) speed up the adoption rate
  • Negative numbers (-1 to -3) slow it down
  • Mild effect = -1 or 1; moderately strong = -2 or 2; very strong = -3 or 3
  • No effect on rate of adoption = 0
Factor affecting adoption rate Manager Worker Adoption Analysis
Relative advantage 2 3 Managers get complete, high quality data, albeit after a learning curve. Workers are not asked to perform unnatural acts; minimal change management.
Compatibility -1 3 Managers are business process owners and have to learn cloud software related to workflow; new but surmountable. Workers get to stay within email and Internet browsers; basically this is change that feels like the status quo.
Lack of Complexity -1 3 Managers have to climb a learning curve, but its mostly cloud-based drag-and-drop tools. IT support is minimal. Workers carry on business as usual.
Trialability 2 2 Managers can get started at a low cost (e.g., just one Onit application) and build it out as needed. Worker feedback enables quick and inexpensive changes in process.
Observability 2 -2 Managers can see the high quality data pile up.  For workers, there is a limited ability to observe fellow knowledge workers being more productive. This factor is hard to change. It is also why we laugh at Dilbert cartoons.
Totals +4 +9

The key insight of this analysis is that Onit is likely to enjoy rapid adoption with workers, largely because it places so few demands on them.  Although managers don’t have it so good — they actually have to learn a new technology — it’s likely worth it.  As the ADM example shows, worker adoption occurs in a low friction way; also, senior personnel in the legal department can finally see, measure, and manage essential business processes. From a big picture perspective, this is a potential home run.

During class, Eric Elfman observed that technology start-ups are essentially “a series of experiments until something works or you run out of money.”  According to Cambria, Onit works well.  That is very good news for Elfman and Onit.

What’s next?  See Legal Services and the Consumer Price Index (042)

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)

In Part I (024) of this series, I introduced Geoffrey Moore’s Crossing the Chasm framework.  In Part II (025), the goal is to apply it to a contemporary example of a high-tech company selling to legal departments. Part II then finishes the chasm framework and discusses some of the special challenges of applying it to the legal industry.


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.

The pre-chasm challenge

Imagine that we are part of a legaltech start-up that has developed a machine-learning AI capability with the potential to be a best-in-class solution for many time-consuming and important activities inside a large legal department.  We’ve made a few sales to some visionary legal innovators/early-adopter types, but the work has mostly been custom.  As yet, we don’t have a turn-key solution that is scaleable. Further, none of us has focused on the humdrum details of successful implementation.  In fact, we have no reference customers that would satisfy a pragmatist buyer. In short, we are a pre-chasm company.

To keep the team believing in the cause and to avoid running out of cash, we have three short-term objectives:

  1. Dramatically reduce our sales cycle
  2. Limit the amount of customization (ideally to zero)
  3. Obtain a base of satisfied pragmatist clients.

Following Moore’s chasm playbook from Part I (024), these three objectives are only possible by overwhelming a niche market segment with our commitment to their problem set, making our company “the only reasonable buying proposition” (p. 110).

Thus, the task on our plate is to correctly identify the right niche market and, through intense focus, successfully deliver a whole market solution. Otherwise, we are going to fall into the chasm.

Which market niche?

As noted in Part I (024), the only tools we have to cope with our “low data, high risk” environment are imagination and empathy.

We start by developing composite profiles of characters working inside our typical buyer and evaluate as objectively as possible how our product positively and negatively affect each of their lives. If the buyer is a legal department, the cast of characters would likely include the GC, the Director of Legal Ops, line in-house counsel, paralegals and admin staff, CEO and CFO, etc.

If we are like other founders and technical types, we’re likely very self-satisfied regarding the versatility of our technology, claiming it can solve many problems well. That may be true, but what product application is going to have the biggest impact across multiple internal stakeholders? If we can deliver a whole product solution in that specific niche, the resulting word-of-mouth buzz will create the enormous tailwind we need to get to the other side of the chasm.

We identify the starting point by building a matrix of stakeholders and applications and scoring each combination on a 1 to 5 scale. Using Moore’s scoring system,  1  = “not usable” and 5 = “must have.” See Figure 6 to right (numbering continued from Part I (024)).

