The chart above, drawn from Everett Rogers, Diffusion of Innovations Fig. 7-1 (5th ed. 2003), shows the adoption of hybrid seed corn by farmers in two Iowa communities. The dashed line on the bottom shows the number of adoptions by year.  The solid line on top shows adoption on a cumulative basis.  The first farmer in the sample adopted hybrid seed corn in 1927. 15 years later, in 1941, the last four farmers made the switch.

The dashed line is a real-world example of a Rogers Diffusion Curve. See Post 004 (discussing curve); Post 007 (discussing adopter types).  Likewise, the solid line is a real-world example of the S-shaped curve. The farmers switched to hybrid seed corn because it was more bountiful, disease resistant, and drought resistant than traditional methods. The chart above is useful because it shows the common diffusion pattern of (1) a prolonged period of slow adoption, even for a highly advantageous innovation; and (2) a short period of rapid adoption. Cf. Post 016 (showing histogram with long innovator tail). Continue Reading Change Agents and Opinion Leaders (020)

The graphic above reflects three different types of innovation “outcomes”:

  1. Initiation of an innovation adoption process that results in an organization making a decision to adopt an innovation. See Post 015
  2. Implementation of the adoption decision, which entails planning, change management, and redefining/restructuring and clarifying the innovation in the field so that it delivers its intended benefits. See Post 015
  3. Adoption Success, which presumes success in both initiation and implementation.

This is Part III of a three-part series on innovation in organizations.  In Parts I and II (Posts 015 and 016), we discussed how multivariate regression models are built around an “outcome” we care about, such as organizational innovation.  These models give us insight on how to influence the likelihood of the outcome. In turn, these insights become of the basis more effective strategies and interventions.

The graphic above, however, reveals a difficult organizational challenge.  Centralized management decision-making impacts the three innovation outcomes differently.  During the initiation phase, centralization has a strong negative correlation with the outcome (Panel 1). During implementation, the relationship is moderately positive (Panel 2). The two opposing effects are then netted out in Panel 3.  The result is a statistically weak and moderately negative relationship between centralization and overall adoption success.

So what does this mean?  If we want more innovation in our organizations, we need to forgo one-size-fits-all approaches to management in favor of a staged approach.

Post 017 is part 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 staged approach is necessary because several factors in Rogers organizational innovativeness model, introduced in Part I and reproduced below, have this peculiar flipping effect between initiation and implementation: (i) Centralization, (ii) Complexity, and (iii) Formalization.  This is one of the primary reasons that Rogers model has relatively low predictive power.  See Part I (Post 015) (“The predictive power of Rogers’ organizational innovativeness model is much lower than the Post 008 rate of adoption model.”).

Yet, we can adjust to these limitations through the application of our reasoning ability. See Part II (016) (noting that models are just guideposts for strategic thinking).

Consistent with the staged strategy discussed above, this Part III analysis assumes that organizational innovation requires successful initiation (agenda setting and matching) and successful implementation (redesigning/restructuring, clarifying, and routinizing). See Figure in Part I (post 015). This approach results in clear prescriptive guidance on how to increase successful innovation adoption in legal organizations. To the extent possible, this analysis uses specific legal industry examples.

Using the Rogers Organizational Innovativeness Model

Rogers models focus on applied research. This means we mine empirical models for usable insights while taking careful note of their constraints and limitations.  Thereafter, we use the resulting superior knowledge as part of a reasoning process to solve practical problems. See Post 001 (explaining difference between applied and academic research).

Below is the superior knowledge provided by Rogers’ organizational innovativeness model.

I. Individual (Leader) Characteristics — Champions

The first category of variables that influences organizational innovativeness is the presence or absence of innovation champions. An innovation champion is “a charismatic individual who throws his or her weight behind an innovation, thus overcoming indifference or resistance that the idea might provoke in the organization.” Diffusion of Innovations 414 (5th ed. 2003).

The champion could be a leader in formal position of authority (president, vice-president, manager, etc), but not always.  As Rogers notes, “The general picture of an innovation champion emerges not as a particularly powerful individual in the organization, but rather as someone particularly adept at handling people” (p. 415). Roger cites research showing the effective champions (1) tend to occupy a “linking” position in their organization, (2) possess analytical and intuitive skills in understanding various individuals’ aspirations, and (3) demonstrate well-honed interpersonal skills in negotiating with others.

It is easy to imagine how a smart, well-connected person with high EQ could be very effective in rallying enthusiasm during initiation and managing conflict and mediating solutions during implementation. Although the presence of such champions does not guarantee organizational innovativeness, Rogers suggests that their absence likely forecloses it, particularly in cases involving non-incremental change.  “The new idea either finds a champion or it dies” (p. 414, quoting Donald Schon, “Champions for Radical New Inventions,” 41 Harv Bus Rev 77, 84 (1963)).

II. Internal Characteristics of Organizational Structure

Various internal characteristics of organizational structure comprise the second category of variables that affect organizational innovativeness.

1. Centralization (-)

Centralization is “the degree to which power and control in a system are concentrated in the hands of relatively few individuals” (p. 412). As noted in Parts I and II, higher levels of centralization tend to have a negative impact on initiation. Yet, if centralized management can nonetheless manage to adopt an innovation, centralized decision-making can aid its implementation. The overall net effect, however, is negative. This is because senior organizational leaders tend to be too far removed from operational-level problems to identify relevant and workable innovations.

In my work with law firms, I have been surprised to find several examples of law firms that flourish economically because leaders have adopted a strategy of “letting partners do what they want.” In most cases, the resulting innovations take the form of specialized practices where partners command premium rates for providing fast, high-quality solutions that solve difficult client problems. The entrepreneurism consists of playing close attention to how substantive legal issues are impacting clients’ business needs and being the first to create a novel legal solution.  Although this decentralized approach can result in a sizable collection of lucrative niche practices, it likely undercuts potentially important firm-wide innovations such as project management and process improvement.

To cite another legal example, the decentralization of faculty governance in legal education results in many symposia to generate new ideas. However, we are completely lacking in effective central mechanisms for coordinating implementation. Hence our reputation for being stuck in the past.

2. Complexity (+)

Complexity is “the degree to which an organization’s members possess a relatively high degree of knowledge and expertise, usually measured by the members’ range of occupational specialities and degree of professionalism (expressed by formal training)” (p. 412). Rogers notes that a highly educated workforce is more likely to grasp the value of innovations. However, the higher levels of complexity make it more difficult to reach consensus on implementation.  Thus, the net effect of complexity on organizational innovativeness is positive but not particularly strong.

Below is a graphic that shows the complexity relationship by phase.

In law firms and legal departments, there is a strong movement to hire allied professionals trained in a wide range of useful disciplines.  This mixing of professional perspectives is bound to raise the quality of innovative thinking.  Translating these new ideas into effective action will be the core challenge of the next generation of legal professionals. See Post 005 (discussing growing size and complexity of corporate legal departments and the rapid growth of CLOC). To cope with the Panel 2 complexity challenge, the legal industry is undoubtedly headed into an era of standard-setting and standardization. This is going to produce a cultural sea change within the organized legal profession.

3. Formalization (-)

Formalization is “the degree to which an organization emphasizes its members’ following rules and procedures” (p. 412).  This internal organizational attribute has an impact that is very similar to centralization — strongly hindering initiation, aiding implementation, and overall having a net negative impact on successful adoption.

In the legal industry, we see the highest levels of formalization among the managed service providers. In this context, new entrants come on the scene with a core competence in designing and following process.  The high level of formalization results in legal work with fewer errors, lower cost, and faster delivery time.  Yet, the emphasis on process also enables more predictable schedules and greater work-life balance. This is a valuable differentiator to attract and retain talent. See Post 010 (“In addition to a professional wage, a collegial work environment, and freedom from business development pressures, lawyers in the managed service sector can refuse work outside the bounds of a 40-hour workweek.”).

4. Interconnectedness (+)

Innerconnectedness is “the degree to which the units in a social system are linked by interpersonal networks” (p. 412). The more interconnected the interpersonal networks, the greater the organizational innovativeness. This is because interpersonal networks tend to be very influential channels for sharing information, as trust and credibility levels are high. An organization can broaden and deepen these networks through the architecture of its office space and investing in regular inter-office meetings.

Interconnectedness is probably an attribute that legal service organizations tend to undervalue, wanting to avoid the lost time and expense of bringing professionals together for learning and socializing. Yet, I was recently surprised to learn that one of the major benefits of Milbank@Harvard, an intensive annual business training program for Milbank associates that lasts for several years, is that associates in the U.S., Europe, and Asia offices get to know one another in ways the spur trust, collaboration, and innovation. Ironically, these benefits were not part of the original business case for the program. They are just a welcomed second-order effect.  For additional information, see “An Update on Milbank’s Big Bet,” LWB, Nov. 13, 2013.

5. Organizational slack (+)

Organizational slack “is the degree to which uncommitted resources are available to an organization” (p. 412). The greater the organizational slack, the higher the level of organizational innovativeness, “especially for innovations that are higher in cost” (Id.).  Rogers speculates that larger organizations may be more innovative because the aggregate levels of downtime are bound to be greater. To use a sports metaphor, more shots usually result in more baskets.

Companies like 3M, Google, and HP have all adopted innovation strategies based on unstructured free time for knowledge workers. However, in most of the legal world, 100% utilization is the perennial holy grail. Exceptions are hard to find.

That said, the law firm Bryan Cave is an interesting accidental example. In the late 1990s, John Alber, the firm’s longtime innovation partner, returned to the firm after the sale of his logistics company. After fixing the firm’s failing IT system, Alber assisted on a client request for an expert system on international trade regulations (albeit no one called it that at the time). Although Alber had no formal staff, he found someone in the IT department with free time to help. The client was very happy with the resulting technology-based solution, thus starting a John Alber/Bryan Cave winning streak that lasted 17 years and resulted in numerous industry awards for innovation.  The IT staffer with free time was Chris Emerson, who went on to get an MBA. Emerson now runs Bryan Cave’s renowned Practice Economics Group (or PEG).

Another law firm example (from India, not the US) is Nistith Desai & Associates (NDA), a firm with numerous FT Innovative Lawyer awards in the Asia-Pacific bracket.  See long list .  Founded in 1989, the 200+ lawyer firm is based on the principle of continuous learning. Every lawyer, including the firm’s founder, is expected to be involved in the firm’s daily hour-long educational programming, both as a student and content provider. NDA essentially mandates slack time in service of creative solutions.  While virtually all law firms are reactive to client problems, NDA’s model is based on the proactive anticipate / prepare / deliver model show below. Not surprisingly, NDA uses value-based billing.

In late 2017, NDA will unveil a new R&D facility on a four-acre, state-of-the-art campus located on the outskirts of Mumbai. The new facility is referred to as the Blue Sky Thinking Center.  The founder of the firm, Nistith Desai, claims to have built NDA based on a composite of the very best professional services firms, including Wachtell Lipton. For an interesting discussion of the firm’s origins and operating principles, see Nistith Desai, “Management by Trust in a Democratic Enterprise: A Law Firm Shapes Organizational Behavior to Create Competitive Advantage,” Global Bus & Org Excellence (Sept/Oct 2009).

6. Size (+)

Part II of this series (Post 016) focused on the relationship between an organization’s size and organizational innovativeness. Roger viewed size as mostly a proxy or surrogate for other important factors, such as overall resources, complexity, and organizational slack.

Although increased size means additional layers of bureaucracy and higher communication overhead, the benefits can often outweigh the costs.  The highly innovative Corporate Legal Operations Consortium (CLOC) was certainly enabled by the size and scale of modern legal departments. See Post 005 (observing that many legal departments have become “the equivalent of a specialized law firm embedded inside a large corporation”). Likewise, Part II (016) presented compelling evidence that larger firms are ahead on AI and other practice management innovations.  This is almost certainly the result of more resources.

To drive home this point, imagine a firm allocating 2% of revenues to invest in people, process, technology, and data. In a firm with $1.7 billion in revenues (the average of AmLaw 1-20), that amounts to $34 million.  In a firm of $100 million (the average of AmLaw 181-200), 2% equals $2 million. Whatever the benefits of being smaller and more nimble, smaller firms are not well-positioned to attract and retain a critical mass of specialized talent. See, e.g., Update from Baker & McKenzie’s Chief Strategy Officer in Germany (during a day of onboarding, welcoming a “diverse group of lawyers, paralegals, business professionals, economists, data analysts, data visualizers, digital marketing experts”).

Yet, in my experience, size very much interacts with firm scope.  Specifically, when a firm narrows its areas of substantive practice, the innovation quotient can skyrocket despite not having AmLaw 1-20 revenues.  Littler Mendelson (labor & employment), Fragomen (immigration), and Chapman & Cutler (financial services) all fit this profile. Higher levels of innovation are enabled by focus and partner alignment — the firm rises and falls by its dominance in a single practice area. Cf. “Fragomen to Launch Unique Tech Development Center in Pittsburgh,” Leg Intelligencer, July 3, 2017 (suggesting that all companies, including law firms, are destined “to become a tech company in some capacity”).

III. External Characteristics of Organization — System Openness (+)

This category of variables is very simple conceptually: Does the organization proactively open itself to new ideas that could solve or mitigate important strategic problems? Compared to other industries, legal service organizations score low on this dimension.

Roger writes, “[m]ost organizations engage in an opportunistic surveillance by scanning the environment for new ideas that might benefit the organization” (Id. 422). When it’s working well, “Answers often precede questions” (Id.) What Rogers is getting at is awareness-knowledge, defined as information that an innovation exists(p. 173).  Awareness-knowledge is obviously impeded by closed systems.  Lawyers are disadvantaged here on several fronts:

  • Ban on outside investment. The Rule 5.4 prohibition on non-lawyer investment means that lawyers cannot co-venture with other professionals, thus cutting lawyers off from valuable perspectives and learning.
  • Culture of immediate productivity.  The legal industry, particularly in the US, is strongly oriented toward production. As a result, eclectic reading, conference travel, and sustained high-level training and programming is often viewed as extravagant, as budget targets are high and the time is non-billable. Unfortunately, this ethos carries over to many legal departments. In-house counsel are largely firefighters. All too often, they lack the time, resources, and mindset to prevent fires.
  • Lawyer-centricity. All too frequently, lawyers refuse to accord legitimacy to the views of people who don’t possess a JD (and hence are “non-lawyers”). This is a recurring theme among allied professionals who work in the legal industry. Pros: high pay. Cons: routinely ignored or dismissed by lawyers.

If a legal organization wants to be more innovative, it can change some of these factors through enlightened leadership. In the long run, lower levels of innovations are ruinous to entire organizations and industries. A fiduciary cannot responsibly ignore these issues.

Finally, whatever I’ve just written about law firms and legal departments (the topic is organizations) applies to legal education.  To this day, I am struck by the lack of academic participation in organizations and events on the front lines of change.  E.g., CLOC, ILTA, LegalWeek. The economic rules of modern practice are poised to get rewritten. Once this happens, a lot of cheese is going to get moved.

Relative Importance of Rogers Organizational Innovativeness Model

Assuming you’re an innovator or early adopter who wants to use Rogers’ models to improve your organization, the following question is relevant: “What is the relative importance of the organizational innovativeness model (analyzed above) compared to the rate of adoption model in Post 008 [see thumbnail to right]?”

We don’t have systematic empirical data to answer this question, but we do have one article worthy of mention.  In a study of 25 hospitals that were adopting 12 new technologies in a midwestern city,  the dependent variable (outcome) was a nine-point scale ranging from “staff being awareness of an innovation (1 point) through adopting and using the innovation regularly (8 points) to expanding and upgrading the new technology (9 points)” (p. 414).  In effect, the scale is measuring the progression through the entire innovation adoption process, see Figure in Part I (post 015), from the early stages of initiation to complete implementation success. This is an ideal dependent variable.

The study authors found:

  • 40% of the variance explained by the perceived attributes of the innovations,  with observability, low risk, and low complexity being key.
  • 11% of the variance explained by organizational innovativeness factors, with CEOs as innovation champions and larger hospital with more aggressive marketing strategies being the most influential attributes.

(p. 412, citing Meyer & Goes, “Organizational Assimilation of Innovations: A Multi-Level Contextual Analysis,” 31 Acad of Mgmt J 897-923 (1988)).

What’s my advice? In both models, systematically explore cost-effective ways to influence every variable in the direction that will make success more likely.  This is how applied research works.

What’s next?  See Legal Operations Skills During Your 1L Summer (018)

The graphic above, adapted from Rogers, Diffusion of Innovations (5th ed. 2013), shows the distribution of innovativeness among 324 German banks.  The innovativeness scale is a count of innovation adoptions from a universe of 12 interactive telecom innovations that were diffusing through the German banking sector during the early 1990s. To help distinguish the early adopters, more recent innovations were weighted more heavily.  The distribution is a textbook example of the Rogers Diffusion Curve. The long innovators tail exists because innovators are typically 2+ standard deviations from the mean on innovativeness.

Rogers uses the German bank study to illustrate numerous factors associated with higher levels of organizational innovativeness.  One factor is size.  Specifically, the largest German banks accounted for a large proportion of the innovators and early adopters.  In Rogers’ dataset, the correlation between innovativeness and total assets was a remarkable .75 (p < .01). Likewise, the correlation between innovativeness and employee headcount was an equally stunning .70 (p <.01). If readers are wondering why I am surprised, it is because the results are contrary to the standard trope that larger, more mature, and more financially successful companies — be it manufacturing, pharmaceuticals, or technology — struggle with innovation.  Indeed, this is the very problem Clayton Christiansen is trying to solve in the Innovator’s Dilemma (1997).

Post 016 is part 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.

This post is Part II of a three-part series on innovation in organizations. See Post 015 (Part I of series).  The goal in this post (016) is to unpack the counterintuitive relationship between size and innovativeness, as the strategic takeaways are far from obvious.

Deft Minds and the Size Effect

Everett Rogers had a remarkably deft mind that could puzzle through seemingly contradictory data and, with enough time and reflection, derive the most plausible causal story. Chris Zorn, my fellow co-founder at Lawyer Metrics (now LawyerMetrix), has a similar rare ability, which is to say I have some hands-on experience in this area. Drawing upon this experience, let me gently set reader expectations: What is important in Posts 015-017 is analytically subtle in a way that is not intuitive for most lawyers.

Let’s start with the size effect, which is present in Rogers’ study of German banks.  The size effect is relevant to lawyers because (a) there is credible, recent evidence that size is correlated with innovativeness in law firms; and (b) as Rogers acknowledges, the higher levels of innovativeness are, in most cases, substantially driven by the “covariants” of size, rather than size itself.  It is this second point (b) that requires the deft researcher’s mind, albeit it can definitely be grasped by patient smart people. So hang in there.

(a) The Altman Weil Law Firms in Transition Survey

The recent credible evidence of the size effect comes from the Altman Weil Law Firms in Transition 2017 survey, The survey polled managing partners and chairs at 798 US law firms with 50 or more lawyers. The response rate was 48%, including 50% of the NLJ 350 (ranking based on lawyer headcount) and 50% of the AmLaw 200 (ranking based on gross revenues).

Ron Friedmann in his post “Law Firm Profitability + Service Delivery: What the Altman Weil Survey Says,” Prism Legal, June 21, 2017, conducted a masterful secondary analysis of the survey results. One of the survey questions asked law firm leaders, “Technology tools that incorporate artificial intelligence (AI) and machine learning — like Watson and Ross — are beginning to be adopted by some law firms.  What is your firm’s stance on the use of legal AI tools?”  From the respond data, Ron generated the chart below:

This graphic shows a very strong relationship between law firm size and the use of AI.  Over 50% of the 1000+ lawyer firms claim to have begun adoption. Further, the effect is clearly linear, with the level of use and exploration steadily declining with firm size. Drawing upon what we learned in Part I (015), the orange bars reflect the “initiation” phase and the blue bars reflect “implementation.”  (Keep in mind that the implementation phase is fraught with difficulties and often ends in failure. See Post (015).)