What are some the applications for machine-learning AI?  Based on what I’ve seen at CLOC, ILTA, the ACC Legal Ops meetings and general networking within the industry, there are many.  Each of the applications in Figure 7 below reflect real use cases currently being pitched to large legal departments. In other words, the fate of numerous pre-chasm companies hangs in the balance. The assigned numbers are based on the composite sketches of how the application would impact the daily lives of specific personnel.  Following Moore’s methodology, we are always looking for “must haves.” Thus, 5’s are highlighted in yellow.

Note that the scores inevitably vary based on the stories we construct, albeit we want to construct the most balanced and plausible story possible.  Indeed, the entire point of the exercise is to prime the right side of our brains so we can see the world through the eyes of prospective customer stakeholders and end users and accurately identify who would most benefit from our product. Once identified, we’ll do everything in our power to adapt it into something they must have.

For example, regarding the first application, M&A due diligence, a corporate acquisition can be a heavy burden on in-house corporate counsel and paralegals. Thus, they might welcome the automation of a large volume of boring scut work.  Yet, how much internal juice do they have?  If, however, the company is a serial acquirer where the typical targets involves complex IP or environmental issues that warrant the extensive use of outside counsel, then the score assigned to the GC, Director of Legal Ops, or the CEO/CFO might reach a 5, particularly if the whole product solution reveals a large quality advantage (i.e., the machine makes fewer mistakes than people; the machine aids corporate integration). This has become Kira System’s value proposition.

Note how the search for “must haves” in the example above has the effect of narrowing the niche market — to serial acquirers with due diligence that is voluminous and legally complex.

The second AI application, outside counsel selection, can also be narrowed.  For example, if legal is a significant cost in a thin-margin business (e.g., insurance, retail, transportation), the GC and CEO/CFO scores might reach the must-have level. This might compensate for the fact that lawyers and staffers who work regularly work with outside counsel aren’t going to like the disruption of changing firms.

Likewise, for the fifth AI application, automated legal review, there are products entering the market that score the legal risks of a proposed contract against desired terms in the company’s playbook, essentially doing the reading and analyzing normally done by lawyers. In most legal departments, this will score a 3 or 4, as it adds no strategic value and the AI machine might make a mistake that will make decision makers look bad. Yet, in complex industries where in-house staff is already at 100% capacity, automated first-level legal review of low-risk, high-volume contracts may be a better long-term solution than more FTEs. Thus, this might become a “must have” for a GC or Director of Legal Ops who needs more lawyer bandwidth focused on high-value company legal work. I know this because Cisco’s legal department is experimenting with this technology in conjunction with Kim Technologies.

The above exercise can be uncomfortable for those of us in the technical crowd who helped build the generic product. We wonder, “why can’t they see what we see?”  Thus, reflexively, we tout data and the technical features of our product, often repeating ourselves. Yet, if we can endure the discomfort of getting inside the head of people very different than us, we’d see how our offering is often a mixed bag when second- and third-order effects are factored in. Cf. Post 020 (reporting “client orientation” and “client empathy” as key attributes of effective change agents).

To boil it down, if this exercise is faithfully performed, we dramatically increase our odds of locating a niche mainstream market where a specific application of our product is a must have. But all-too-often, the temptation is to double-down on sales. “We don’t have time for theories. We don’t have time for books.” Cf. Moore at 68 (“The consequences of being a sales-driven during the chasm are, to put it simply, fatal”).


The above exercise is based on Chapter 4 “Target the Point of Attack” of Geoffrey Moore’s Crossing the Chasm (1st ed. 1991). The original exercise, now more than 25 years old, used a pen-based laptop as the innovative new technology.


How to position (i.e., describe) our product

Buyers have different agendas than sellers, particularly in the mainstream market.  As Moore notes, the lead buyers in the mainstream are pragmatists who want to make a safe choice that will enable them to look good and hit their numbers. Pragmatists also have other things on their plate besides making a purchasing decision.  Thus, to save time and avoid mistakes, the’re going to categorize our product based upon their current frame of reference.

According to Moore, this will be done by placing us within a competitive bracket based upon other vendors and products.  Such categorization takes mental work.  If we leave all of this work to the pragmatist, the comparisons will be too simplistic and unfavorable to us.  Thus, as much as possible, we’ll pre-package a comparison to aid our prospective customers.

Moore calls this “positioning” and offers the following plug-and-play formula to make sure we get it right. Moore instructs the reader to “just fill in the blanks”:

  • For (target customer)
  • Who (statement of need or opportunity)
  • The (product name) is a (product category)
  • That (statement of key benefit–that is, compelling reason to buy)
  • Unlike (primary competitive alternative)
  • Our product (statement of primary differentiation). [pp. 160-61]

How useful is this? Moore offers the following example of Microsoft’s positioning of Windows 3.0 in the early 1990s:

For IBM PC users who want the advantages of a Macintosh-style graphical user interface, Microsoft Windows 3.0 is an industry-standard operating environment that provides the ease of use and consistency of a Mac on a PC-compatible platform. Unlike other attempts to implement this type of interface, Windows 3.0 is now or will very shortly be supported by every major PC application software package. (p. 162, emphasis added)

In a profoundly concise format, this positioning statement give the pragmatist everything he or she needs to make a purchasing decision.

By proper positioning, we boil everything down so we can pass what Moore calls “the elevator test.” Specifically, if our product can’t be easily described in the time it takes to travel from floor to floor in an elevator, then our product will never get the enormous tailwind of a word-of-mouth campaign within the mainstream market. Cf Moore at 159 (“Since we have already established that word of mouth is fundamental to success in high-tech marketing, you must lose [if you can’t pass the elevator test]”). Until we get this distillation right, we’re stuck with an impossibly long sales cycle and the likelihood that our competitors will do our positioning for us.

What our customers say about us

When crossing the chasm, there is (a) the positioning statement we communicate to our target customers before the sale, and (b) what our customers say about us after they’ve experienced our product.  The subtitle of Moore’s book may lull lawyers into believing that Moore is only talking about (a) — how to position the product. Yet, Moore seems no less worried about (b). Moore writes:

In the simplified [whole product] model there are only two categories: (1) what we ship and (2) whatever else the customers need in order to achieve the compelling reason to buy. The latter is the marketing promise made to win the sale. The contract does not require the company to deliver on this promise – but the customer relationship does. Failure to meet this promise in any business-to-business market has extremely serious consequences. As the bulk of the purchases in this marketplace are highly reference-oriented, such failure can only create negative word-of-mouth, causing sales productivity to drop dramatically. (p. 115).

A careful reading of Moore reveals that the “big fish, small pond” strategy is as much about conserving bandwidth and resources by not overpromising as it is finding a market segment with a must-have customer need.

Ironically, as difficult as it is to enter the mainstream market — have a great generic product, pick the right market niche, position the product so it’s easy to buy, and then deliver on the whole product solution — the rules seem to operate in reverse once a company gets to the other side of the chasm.  Moore notes, “the more you spend time with mainstream customers, the more you see how relentlessly they pursue this conspiracy to sustain market leaders” (p. 75). Thus, crossing the chasm is a one-time event that permanently alters the financial fortunes of a company — a game that is very much worth the candle.

Selling and law firms as distribution channels

Returning to our AI-enabled legaltech start-up, what’s our sales plan?

Most of the context of Crossing the Cross is based on enterprise-level technology solutions sold to large corporate clients — that is, the same posture as most legaltech start-ups. Moore lists out several options for making sales along a spectrum of “demand creators” (a direct sales force using consultative sales) to “demand fulfillers” (retail outlets).  The more novel and innovative our product, the more we’ll need a direct salesforce to prime the pump.

The problem is that direct sales is expensive. Moore notes, “To support a single consultative salesperson requires a revenue stream of anywhere from $500,000 to several million dollars [in 1991 dollars], depending upon presales and postsales support provided” (p. 173).  As good as a direct sales team can be at educating prospective customers and creating demand, Moore argues that a direct sales force is probably not viable unless the minimum sales is at least $50,000 — again, in 1991 dollars.

As a more cost-effective alternative, Moore suggests a “selling partnership” with another company that already has a business relationship with the target clientele.  Here, law firms come to mind, either as a bundled offering with the firm’s consultative legal services or as a preferred vendor when the firm cannot get the work without adding an external capability that the client is demanding. Under this approach, law firms could become an invaluable distribution channel.  Although Moore acknowledges that this approach may dramatically cut into pricing power — “he who owns the customer owns the profit margin and the future of the product” — he nonetheless endorses it as a way to reduce risk and avoid the grief of managing a salesforce not fit for purpose (p. 175).

For many a legaltech and NewLaw start-up, this approach sounds good in theory but has seldom worked well in practice.  Perhaps the reason can be found in the must-have value proposition that mainstream pragmatist buyers find most irresistible. According to Moore, this is a product offering that “radically improves productivity on an already well-understood critical success factor” (p. 103).  No disruption; just a quantum improvement in what we already known. Unfortunately, so often the business opportunity of legaltech and NewLaw is reducing the inefficiencies and quality constraints of the traditional practice of law billed by the hour.