Further, the relationship between size and innovation is not limited to AI.  We observe the same size/innovation effect in results that show the linkage between alternative fees and changes in how work is being staffed and delivered.  The graphic below is also courtesy of Ron Friedmann:

[Query: Why is linking AFAs to staffing and service delivery so innovative? Because the real value of alternative fees is to incentivize a re-design of workflow that (i) increases quality, (ii) speeds up delivery, and (iii) decreases cost. Otherwise, alternative fees become either a price discount or a gamble with poor or unknown odds. Stated another way, there is no point in hiring a pricing specialist unless you’re also going to hire specialists in project management and process improvement.]

(b) Covariants to size, not size itself

The graphics above reveal a clear and meaningful relationship between size and innovativeness. Yet, it does not necessarily follow that increasing size will increase innovation.  Correlation, as they say, is not causation.  Instead, it may be the case that other actions or activities need to be taken to improve or enable innovation; and for a variety of reasons, those actions or activities are more likely to occur in a larger firm.

To illustrate, let’s return to Rogers’ Organizational Innovativeness model, which is reproduced below:

In category II, Internal Characteristics of Organizational Structure, there are six factors (i.e., independent variables) listed, with size being number 6.  In Diffusion of Innovations, Rogers asks the question, “Why do researchers consistently find that size is one of the best predictors of organizational innovativeness?”  The first reason, writes Rogers, it that size is easy to measure with precision and thus “is included for study in almost every organizational innovativeness investigation” (p. 411).  Rogers continues:

Second, size is probably a surrogate measure of several dimensions that lead to innovation: total resources, slack resources (defined as the degree to which an organization has more resources than those required for ongoing operations), employees’ technical expertise, organizational structure, and so on. These unidentified variables have not been clearly understood or adequately measured by most studies. These “lurking” variables may be a fundamental reason for the common finding that size and innovativeness are related (Id.).

These “lurking” variables are covariants — i.e., attributes that generally move in a linear relationship with one another, either positively (height and weight) or negatively (age and memory).  Thankfully, when we have a lot of potentially meaningful variables that are correlated with one another, we can sort out what matters, by direction of effect and magnitude, through multivariate models.  In this case, factors 1-5 in Rogers’ model reveal the more valuable insights. We will carefully review those factors in Part III (017). But before we do that, let’s make sure we know enough about the underlying statistical models to avoid very serious errors in judgment.

Size is not a strategy

In the quoted paragraph above, Rogers is describing what statisticians call “omitted variable bias.”  This occurs when we leave something out of a multivariate model — like factors 1-5 above — and get a result that inflates or deflates the predictive power of the remaining variables (like size of firm).  The risk here is that folks running and interpreting the models are not sophisticated enough to know that they might have left something out and, if so, how to correct for it.  In turn, they drawn incorrect inferences that could form the basis for disastrously wrong strategy.

An example of the subtleties at play here can be seen in a law firm profitability model that Evan Parker (Managing Director of Analytics at LawyerMetrix) and I published in The American Lawyer. See “Playbook: Top 5 Strategies of the Most Successful Firms,” January 2017. As a first-cut analysis, size is positively correlated with average partner compensation: .53 with revenues, .28 with headcount.  And among many lawyers, there is a reflexive view that bigger is better, particularly in uncertain economic times.  See, e.g., Laurence Simons, “Number of US law firm mergers rockets,” Oct. 14, 2015. Yet, many other factors are bound to matter as well, such as (a) geographic presence in particular markets, (b) geographic concentration, (c) specific practice areas, (d) practice area concentration, (e) client concentration in specific industries, and (f) measures of reputation in lucrative financial services markets.

The graphic below shows the results of a model that includes all the factors just listed.

When reliable measures of these additional factors are included in a multivariate model, size (in this case, headcount) becomes a negative predictor of profitability at a level that is statistically significant.  In other words, when all these other levers of strategy are factored into the analysis, more lawyers means lower average partner compensation.  Further, the model explains approximately 80% of the variation in average partner compensation, which makes it highly unlikely that many firms can thrive using strategies significantly at odds with the model’s results. (For the prescriptive advice that flows from this model, please read the full article.  H/T Chris Zorn and Erik Bumgardner, both PhD social scientists, who helped build the model. )

I show the profitability model to make a simple but important point:  The use of statistics to guide strategy and operational decisions only becomes valuable when deep contextual knowledge of an industry and its problems is combined with quantitative competence and the ability to effectively communicate results. By dint of his deft mind and an amazing work ethic, Everett Rogers developed this ability in the realm of diffusion theory.  Outside my former colleagues at LawyerMetrix and a few others, this combination remains all-too-rare in the legal field.  Over the next generation, this gap is destined to close.  In the meantime, beware of charlatans selling into a naive and fearful market.  Also, don’t expect an internist to perform surgery.

Strategy that works = models + reasoning ability

For lawyers, there is a silver lining to all of this complexity: High quality empirical models — like the Rogers’ rate of adoption model (Post 008), the organizational innovativeness model, or the profitability model above — are nothing more than signposts that communicate what is more, or less, likely to matter. They don’t, by themselves, produce fully baked strategy.  Rather, strategy based on models requires the application of additional reasoning ability, of which lawyers have no shortage. Fortunately, sophisticated quantitative analysis is itself an innovation that is starting to diffuse through the legal industry social system.  See Post 004 (“Rogers’ core insight – one that is absolutely foundational for Legal Evolution readers – is that the diffusion of innovation is a process that occurs through a social system” (emphasis in original)).

In Part III (017), we can finally dive into the Rogers organizational innovativeness model with confidence that we can draw the right inferences and, in turn, use the model to set and execute sound organizational strategy.

What’s next? See Innovation in Organizations, Part III (017)

Every legal innovatorearly adopter and change agent shares a common, unifying desire: To speed up the pace of innovation within their organization.

This statement is true whether the context is a law firm, legal department, government agency, bar association, or law school. Over the years, I have commiserated with them all. Although they don’t know it, their disappointment is rooted in the fact that organizations are much harder to influence than individuals. See foundational posts 007 and 008 (discussing complexity and challenges of successful organizational adoption). For better or worse, organizations are everywhere within the legal ecosystem. Thus, it would be extremely useful to understand what levers to pull that can make them more innovative.

Post 015 is part 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.

Rogers Organizational Innovativeness Model

The model above, drawn from Everett Rogers’ Diffusion of Innovations Ch. 10 (5th ed. 2003), summarizes several factors that positively or negatively affect an organization’s level of innovativeness.  The model aggregates the results of numerous empirical studies that utilize multivariate regression analysis. However, just like the “rate of adoption” model discussed in Post 008, Rogers conveys the key findings using words rather than numbers. This is because, as an applied researcher, Rogers wants his analysis to be understood and used by a smart lay audience. See Post 001 (explaining difference between applied and academic research).

To illustrate, a multivariate regression model has some number of “independent” variables that predict some outcome we care about. We call that outcome the “dependent” variable. In the graphic above, the left side lists several independent variables while the right side contains a single dependent variable.  Thus, it can be said that the level of organizational innovativeness depends upon the values of several specific independent variables. In very practical terms, the model tells us what categories of change we should focus on to increase innovativeness within our organizations. And, by implication, it tells us what not to do.  It is very hard to overstate how useful this is. In the early days of any innovation, Rogers’ models (above and in Post 008) are both map and compass. It is just plain foolish not to learn how to use them.

That said, to have a fair chance of success, readers need additional background knowledge on the challenges of organizational innovativeness.  Thus, I am breaking this topic into three parts. Part I (Post 015) reviews the reasons why organizations tend to become bottlenecks for innovations that are crucial to their long-term survival. Part II (Post 016) discusses a very counterintuitive fact — that organizational innovativeness is strongly correlated with size, even in law firms. With this background information in place, Part III (Post 017) dives into the details of Rogers’ innovativeness model (above) with special emphasis on how it applies to legal service organizations.

Brief Review of Diffusion Theory

Innovators and early adopters are very interested in speeding up the rate of adoption of innovations. Everett Rogers’ rate of adoption model in Post 008 sets forth many factors that positively or negatively influence this outcome. The model groups these factors into five distinct categories: (I) Perceived Attributes of Innovation, (II) Type of Innovation-Decision, (III) Quantity and Quality of Communication Channels, (IV) Nature of Social System, and (V) Efforts of Change Agents.

As noted in earlier foundational posts, the first category, “Perceived Attributes of Innovation,” contains the most biggest levers for change. This is because the five attributes identified in the research — higher relative advantage, lower complexity, greater compatibility, use of pilot trials, and increased observability for prospective adopters — explain the majority of variation in rate adoption.  With sufficient quantities of time, money and effort, innovators, early adopters and change agents can alter these factors in the right direction. See Post 008 (urging those favoring innovation to “focus your attention on these five factors”); Post 011 (explaining “slow innovations” based solely on these five factors).

Yet, for those of us working in the legal industry, “Type of Innovation-Decision” is equally important. This is because Type of Innovation-Decision is essentially distinguishing between individual and organizational adopters. And the latter are (a) much more common and economically influential within the legal industry, and (b) more likely to result in adoption failure, particularly in the absence of significant planning and intervention.

Innovation in Organizations

As noted in Post 008, there are three types of innovation adoption decisions: (1) optional, (2) collective, (3) authority.  If the adoption decision is optional, it’s akin to market forces: individuals are free to take it or leave it (think Smartphone, Uber, or wearables). In contrast, when an organization is the adopter, either collective or authority adoption decisions apply.

Collective is the most problematic decision type, as a collective adoption decision requires some level of group consensus (think law firm partnership or law school faculty).  Authority adoption decisions are, in theory, easier because a single authority can decide (think CEO or GC). But successful implementation still depends upon overcoming the opposition of the laggards and late majority. See Post 007 (defining adopter types).  Indeed, “massive passive resistance” (MPR) awaits the executive who underinvests in team buy-in. See Post 008 (defining MPR and discussing its pervasiveness in corporate legal departments).

In summary, if you work in the legal industry and want to bring about beneficial change, your success largely depends upon your ability to work with, or within, organizations.  This is because good ideas, unsheltered by a well-informed sponsor, are no match for the strong anti-change headwinds created by organizational decision making. This is a structural feature of the industry that consistently impedes organizational innovation, albeit innovation is never foreclosed — not unless you and others give up. For this ultramarathon journey, Rogers’ models are essential survival tools.

That said, an important caveat is in order.  The predictive power of Rogers’ organizational innovativeness model is much lower than the Post 008 rate of adoption model.  One of the main reasons for the lower predictive power is that factors that make an organization more likely to innovate are simultaneously factors that tend to undermine successful implementation.  Specifically, the likelihood of an organization deciding to adopt an innovation is positively correlated with (i) lower centralization of authority, (ii) higher complexity of work, and (iii) less formalization of procedures. Yet, these three attributes are negatively correlated with successful implementation.

Obviously, very few organizations have the level of self-awareness necessary to make appropriate mid-stream adjustments.  Instead, leaders try to power through obstacles with a one-size-fits-all management approach. In legal organizations in particular, when an innovation fails, we place the blame on lawyers’ contentious, skeptical, autonomy-loving nature. This is a bogus uninformed analysis.  Fortunately, this pathetic cycle can be broken through careful planning and leadership.

Initiation versus Implementation

Below is a graphic that summarizes the five stages of an innovation adoption process in an organization. Notice that the adoption decision is made only after a period of agenda-setting (Stage #1) and matching (Stage #2). Thereafter, the painstaking work of implementation begins.

Note also that the model above essentially assumes that the innovation process is managed by an existing bureaucracy, ostensibly just one of many managerial duties.  The process begins with “Initiation,” which consists of “all of the information gathering, conceptualization, and planning for the adoption of the innovation, leading up to the decision to adopt” (pp. 420-21). After the leadership makes the adoption decision, the organization commences the “Implementation” phase. This consists of “all the events, actions, and decisions involved in putting the innovation to use” (p. 421).  When the innovation is so integrated in the organization that it becomes routinized, it “loses its identity” as something new. In essence, the innovation has merged into the status quo.

As noted above, several organizational attributes that support successful initiation become sources of weakness during implementation. This should be very humbling to legal innovators and early adopters who likely excel at initiation but are prone to underestimate the hardships and complexities of successful implementation. This tendency is explicitly discussed in the Silicon Valley classic Crossing the Chasm by Jeffrey MooreMoore’s solution is simple: when the time comes, replace the innovator/early adopter management team with more mainstream operators whose skill set is execution rather than ideation. For the opposite situation — when an organization is very good at setting and following procedures but struggles to innovate — Rogers suggests a skunkworks as a potential solution.

Unfortunately, there is good reason to believe that law firms, the longstanding cornerstone of the legal industry, reflect the worst of both worlds. The partnership structure hinders both successful initiation and implementation, not to mention making a timely adoption decision. Cf. Bruce MacEwen, Tomorrowland: Scenarios for Law Firms Beyond the Horizon (2017) (discussing at length the business liabilities of governing a law firm as a partnership; suggesting that the partnership model will become a source of numerous law firm failures). Yet, this is less a reason for hopelessness than cause for careful study and preparation, at least among those who intend to stay in the industry beyond the short to medium-term.  Society has many hard problems. This one belongs to lawyers.

There is more to unpack in Parts II (016) and III (017), which I’ll post shortly.

What’s next? See Innovation in Organizations, Part II (016)

The global law firm Gowling WLG has just launched a platform that automates document production for a private placement offering.  The video above does a remarkably good job of explaining how the product (called Smart Raise) works.  Far from scary and technical, the innovation comes across as simple and inviting. Quite an accomplishment in two short minutes.

Gowling WLG is a global law firm that operates in Canada, the UK, Continental Europe, the Middle East, and Asia. Although it doesn’t have a US office, US firms ought to take notice, as the Gowling’s rollout is a good illustration of two trends starting to take hold in the legal ecosystem:

  1. The use of complex technical sales methods that include market preparation activities as part of a long-term strategy;
  2. New pricing models that connect together commodity and bespoke offerings in ways that thin out weak competitors.

Complex Technical Sales

This sounds like an oxymoron, but complex technical sales is about simplification. For example, when a new innovation is launched, prospective clients don’t understand its technical aspects. Thus, they have a reasonable fear of making an expensive mistake.  Closing this knowledge gap is costly, particularly in the B2B space, because it takes time and cognitive effort.  Showing the product in action in often the best way to reduce this load. Cf. Post 008 (explaining how lower complexity and higher trialability and observability increase innovation adoption).

In contrast to the rest of Law Land, Gowling WLG has head start. Its Leader of Innovation Initiatives is Mark Tamminga (pictured right), a long-time partner who pioneered the use of practice automation tools in building the firm’s Recovery Services practice. Through automation efforts that began over a decade ago, Mark and his colleagues built a series of products and services that captured the Canadian market. The practice has become very profitable and highly defensible.

One of the things that Tamminga and his colleagues understand is that you start the sales process by emphasizing simplicity and ease of use rather than technical prowess. This is hard for innovators because it requires extra steps.  The natural tendency is to jump to the most advanced features in an attempt to impress prospective clients. The result is typically confusion. Yet legal entrepreneurs make this mistake over and over again. See Post 008 (discussing how immersion in technical details makes it difficult to see the world through the eyes of the end user).

Finally, a short video can be an extremely effective sales tool because it is asynchronous and puts the viewer in control. If it’s done well, qualified buyers find you.  I first watched the video via a LinkedIn post.  In the year 2017, LinkedIn is a very important “communication channel.”   See Post 008 (discussing knowledge awareness and the adoption decision; discussing how more and better communication channels speed up adoption).


Smart Raise reduces the volume of hourly work. It then seemingly compounds the financial hurt by showing the ease of the new process. Skeptical lawyers are bound to ask, “How does this support revenue production?”

The answer is that it probably doesn’t, at least not directly or in the short-term.  Instead, it signals expertise.  If Gowling WLG is smart enough to automate a substantial portion of the private placement offering process, it’s likely they’re experts on the remaining complex issues.  “Perhaps we would give them a call.”  This is a market positioning strategy based on a realistic assessment of where the legal market is headed.  As Susskind has written, “If [cannibalization of legacy offerings] is going to happen, you should be one of the first to the feast.” See Tomorrow’s Lawyers 128 (1st ed. 2013).

What’s next?  See Innovation in Organizations, Part I (015)

glasses_diffusionAre rapidly adopted innovations more valuable and important than innovations that take a long time to take hold? Not necessarily.

Post 011 is part of LE’s foundational series on diffusion theory.  Here’s the key point:  Speed of adoption is not a reliable guide for an innovation’s importance. In fact, competitive advantage is much more likely to lie among slower ideas where innovators focus on several key factors to accelerate the rate of adoption.

It is difficult to accept an insight this counterintuitive. Thus, we need an illustration. Continue Reading Fast versus Slow Innovations (011)

Below are two beliefs I carried with me for many years.

  1. In all human endeavors, incentives exert a powerful effect on behavior
  2. Within the legal industry, the billable hour is the primary impediment to innovation and efficiency

efficiencyengines2Belief 1 still stands. But belief 2, which I viewed as a corollary of 1, recently fell like an oak tree. This shift in worldview happened during my research for Efficiency Engines, a story on rise of legal managed services.  During visits to several managed service facilities, I witnessed quantum leaps in legal productivity for relatively sophisticated legal work.  And in each case, the work was priced and sold by the hour.

The biggest value of visiting an innovator is the possibility of learning something that disconfirms one’s own belief system.  A character in a John le Carre novel once quipped,  “A desk is a dangerous place from which to view the world.” That’s good advice for those seeking to understand today’s legal industry.

A better theory

After the fall of belief 2, I needed a theory on innovation and efficiency that incorporated my new learning. Here is what I came up with:

The billable hour can be harnessed as a powerful tool for innovation and efficiency.  This can be accomplished by: (a) selling work with a clearly stated budget, (b) paying your workforce by the hour, and mostly crucially (c) managing quality and the risk of cost overruns through world-class project management and process improvement.  A service provider who reaches scale and establishes a brand based on both quality and price can lock-in a profitable business with a long-term competitive advantage.

In a nutshell, this is the business logic of the legal managed service model.  The private equity/venture capital crowd have found it sufficiently compelling to fund it with hundreds of millions of dollars.

This post (010) situates the managed service model within a more fundamental theory of professional service firms.  It also explains how the managed service model is successfully pulling on the levers of diffusion theory, particularly compatibility, to accelerate its growth. Cf. Post 008 (adoption more likely if innovation is compatible with existing practices and norms). Post 010 then offers a few thoughts on the adoption of managed service methods, which is something separate from the managed service business model. Regardless of who wins and who loses, the methodology pioneered by managed service providers represents an innovation that is diffusing throughout the legal industry.

Balancing three goals inside two markets

The fundamentals of the professional service business model are explained in David Maister’s Managing the Professional Service Firm (1993) (chapter 1).  As shown in the diagram below, firms operate in two markets: clients and talent. For the owners of the firm, profitability is certainly the ultimate goal. Yet, this outcome is entirely derivative of (a) providing outstanding service to clients (market 1), and (b) offering high-quality career opportunities to a talented workforce (market 2).  Thus, under Maister’s theory, the professional services firm is always balancing three goals in the context of two markets.