I know several start-up founders who wish they could get back the thousands of hours invested in trying to strike a deal with law firms. Whether it’s short term self-interest or the consensus decision making of law firm partnerships, see Post 008, law firms have yet to see the benefits of being a distribution channel for new products or services that could significantly help their clients.  Unfortunately, this is a major bottleneck to innovation diffusion within the legal industry.

What’s next? See “Crossing the Chasm” and the “Hype Cycle”, Part III (026)

The two figures above reflect frameworks that are widely used within the technology industry to grapple with the treacherous nature of high-tech product development.

Figure 1 is the 2017 Hype Cycle, which is published by Gartner, a large international research company that helps CIOs and other IT professionals understand and evaluate emerging technologies. The Hype Cycle has been published every year since 1995, always with the same shape and the same five stages, beginning with the “innovation trigger” and ending with the “plateau of productivity.” The only changes are the technologies and their relative placement on the Hype Cycle.

At the “peak of inflated expectations” for 2017, we see several types of artificial intelligence that are now widely discussed in the legal press, often with headlines that foreshadow the replacement of lawyers by machines. If Gartner is right, such a threat is premature, overblown, or both.

The second figure (Figure 2) looks like a Rogers Diffusion Curve, see Post 004, but with a large gap between the early adopter and early majority segments. The gap is the “chasm” discussed in Geoffrey Moore’s Silicon Valley classic, Crossing the Chasm (1st ed. 1991).  Figure 2 is titled “The Revised Technology Adoption Life Cycle” because Moore added the gap to reflect the crucial transition from early adopters to the early majority. (Prior to Moore’s book, the high-tech community relied heavily upon the unrevised model — i.e., a model identical to the Rogers Diffusion Curve.)

Moore’s core thesis is that most high-tech ventures fall into the chasm and die because they fail to grasp the many moving parts that must be fashioned and coordinated to move from early market to the mainstream market — i.e., to cross the chasm.  Moore’s book provides very detailed prescriptive advice. Once on the other side of the chasm, the company has a much higher probability of ascending the upward-bound S-curve and thus producing a large financial return for company founders and investors.

Moore’s book is essentially a practitioner’s manual, far removed from academic theory or empirical validation.  Yet, it is now in its third edition and has sold more than 300,000 copies.


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.

The Roadmap

This is Part I of a three-part final installment in Legal Evolution’s foundational series on diffusion theory, albeit the topics covered — “Crossing the Chasm” and the “Hype Cycle” — are not part of diffusion theory, at least not directly.  Nonetheless, these two frameworks have long guided decision making in the tech industry; and tech is indisputably where the legal industry is headed. Therefore, those working in legal innovation need to understand how these concepts fit together.

  • Part I (024) summarizes the key features of Geoffrey Moore’s widely used and powerful chasm framework.  It is very important for readers to understand these ideas from the perspective of Moore and his audience — i.e., as practical business advice being dispensed to entrepreneurs. Surely practicing lawyers ought to be sympathetic to this approach.
  • Part II (025) applies Moore’s framework to a real-world example of high-tech companies selling to legal departments.  Part II then finishes the chasm framework and explains the special challenges of applying it to the legal industry.
  • Part III (026) reveals the unusual intellectual origins of Crossing the Chasm and how those origins illustrate several of the key concepts of diffusion theory in ways that are surprising and ironic. Part III also returns to the Gartner’s Hype Cycle as a lens for viewing technologies at the industry rather than the company level.

More so than any other foundational posts, Posts 024-026 speak to the specific challenges of legal start-ups and technology companies. Law firms are discussed, albeit primarily as part of a “distribution channel” that controls valuable client relationships.  For a variety of reasons, most law firms will be reluctant partners. It is unclear whether in the long run that will prove to be a wise strategy.

The Whole Product Solution

An entrepreneur “crosses the chasm” by turning a fledging start-up into a high-growth business built around a new technology. Much to the chagrin of technology inventors, the technology itself is not sufficient to reach this goal. Instead the technology must to become part of a “whole product solution” that anticipates and overcomes a wide range of potential obstacles to adoption.

Building a whole product is less a technical feat than an extended exercise in commercial empathy. Several market competitors may have similar technology.  But according to Moore, the first to build and communicate a whole product solution will be the first to cross the chasm and capture the mainstream market.  See p. 114 (“[W]inning the whole product battle means winning the war”).

Below are two graphics that reflect the whole product solution.

Figure 3 is what Moore refers to as the Whole Product Model.  At the center is the Generic Product, which is “what is shipped in the box and what is covered by the purchasing contract” (p. 111).  However, end users make buying decisions based on the “expected product”, which Moore describes as “the minimum configuration of products and services necessary to have any chance of achieving the buying objective” (Id).  For example, if the generic product is an IBM PC equipped with a Microsoft DOS operating system — a product on the market when Moore was writing the first edition of Crossing the Chasm — Figure 4 is a reasonable depiction of the ancillary products and services that make up the expected product.

A company has crossed the chasm when it has become a market leader in a niche portion of the mainstream market.  Although the foothold is not large, it is the ideal place to develop the “augmented” and “potential” products (the third and fourth rings in Figure 3).  If the expected product was the IBM PC shown in Figure 4, the augmented product might include a customer hotline, advanced training, accessible service centers, and expanded software offerings. Likewise, the potential product might include what we see today — a platform for streaming entertainment and playing complex, interactive games.

The Early Market versus the Mainstream Market

According to Moore, its not the underlying technology that separates winners and losers.  Rather, it is a failure of both entrepreneurs and investors to realize that the market is divided into two parts — an early market, where a promising generic product is sufficient; and a mainstream market, where customers will not buy without overwhelming evidence that they are, in fact, buying the whole product. See Figure 5 below.

Success in the early market comes in the form major sales to visionary clients who see the technology’s breakthrough potential. This market evidence is often sufficient for venture capitalists to provide another round of financing in anticipation of rapid growth. This is because VCs — more so in the days before Moore’s book — bought into the smooth continuous shape of the Technology Adoption Life Cycle (Figure 2 above, but without the chasm).  All-too-often, however, the S-curve adoption never materialized.

The recurring mistake, according to Moore, is that customer expectations are dramatically different in the early versus the mainstream market.  In the early market, “visionary” early adopter customers are drawn to the potential breakthrough implications and have the imaginative capacity to envision the whole product as something real and inevitable.  Yet, visionary buyers are relatively rare. But Moore argues that the problem runs deeper than that — these “visionary” early adopters are unsuitable as reference clients.

Moore refers to the early majority (the leading edge of the mainstream) as “pragmatists” because their buying requirements are so practical and stringent.  “When pragmatists buy, they care about the company they are buying from, the quality of the product they are buying, the infrastructure for supporting products and services and systems interfaces, and the reliability of the service are going to get” (p. 43).  When the company’s sales team points to visionaries, the pragmatists are unimpressed, distrusting the visionary’s risk-taking, flaunting of convention, excessive attention given to early stage technology, and the “overall disruptiveness” they impose on others. See p. 58-59.

If a tech start-up is not aware of the chasm, it runs the risk of being lulled into complacency by a few large sales to visionary clients.  But more problematic is the resulting “catch-22.” As Moore notes, “The only suitable reference for an early majority customer … is another member of the early majority” (p. 21).  This is the problem that Crossing the Chasm is trying to solve.

How does a company cross the chasm?

A company transitions from the early market to the mainstream market — i.e., crosses the chasm — by focusing on a niche market where, by sheer dint of preparation and focus, it becomes “the only reasonable buying proposition” (p. 110).  The narrow focus is necessary to conserve limited resources and increase the odds of delivering a whole product solution.  This “big fish, small pond” strategy enables the start-up to “secure a beachhead in a mainstream market — that is, to create a pragmatist customer base that is referenceable” (p. 68).

Moore provides tremendous guidance on how to find the right niche market.  The difficulty is that a technology start-up only has a few significant clients in the early market, none of whom are representative of the mainstream.  Because better information is time and cost prohibitive, pre-chasm companies operate in a “low data, high risk” environment.  Thus, the only option is to engage the management team’s imaginative faculties to anticipate the needs, preferences, and objections of the various stakeholders employed by your target clientele.  This is the extended exercise in commercial empathy mentioned earlier — and its extremely difficult, particularly for left-brained technical types (lawyers as well as engineers).

In Part II (025), I will illustrate how this is done by applying Moore’s methodology to a contemporary legal industry example.

What’s next?  See “Crossing the Chasm” and the “Hype Cycle”, Part II (025)