Although this model looks simple, it’s easy to get wrong.  Firms that fail to understand their own cost structure are at risk of substituting revenues for profits.  As recently observed by Bruce MacEwen, this is why so many firms overpay for lateral partners.  See Opinion: It’s time to re-think the price war on talent.  Likewise, in the client marketplace, the growth of national and international businesses has reduced the importance of client relationships based on geography and increased the importance of best-in-class talent in specialized areas. On some level, law firms know this because they have jettisoned the “general service” descriptions that were so common 20 years ago.  However, there remains considerable internal resistance to closing down out-of-scope practice areas and offices. Cf. Henderson, “How to Take Market Share,” American Lawyer (Oct. 2015) (discussing ruthless focus needed to become market leader based on quality).

Perhaps its obvious that the client marketplace has become differentiated. Yet, differentiation is also occurring in the legal talent market — a point I did not fully grasp until the belief 2 oak tree fell.  Beyond preferences based on practice area, some lawyers are drawn to BigLaw for reasons of money and prestige.  But other lawyers — with the same level of intellect and pedigree — are looking for a different type of work environment.

In the course of writing Efficiency Engines, I asked Jane Allen, Founder and Board Member of Counsel on Call, how the company selected its talent.  Jane described a behavioral interview process that focused on a profile very different than a BigLaw rainmaker:

  • Loves the technical aspects of law
  • Wants to be part of a team
  • Does not need to be in charge
  • Is comfortable learning new technology
  • Places a high value on work-life balance

In a large law firm, a lawyer who fits the above profile would likely be diverted to an “off-track” position. Yet, in a managed service firm, these same lawyers are the core building blocks of the business.

Using the billable hour to balance the legal talent market

The managed service model is tapping into the large segment of the legal talent market that wants work conditions very different from BigLaw.  At the top of the list is work-life balance.  In addition to a professional wage, a collegial work environment, and freedom from business development pressures, lawyers in the managed service sector can refuse work outside the bounds of a 40-hour workweek (or, in some cases, pre-negotiated shorter weeks).  Further, if the managed service firm needs additional hours, the lawyers are paid for their time. These constraints force managed service providers to build remarkably tight systems for project management and process improvement.

In large law firms, the incentives run in the opposite direction.  Once the firm locks in its labor costs in the form of high guaranteed salaries to associates, it benefits financially from hours that are billed during nights and weekends. Work that is unplanned, unpredictable and urgent is often the most profitable.  It is any wonder that firms would be reluctant to invest in technology and systems that would make client work more transparent and thus more manageable?  Some legal work will always be unplanned, unpredictable and urgent. But not all legal work. Clients are slowly figuring this out.

In all three of the managed service facilities I visited (Counsel on Call, United Lex, and Axiom Law), I encountered the same thing: lawyers who enjoyed working in a team-based environment where efficiency and innovation were valued.  Indeed, being part of a continuous improvement process appeared to be a key component of their job satisfaction. They enjoyed the challenge of exceeding their clients’ expectations. In turn, their employers benefited through higher volume that included a built-in profit margin.  Note the careful balancing of Maister’s three goals.

Leveraging cultural compatibility

One of the reasons that the legal managed service market is growing at 15-20% per year is that most managed service providers have packaged their offerings in a way that is culturally compatible for legal department clients.  As noted in Legal Evolution’s foundational posts, particularly Post 008, compatibility is an important driver of innovation diffusion.  When an innovation is highly compatible with a social system’s existing practices and norms, adopters can obtain the benefits while staying within their comfort zone.

In the managed service model, there are two major touchstones of compatibility.  First, the work is still being done or supervised by lawyers with large firm experience and strong academic qualifications — lawyers just like the in-house buyer. Second, and perhaps most crucially, the work is sold in billable hour units, which is the only system of measurement that all lawyers understand.  Pricing by the hour invites a direct cost and quality comparison with law firm associates, which casts the managed service provider in a very favorable light.

It near impossible to overemphasize the importance of cultural compatibility.  I have witnessed other highly innovative legal services providers who have refused to share the amount of lawyer effort needed to produce their outstanding work product. Instead, they hold to a pricing model based on terabytes of data or overall scope of work.  Most in-house lawyers lack the time and interest to get into the weeds of a cost and quality comparison.  An easier sell is pedigreed lawyers working by the hour in a process-driven environment.  Cf. Post 008 (discussing crucial importance of relying on the buyer’s rather than the innovator’s perspective).

NewLaw is not as new as we think

Managed service companies like Counsel on Call, Axiom, UnitedLex, Pangea3, and Elevate are often put into the NewLaw bucket.  I don’t dispute the categorization, except to point out that it’s our awareness of alternative models that is new, not the companies themselves.  Axiom and Counsel on Call both launched in 2000. Pangea3 was founded in 2004 and sold to Thomson Reuters in 2010.  UnitedLex opened in 2006.  Although Elevate is a relative newcomer (opening in 2011), its CEO, Liam Brown, founded another NewLaw company, Integreon, in 2001. Further, he began in the NewLaw space nearly 20 years ago, starting Conscium in 1998, which pioneered virtual deal rooms for lawyers and investment bankers.

Sally_crab_labelWhy does “new” takes so long in law?  Like the Galapagos Islands at the time of Charles Darwin’s landing, the legal sector operates in peculiar and isolated ecosystem that bears only a distant resemblance to the economic mainland. Under the ethics rules, lawyers can’t co-venture with professionals from other disciplines. If you can’t co-venture, opportunities to share knowledge, know-how, and perspective are inadequate for the challenges being faced. As noted in Post 008, this dramatically slows the diffusion of innovations within the legal social system.

Yet, let’s not confuse slow change with no change.  Very few lawyers appreciate the amount of outside investor money that has arrayed itself to profit from the inefficiencies of law firms. These capitalists are waiting longer than usual for their desired return (7-10 years are the usual outer limits for PE and VC investors).

However, they are also learning more about the legal industry and normalizing their involvement in the legal supply chain.

I first interviewed Mark Harris, founder and then CEO of Axiom Law, back in 2013.  At the time, I had the mindset that Harris was running a legal start-up.  But by then, Harris was 13 years in.  Axiom was less a start-up than an ultramarathon. (In late 2016, Harris became Axiom’s Executive Chairman, handing over the CEO reigns to Elena Donio, formerly President of Concur, a $1 billion business software company.)

The long game

During that 2013 interview, Harris laid out the long game analysis — the same analysis he was then using to sell services to Fortune 500 general counsel.

On a whiteboard, Harris drew a set of diagrams that segmented legal work into three groups: extraordinary events, experienced demand, and efficiency demand. In the past, corporate clients viewed virtually all legal work as risky and complex. Thus, they outsourced virtually everything to law firms. Over time, as in-house lawyers took over the role of buying legal services, they began unbundling legal work and insourcing some of it to themselves. This fueled the rapid growth of corporate legal departments. See Post 003 (showing the 20-year grow trajectory of in-house legal departments). In its early stages, this was pure labor arbitrage. Yet, as in-house lawyers develop more sophisticated sourcing strategies, Harris explained, the extraordinary events and experienced demand segments will shrink while the efficiency demand grows.  See diagrams below.


A huge part of moving work from the top of the pyramid to the bottom is introducing systems and process that can partially supplant the clients’ deeply held faith in elite brands and credentials. This challenge is truly an ultramarathon, and only a handful of managed service providers are running it.  If Harris and his investors are correct, and they play the long game correctly, they will be among a relatively small number of competitors who divide up a large portion of the green triangle above.

How does this end?

One scenario is that extraordinary events work consolidates with a small number of firms that attract brain surgery-type talent. Think the Wall Street elite plus Latham, Kirkland, Gibson Dunn and a few others.   A tranche of complex and strategic work remains in-house. See Post 003 (reporting that more than 105,000 lawyers work in-house).  And a large portion of the remaining pyramid goes to large managed service providers who specialize in high-volume process work. These companies could go public or be owned by the BigFour accounting firms. Think Accenture. (See Efficiency Engines for how this is possible under the existing ethics rules.)

Yet, there are alternative scenarios that are likely to co-exist with the ambitions of the managed service sector. For example, it is likely that some US and UK law firms will emerge as global “general contractor” firms. They will earn a premium for their supply chain expertise, from captive LPOs to AI-enabled automation to high-stakes court room practice. Think Allen & Overy, Herbert Smith Freehills, Baker McKenzie, Hogan Lovells, and a few others.

In the labor & employment space, Littler Mendelson and Ogletree Deakins have already incorporated many managed service methods into their businesses. They tend to get ignored by the legal press because their profits per partner are lower than the rest of BigLaw.  Yet, managed service methods are the equivalent of a moat around the franchise. Would you rather have $2 million this year, or $500,000 per year for 20?  This isn’t a lottery hypothetical. It’s a strategy choice made by lawyers with large L&E practices.

Likewise, many elite US law firms have relatively large alternative staffing operations that are deployed in massive M&A deals and Big Game litigation. To protect their brands, these firms seldom publicly tout these capabilities. Yet, within the confines of a client pitch, the existence of these capabilities helps protect work at the top of the pyramid. In this context, bundling is likely more valuable to the client than fine gradients of cost and quality.  Although currently run primarily as support units for high-end work (at least for now), many of these operations are quite profitable based on their own P&Ls. Thus, in some segments of the market, the rich are only getting richer.

How does this end?  Obviously, the work methods of managed service providers are innovations that are diffusing throughout the legal industry.  Large scale disruption of the legal industry by managed service companies seems less likely that successful co-existence with law firms who adopt similar work methods. The buyers, after all, are mostly lawyers working in legal departments.  That said, a lot of law firms are far behind on the methods front.  It’s a difficult slough for law firm leaders because the required investments don’t produce higher profits this year or next. Instead, the payoff is long-term relevance and survival, a topic many senior partners put in the same category as global warming.

At some point, legal education will begin to grasp the import of managed service methods in helping law grads obtain high quality employment.  But that is a topic for another day.

What’s next?  See Fast versus Slow Innovations (011)

Rogers Figure 6-1

If you have been readings the foundational posts for Legal Evolution, this installment (Post 008) will reward you with something of clear, practical value: An empirically grounded model that identifies specific factors that influence the rate of adoption of an innovation.

What is the specific practical value?

  • If you are an innovator, this model can be used as a functional checklist to assess whether your innovation is ready for market; and if so, where to focus your limited bandwidth to maximize the odds of successful adoption.
  • If you are an early adopter, this model helps you assess whether you want to cast your lot with a specific innovation or, instead, hold your powder until the innovation is more developed or another innovator produces something better.

bookdiffusionsofinnovationsThe graphic above is adapted from Chapter 6 of Everett Rogers, Diffusion of Innovations (5th ed. 2003). As noted earlier, this is one of the most cited books in all of the social sciences.  Although the graphic does not look quantitative, it is actually a user-friendly presentation of a multivariate regression model.

The left column of the graphic lists five groups of variables that influence the rate of adoption of an innovation.  The rate of adoption is the dependent variable, which is listed in the right column. The rate of adoption is a dependent variable because its value depends on the value of the other variables. In the parlance of statistics, the other variables are called “independent” or “predictor” variables. The five groups of variables on the left have been shown by Rogers and others researchers to be valid and reliable predictors of the rate of adoption of an innovation.

If you’re investing a lot of time and money in an innovation, this is a profoundly useful model.

I. Perceived Attributes of the Innovation

Among the five categories of predictor variables, the most important is the first category, the “perceived attributes of innovation”.  Rogers reports that between “49 and 87 percent” of the variance in the rate of adoption can be explained by five attributes: (1) relative advantage, (2) compatibility, (3) complexity, (4) trialability, and (5) observability (p. 221`).

Note that this is a list of perceived attributes. Perceived by who?  The target adopter.

There are many ways to fail as an innovator, but one of the most common is failing to adopt the perspective of the end user.  Rogers begins Chapter 6 with a telling quote: “If men perceive situations as real, they are real in their consequences” (quoting W.I. Thomas Florian Znaniecki, The Polish Peasant in Europe and America 81 (1927)).  Adopting the perspective of the end user is an exercise in empathy. This can be very difficult for the innovator, who if often deeply immersed in the technical workings of the project. He or she is at grave risk of falling in love with features that are of little practical value to the target end user.  Cf. Curse of Knowledge (cognitive bias that afflicts experts).

Rogers distinguishes between “objective rationality” relied upon by the expert who carefully reviews data and “subjective objectivity as perceived by the individual” (p. 232). The latter is what is relevant to adoption. Most of us try to generalize based on what makes sense to us. Instead, we need to spend all of our time studying someone very different and seeing the world through their eyes.  Acquiring this skill set take effort, self-awareness and humility. What you think or I think literally does not matter.

Here is a summary each perceived attribute.

1. Relative Advantage

Relative advantage is “the degree to which an innovation is perceived as being better than the idea it supersedes” (p. 229). The advantage could take the form of economic benefit, an increase in social status, or both.

It is worth reinforcing the user perspective here.  I have seen numerous legal start-ups struggle and fail because the founders were pitching efficiency to law firms.  Although clients complain about high legal bills, the law firm that makes a large capital investment in efficiency has a very difficult time capturing a reasonable portion of the value created. See Henderson, The Legal Profession’s ‘Last Mile Problem”.  When a salesperson makes the efficiency pitch, they are generalizing from their world, not the world of the prospective law firm adopter.  Quality, on the other hand, has a much stronger appeal to lawyers, primarily because it is associated with lower risk. We’ll go deeper on this point in a future post. See also the discussion below regarding trialability and Practical Law Company’s successful entry into the US legal market.

2. Compatibility

Compatability is “the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters” (p. 240),  The phrase “disruptive innovation” undoubtedly helped Clayton Christensen sell hundreds of thousands of copies of his famous book, The Innovator’s Dilemma.  However, it not a phrase that will endear you to the vast majority of adopters who have zero interest in having their livelihoods disrupted. The touchstone here is familiarity. The closer we hew to what is known and accepted, the lower the levels of perceived uncertainty.  That is a zone where your innovation has a chance of getting adopted.

To illustrate this point, Rogers notes that care should be taken in naming an innovation, as the name often carries influential connotations that can undermine relative advantage (pp. 250-51). Note that compatibility is often treated as an empirical question. “Positioning” research looks for optimal associations with accepted products or services in the adopters’ environment. Likewise, “acceptability” research seeks to identify factors that tend to make or break an adoption decision. Compatibility research is quantifying the emotional, subjective reactions of potential users.  The only thing close to this in law are focus groups designed to simulate juror reactions. The best trial lawyers use this methodology in preparation for trial. (E.g., Fred Bartlit once told me he used eight separate mock juries for case he was trying. No surprise — he won.)

3. Complexity

Complexity is “the degree to which an innovation is perceived as relatively difficult to understand and use” (p. 257). Whereas relative advantage and compatibility exert a positive influence on adoption, complexity has a negative effect. The higher the perceived complexity, the lower the rate of adoption.  Thus, it is not surprising that successful tech companies obsess over user experience (UX) and user interface (UI).  Design thinking often adds value by removing unnecessary and cumbersome complexity.  See, e.g.,  Design Thinking Comes of Age, HBR (Sept 2015). The graphic below illustrates this point.  The product on the left was designed for the end user; the product on the right stayed too much within the perspective of the engineer.


For the curious, the iOS Human Interface Guidelines are published online here.

4. Trialability

Trialability is “the degree to which an innovation may be experimented with on a limited basis.” Rogers continues, “New ideas that can be tried on the installment plan are generally adopted more rapidly than innovations that are not divisible” (p. 258).

Several years ago, the original US sales team of Practical Law Company (PLC) shared with me how they successfully established their US operations. PLC sells annotated forms and practice guides for sophisticated corporate work.  Although PLC had a complete lock on the UK market, they had no US customers when they landed in New York in 2007. Through trial and error, they soon discovered that the single best way to overcome the skepticism of US lawyers was to put them in front of a computer and let them use the PLC product.  After experiencing the product’s immense utility, subscriptions were relatively easy to close. By the time PLC sold to Thomas Reuters in 2013 (for a price between $300-450 million), PLC had 700 legal departments and 86 percent of the AmLaw 200 as customers.  See Thomson Reuters to Acquire Practical Law Company.

Trialability was certainly relevant to PLC’s rate of adoption.  However, the PLC product line also had a huge relative advantage over the incomplete, out-of-date, and unannotated internal forms they were replacing. Trialability enabled perspective adopters to experience the quality difference. To enable high quality decision-making, it is important to keep analytically distinct each of the five perceived attributes of an innovation. Trialability is different than overall relative advantage, though both levers are important.

5. Observability

Observability is “the degree to which the results of an innovation are visible to others.”  Observability is very much related to relative advantage and trialabilty. If an innovation is trialable for early adopters, its relative advantage can be more easily observed by other parts of the social system. See foundational posts 004 and 007.

The importance of observability is documented in an early and influential diffusion study that focused on adoption of hybrid seed corn in two communities in Iowa. See Ryan and Gross (1943). What drove adoption for the vast majority of farmers was not the technical sales pitch made by college-educated agronomists. Rather, it was the observably better corn growing on their neighbor’s land. The technical pitch was primarily relevant to the innovators and early adopters in the social system, who set the adoption cycle in motion. The average time between “knowledge awareness”  and the “adoption decision” (technical terms of art in diffusion research) was a fairly lengthy six years. See chart below.


I believe the above chart is very relevant to all the hype regarding how artificial intelligence is going to revolutionize the legal field.  AI does not have a relative advantage that is easy to observe. Mere efficiency (an obvious and potentially observable advantage) is not good enough for many lawyer-adopters, as efficiency currently creates collateral business problems that most clients fail to acknowledge. See Henderson, The Legal Profession’s ‘Last Mile Problem”. AI is also very complex.  These perceived attributes are going to impede AI’s rate of adoption in law.  Many smart people in legal start-ups are trying to use design principles to solve or mitigate these issues. Yet, the best of them know they are climbing a very steep mountain.

Summary of perceived attributes

As noted earlier, the five factors above explain 50% or move of the variance in adoption rates. Stated another way, if you have an innovation you would like others to adopt, focus your attention on these five factors. This simple, empirically derived piece of guidance is one of the reasons that applied research can be so powerful.

Four other categories of variables influence the rate of innovation adoption (II to V in the graphic above). Most of them cannot be significantly influenced by the efforts of innovators, though they are highly relevant because they enable an innovator or early adopter to handicap the odds of market acceptance. In other words, they bear on practical questions like, “should I put more money in?”; “should I sell now?”; “should I fold the business?”;  “how long is adoption likely to take compared to other business contexts?”  Thus, let’s finish the model with a eye toward how it applies to the legal industry.

II. Type of Innovation Decision

At some point after a potential adopter becomes aware of an innovation and weighs its relative advantages, a decision will be made to accept or reject.  There are three types of innovation decisions.

  1. Optional. Basically everyone in the social system is free to decide for themselves. This is market-based.  E.g., smartphones, healthier foods, Facebook.
  2. Collective. Through agreement or strong cultural norms, adoption requires a consensus of the entire group. This mechanism has the most negative impact on rate of adoption.  It is also the mechanism that best describes the typical law firm partnership.
  3. Authority.  One decision-maker makes the decision for the entire social system. E.g., corporate executive; government official. Although authority innovation-decisions are generally the fastest, they run the risk of being “circumvented by members of a system during their implementation” (p. 29).

The type of innovation decision is very relevant to the legal industry.  Back in 2015, I organized a panel of legal innovators for the ABA Center on Professional Responsibility.  One of the panelists was an venture capitalist who was an investor in Modria, an online dispute resolution service that uses an automated dispute resolution methodology similar to those used by eBay and PayPal. As a former associate at a prominent Silicon Valley law firm, the VC helped pioneer some of the early investment in legal tech, albeit not all investments worked out well. In front of an audience of 300 law firm lawyers, the VC stated that he would never again invest in a technology that was designed to be sold to law firms because “law firms don’t made decisions like rational businesses.”

Placed into the Rogers decision framework, the VC was frustrated by the collective decision-making process of law firm partnerships.  From far away, it looks irrational. Up close, however, it’s justified as culture.

That said, it is very easy to confuse the long sales cycle in law with the more fundamental issue of relative advantage. For example, many partners hear their clients clamoring for greater efficiency, and hence are willing to listen to sales pitches. Yet, the partners don’t know to how to honor the clients’ wish because it requires to them to simultaneously (a) pay for, and learn how to use, expensive, complex innovations, and (b) endure a loss in revenues because the clients insist on using hourly production to measure value. Insistence on hourly billing, or shadow billing of AFAs, is a great example of a compatibility restraint that impedes innovation.  The legal profession has a very serious last mile problem.

type 6 clientI am confident that the rise of the legal operations role within legal departments is substantially due to the authority innovation-decision advantages of having a single general counsel who possesses traditional executive perogatives. That authority is increasingly being delegated to legal ops professionals who have a clear directive for better, faster, less expensive. See Post 005 (discussing CLOC and the rise of the Type 6 client).

Yet, in the best of circumstances, change management in legal departments is no cakewalk. My friend Jeff Carr, formerly GC of FMC and now at Univar, acknowledged the challenge of MPR, or “massive passive resistance”, in implementing necessary change.  Having achieved remarkable financial results through his ACES model, Jeff became a fierce proponent of general counsel as leader, a discipline and topic completely foreign to most lawyers.

jeff carrIf you ask Jeff about the key to successful implementation of change — e.g., requiring every in-house lawyer in his department to regularly score outside counsel using a standard grading rubric — he is likely to point to his face:  “See this look. This is the look of me not caring. These metrics are necessary for the functioning of the company. Please do your job.”  Another prominent general counsel who successfully transitioned a large legal department away for the billable hour, and has served as an influential advisor to many general counsel, acknowledged to me that such a transition could easily entail the resignation or dismissal of roughly 30% of the department — that was the volume of turnover in his department and other successful legal department transitions he has observed.  Change is hard, even for highly educated professionals.

Suffice it to say, whether its collective innovation-decisions, or the reluctance of lawyer-leaders to stay the course because we have little training or experience as managers or leaders, the legal industry presents special challenges for innovation adoption and diffusion.

III. Communication Channels

The rate of innovation is positively influenced by the number and quality of communication channels. This is true in two ways. First, early adopters may become aware of an innovation through a new communication channel (e.g., the trade press or an industry conference).  Second, more and better communication channels make innovations more observable to the rest of the social system. Not only does this facilitate economically driven adoption decisions based on relative advantage, it also works to set and reinforce group norms. Thus, a subset of adoption decisions will be socially driven by a desire to fit in or avoid feeling left behind or out of date. Again, diffusion of innovations is a social process; incentives are present, but they are often more social than economic.

Not surprisingly, the advent of new communication channels like print journalism, radio, television, and the Internet have all increased the pace of innovation adoption.  The rise of mass media is one of the most important areas of study in diffusion research.  Following the publication of the first edition of Diffusion of Innovations in 1962, Everett Rogers, who was a sociologist by training, joined faculty of Department of Communications at Michigan State University. At the time, MSU was the leading institution in this fledgling academic discipline.

Communication channels are important to innovation because they increase the flow of information. Yet, factors that influence total flow are different than the factors that influence the persuasiveness of the information content.  For the latter, relative advantage, compatibility, complexity, trailabilty, and observability remain the touchstones.

curveLegal Evolution is designed to be a new communication channel that will help accelerate the pace of legal industry innovation.  As noted in Post 001, this publication is an experiment in applied research.  To be successful, I need the readership of legal innovators and early adopters — the light blue portion of the curve.  I hope this elite readership enjoys Legal Evolution’s clean layout and the absence of banner ads. If you have the stamina to read a 3,500 word foundational post, these niceties are the least I can do.

By the way, what is the likelihood I could adequately reach my target readership if I published this analysis in a traditional law review?

IV.  Nature of the Social System

In Rogers’ model, the nature of the social system is the fourth category of variables that can impact the rate of adoption of an innovation.

For the legal industry, the nature of the social system generally impedes innovation adoption. The most established, influential, and prestigious portions of the legal profession — large law firms, the federal judiciary, legal academia, and the ABA — tend to be traditional bound and skeptical of change that does not initiate with them.

Part of this conservative ethos may be the product of Rule 5.4, which has been adopted in some form by every state.  Rule 5.4 prohibits lawyers from co-venturing with other professionals in any business that involves the practice of law. If lawyers can’t be business partners with accountants, engineers, software developers, process experts, and data scientists, etc., that’s going to cut down on the opportunities to learn from them. This makes our social system much more isolated from other innovative parts of modern information economy.

Enough said about that.

V. Efforts of Change Agents

Chapter 9 of Diffusion of Innovations is focused on the change agent.  It begins with the following quote:

One of the greatest pains to human nature is the pain of a new idea. It … makes you think that after all, your favorite notions may be wrong, your firmest beliefs ill-founded. … Naturally, therefore, common men hate a new idea, and are disposed more or less to ill-treat the original man who brings it (p. 365, quoting Walter Bagehot, Physics and Politics 169 (1873)).

This is harsh but also has a ring of truth to it.  To avoid a hostile reception, effective change agents seek out individuals more disposed toward their message, a group disproportionately comprised of innovators and early adopters. After the change agent assists this group in obtaining a large advantage that others can observe, the change agent will become more accepted within the broader social system.  But probably not until then.

Change agents can be university field specialists trying to disseminate agricultural best practices for the good of the state economy. They might also be public health professionals seeking to curb a longstanding but harmful cultural practice that is increasing the spread of disease. The biggest challenge facing change agents tends to be “hetereophily” — i.e., they are often conspicuously different than members of the social system in terms of background and technical expertise. Hence, they struggle to communicate effectively with prospective adopters. Successful change agents find ways to overcome this hurdle. Rogers writes, “As a bridge between two different systems, the change agent is a marginal figure with one foot in each of two worlds” (p. 368).

In the legal industry, change agents are most likely to take the form of technical sales people who are trying to get onto your calendar to sell you a new technology or service.  At industry events, these folks are typically called “vendors.”  The connotation associated with vendors is often negative. In my opinion, this is a parochial way of viewing the world that cannot be squared with our poor record on client service, innovation, and access to justice.  In light of these issues, perhaps we should be more gracious and openminded to those offering tools for improvement.

That said, change agents also exist in established law firms and legal departments — they are quixotic lawyers and other professionals convinced there has to be a better way. In turn, they forge ahead without an empirically grounded theory to guide their actions.  As a result, their courage and good intentions are too often wasted.

As editor of Legal Evolution, I’ll acknowledge my own desire to serve as a change agent. After 15 years of study, it is clear to me that traditional methods of legal problem-solving are underserving clients and broader society. See Post 001 (explaining problem of stagnant legal productivity); Post 006 (connecting the breakdown in judicial system with declining legal job market and declining legal enrollment). This systemic breakdown can only be shored up through innovations that improve legal productivity — i.e., combining lawyerly judgment with better people systems, process, data, and technology. Higher productivity will enable more legal output to be afforded by more people and businesses. I realize this entails a value judgment on my part — I generally favor the innovators. But it is also a judgment informed by a lot of data and field research.  I am also motivated by the longterm welfare of my students at Indiana Law. I need to be part of a system that works for them and their clients.

My change agent role at Legal Evolution has a very simple formula. After explaining the basics of diffusion theory — through these foundational posts — I’ll present finely drawn examples of innovations that appear to be working in the field. In each case, I’ll provide as much context as possible, as the goal is to enable the success of legal innovators and early adopters.

Post 008 will be the longest foundational post by a wide margin. But this is the heart of diffusion theory and how it can be used as a tool of applied research.

Related posts:

What’s next? See Online Dispute Resolution Leader Modria Acquired by Tyler Technologies (009)

Post 007 is another building block in our understanding of diffusion theory.  This sounds like the spinach of blog posts.  And perhaps it is. To make high quality decisions in a complex, rapidly changing legal industry, we need a high quality theoretical lens.  Others have done the hard part — building and validating a useful theory over a period of decades. The purpose of these foundational posts is to understand diffusion theory well enough to apply it to the legal context.

For background on Legal Evolution and a current listing of foundational posts, see the About page. Part I of this post covers units of analysis. Part II presents composite sketches of the five adopter types. Before getting to these new topics, however, let’s briefly review the previous foundational post.

004: Law is a Social System

Post 004 introduced readers to the key insight that innovation diffuses through a social system.  The social system has five segments: (1) innovators (~2.5%), (2) early adopters (~13.5%), (3) early majority (~34%), (4) late majority (~34%), and (5) laggards (~16%). With the exception of innovators, the decision to adopt an innovation is based upon the observed experiences of the adjacent reference group.  Imitation and copying play a much bigger role than analytical or abstract reasoning.

This raises a foundational question — does diffusion theory apply to the legal profession? The short answer is yes.  See Post 004.  Lawyers very much value the security of the pack, albeit we may be reluctant to acknowledge its influence on our own judgments. Why? Because it cuts against our self-identity as a smart person. We want to believe we are smart enough to identify the right answer ahead of others; yet we don’t want the risk and exposure of being separate from the crowd.  Hence, a heavy veneer of reason is layered onto non-adoption decisions that are primarily driven by social proof.  All of this noise invariably slows the pace of innovation for the entire profession.

Yet, here is the crucial insight: In law as in other social systems, the protestations and resistance vary along a continuum.  If you want your innovation to be adopted, don’t waste time trying to convert the early majority, late majority, or laggards.  You have only one audience that matters — early adopters.

I. Units of Analysis

Part II of this post presents composite descriptions of adopter types. Each description is written as if the adopter were a person, which makes them relatively vivid and easy to understand. Yet, in the legal industry as in other complex parts of the economy, innovation often requires the engagement and support of an entire organization. Therefore, before getting into adopter types, we need to cover a technical concept called “unit of analysis” (or, for diffusion research, “unit of adoption”).

A. Organizations

People adopt innovations (e.g., telephones, personal computers, smartphones, etc.), but other valuable innovations often depend upon successful adoption by businesses (e.g., health benefits, enterprise software, flex-time) and/or governments (e.g., seat belt laws, environmental legislation, smoking bans, gay marriage).

When the unit of analysis is an organization rather than a person, the dynamics surrounding the innovation decision (to accept or reject) are much more complex.

To illustrate, imagine the AmLaw 200 grouped along the adopter continuum. A handful of firms would be innovators (~3 – 7) while others would be laggards (~30 – 36 firms, or 1/6 of market).  Yet, the AmLaw 200 social system is dependent upon a separate social system of corporate clients who also fall into the five adopter types.  For an innovator law firm to be successful, it has to find its counterparts among corporate legal departments — i.e., clients willing to pay for something promising even though its new, novel, and relatively untested.

curveIf left to random chance, this complex dialogue will be a fairly rare event.  The 2.5% innovator law firms need an audience with the 16% innovator-early adopter clients. Without awareness of diffusion theory, the mathematical odds are bleak (2.5% x 16% = .4% of buyer-supplier relationships). Once the right pairing occurs, the parties need a dialogue of sufficient depth to plan, build, and execute a successful innovation that benefits both buyer and supplier.

After that, and only after that, will the innovation be picked up and copied by the rest of the social system. This is why the blue part of the diffusion curve is so crucial toward making everything else go.

B. Organizational Innovation is Harder

It is extraordinarily difficult to be a true innovator organization, particularly within the legal industry.  This is true for several reasons.

  • Wrong Analytical Frame. Legal organizations are social systems made up of people and subunits that track the five adopter types. Yet we lack this awareness.  So when promoting an innovation, we place excessive faith in reason and data. After all, everyone is a highly educated professional. Our lack of progress is then blamed on the lawyer stereotype — risk averse, conservative, too focused on precedent, bad at math, etc. — rather than the possibility that we are talking to the wrong group of lawyers.  If we are pitching reason and data to early adopter lawyers, things will go better.
  • Consensus Decision Making.  Legal service organizations tend to make organizational change decisions through committees. That is challenging enough. But the composition of these groups are often designed to manage prideful and contentious lawyers. Optimizing innovation is not even on the table. Think I am just talking about law firms? Not true.  David Cambria, Director of Global Legal Operations at ADM, and Jeff Carr, GC of Univar, often use the term “MPR” (massive passive resistance) to describe the most common reaction to in-house change efforts.  This is fixable, but it takes time and planning, as the politics can’t be ignored.
  • True Innovators Often Lack a Brand.  I have seen this fact pattern many times. Innovator sees a better way while working inside a large industry leader.  The better way is presented to colleagues who cannot yet grasp the advantage. Innovator leaves to form a legal start-up.   Yet, the innovator fails to fully appreciate the difficulty of making sales (or even getting a meeting) without the halo of an established legal brand. In turn, the sales cycle lasts forever plus three days. Some innovators have overcome this hurdle (e.g., United Lex, Pangea3, Axiom Law, Radiant Law), and more will in the future.  But it’s a brutal road.

There are several more challenges, but that is enough for now.  Suffice it to say, it takes tremendous knowledge, skill, persistence, and leadership to create an innovative legal organization.  What we are trying to do here is create a reliable roadmap — that is the purpose of all this empirically grounded theory.

C. The Consumer Market is Different

The market for legal services has two major segments: individual clients (people) and organizational clients (mostly corporations). See, e.g., Deborah Merritt, Two Hemispheres; Bill Henderson, Lawyers for People Versus Lawyers for Business. In the smaller PeopleLaw segment (roughly 1/4 of the US legal market), the unit of adoption is a person with a legal problem. If the person can understand the innovation and the relative benefits are fairly large, the innovation will take hold. Advertising and marketing can often speed this up. This is the market space occupied by LegalZoom, Avvo, and Wevorce.  The diffusion analysis is relatively straightforward and conventional.

However, organizational clients account for 3/4 of the legal services market. Further, the organizational market is not merely buyers and sellers — a complex supply chain is coming into being with managed service providers, legal tech companies with workflow and automation offerings, and various sourcing consultants. For now, however, it is enough to say that innovation roadblocks are more formidable when all the buyers and sellers are groups of lawyers accustomed to consensus decision making.

II. Adopter Types

The descriptions below draw extensively from Everett Rogers, Diffusion of Innovations (5th edition 2003), particularly pages 280-290.  I hope you ask yourself the question, “Within the legal social system, which adopter type am I?”

InnovatorsInnovators place a high value on venturesomeness.  Their interest in new ideas leads them out of conventional peer networks into more far-flung social and professional circles. “Communication patterns and friendships among a clique of innovators are common, even though the geographical distance between the innovators may be considerable.” This is certainly true in law.  The early days of Legal OnRamp revealed the broad geographic dispersion of legal innovators and their desire to communicate with each other.  The LOR chat boards circa 2007-2009 were routinely populated with lawyers from three or more continents.

One of the reasons for the far-flung connections is to better accumulate and understand complex technical information that can be applied to difficult problems. Rogers notes that the “innovator must be able to cope with the high degree of uncertainty about an innovation at the time that the innovator adopts” and also be comfortable with occasional failures and setbacks. Although innovators are generally viewed with skepticism by mainstream peers, they play “a gatekeeping role in the flow of new ideas into a system.” (pp. 282-83).

Early AdoptersEarly adopters are much more integrated into the social system than innovators. They are often the opinion leaders and thus are influential in getting others to act. As compared to the early and late majorities and the laggards, early adopters tend to be more intellectually curious, favorably disposed to science and data, comfortable with abstraction and uncertainty, and more socially and professionally ambitious.

The early adopter is also aware of his or her favored standing among peers. Per Rogers, the early adopter “knows that to continue to earn this esteem of colleagues and to maintain a central position in the communication structure of the system, he or she must make judicious innovation-decisions.  The early adopter decreases uncertainty about a new idea by adopting it, and then conveying a subjective evaluation of the innovation to near peers through interpersonal networks.  In one sense, early adopters put their stamp of approval on a new idea by adopting it” (p. 283).  In the logo of Legal Evolution, innovators and early adopters are both represented by the same light blue color. This is because their relationship is fundamentally different than the relationships between other adopters.  See Post 004.

Early MajorityThe early majority adopts innovations faster than the average member of the social system.  Although they interact frequently with their peers, the early majority “seldom hold positions of opinion leadership in a system.”  Yet, because of their position in the adoption process, they are the group that sets off the tipping point for eventual mass adoption. Rogers quotes Alexander Pope to describe this group: “Be not the first by which the new is tried, nor the last to lay the old aside” (p. 284, quoting An Essay on Criticism (1711)).

The journalist Geoffrey Moore has characterized the transition between early adopters and early majority as “crossing the chasm.”  Moore’s context is primarily Silicon Valley high-tech companies selling enterprise software and similar complex products to corporations.  See Geoffrey Moore, Crossing the Chasm pp. 20-23 (1st ed. 1991). Moore’s analysis is quite relevant to law.  More on that later.

Late MajorityThe late majority is skeptical and cautious.  They generally will not adopt an innovation until “most others in the system have done so” (p. 284).  By this time, the decision is likely to be either a matter of economic necessity or to avoid the discomfort of being outside the norms of the social system.

Rogers notes that socio-economic status tends to be correlated with adopter type.  Thus, the late majority may have fewer resources to take risks and thus may prefer to wait and learn from the experience of others.  Yet, the late majority’s risk averse mindset by be less an effect of fewer financial resources than its cause.  Rogers characterizes this group as followers because the “pressure of peers’ is usually a necessary ingredient to get them to adopt (p. 284).

LaggardsLaggards are traditionalists who tend to make sense of the world by reference to the past.  Among the five adopter types, they have the fewest connections to others. Many laggards are “near isolates in the social networks of their system” and “interact primarily with others who also have relatively traditional values.”  Yet, their slow adoption is not merely a function of limited connectivity. Laggards “tend to be suspicious of innovations and change agents.”  Thus, once made aware of a new idea or methodology, their time period for adoption is significantly longer than others (pp. 284-85).

Rogers acknowledges that late adoption may be rational for those in a social system who can least afford to bear the cost of failure.  Likewise, laggard “might sound like a bad name” though no disrespect is intended by diffusion researchers (p. 285). Rogers observes that a negative connotation would attach to any label associated with the last group to adopt.  This is because the rest of the social system tends to view innovation more favorably.

The next Diffusion Theory post will discuss the levers that influence the rate of innovation adoption.

Related posts:

What’s next? See Variables Determining the Rate of Adoption of Innovations (008)

Six Types of Law Firm Clients
Six Types of Law Firm Clients

As the legal market remains flat for law firms, the focus naturally turns to clients.  How they think. What they care about. How they spend their budgets. Etc.  Yet, to the extent that clients vary in significant ways, the generalizations aren’t particularly helpful.

Six Types of Clients

There are many ways to categorize clients, but by my lights the most useful is size and organizational structure of the in-house legal department. As shown in diagram above, this metric varies from zero for individuals (Type 1) and business owners (Type 2), to the equivalent of a specialized law firm embedded inside a large corporation (Types 5 and 6). Continue Reading Six Types of Law Firm Clients (005)