A worksheet to help innovators avoid failure
The graphic above is worksheet designed to aid the development and adoption of legal innovations. I created it for my “How Innovation Diffuses in the Legal Industry” courses at Bucerius and Northwestern Law (downloadable PDF available here). This past week, I had the opportunity to present it at LMA’s P3 Conference in Chicago.
The worksheet is grounded in diffusion theory, which is a branch of applied research focused on solving difficult adoption problems in a wide array of contexts, including public health, agriculture, education, manufacturing, and technology. See Everett Rogers, Diffusion of Innovations (5th ed. 2003) (meta-analysis of entire body of research and practitioner guide for those engaged in applied research). If the legal industry is added to this list, Legal Evolution will have achieved its core purpose. See Post 001 (explaining reasons for launching Legal Evolution).
Embedded in the worksheet is a methodology for creating a faster, more direct, and less risky path to innovation adoption. With a modest amount of instruction in diffusion theory, which this post provides, a smart, diligent reader can immediately start using the methodology. Indeed, accessibility is one of the hallmarks of applied research.
Reminder on what we’re doing
There are compelling reasons to invest in a tool that accelerates innovation adoption. Innovations that get adopted are innovations that can be monetized. That’s all for the good. But I also want to remind readers of the larger project, where the stakes are much higher.
In Post 001, I wrote that “Legal Evolution is an experiment in applied research.” The experimental part is ascertaining whether an online publication can be a worthy and valuable medium for distributing serious research. Although Legal Evolution specializes in #longform content, our articles are unacceptably short for traditional academic outlets. Likewise, the applied research part is connected to yet another hierarchy and set of norms. In most Research I universities, the focus is on basic research. Lawrence Berkeley Lab at UC Berkeley, a government-financed applied research lab, provides the following useful definitions:
Basic (aka fundamental or pure) research is driven by a scientist’s curiosity or interest in a scientific question. The main motivation is to expand man’s knowledge, not to create or invent something.
Applied research is designed to solve practical problems of the modern world, rather than to acquire knowledge for knowledge’s sake. One might say that the goal of the applied scientist is to improve the human condition.
(italics in original). In terms of this experiment, publishing outside of academic journals is strike one. Focusing on applied research (e.g., creating worksheets) is strike two. The only thing that justifies Legal Evolution (my experiment, our experiment) is the importance of the practical problem we are trying to solve, which is lagging legal productivity.
Lagging legal productivity is the root cause of the pro se meltdown in state courts (Post 037), the inadequacy legal aid funding (Post 091), the declining PeopleLaw sector (Post 042), antagonism between law firms and clients (Post 019), stagnation in the entry-level legal job market (Post 060), and the dramatic drop in law school applications and enrollment (Post 006). Lagging productivity is also the type of problem ordinarily addressed through market regulation. See Post 058 (lagging legal productivity discussed in Legal Market Landscape Report prepared for the State Bar of California).
The worksheet is designed to aid in the development and adoption of legal innovation. Let’s acknowledge that we all tend to fixate on our innovation and the benefits to our organization. I’ve been there. I know. But let’s not lose sight of the larger project. We’re all failures if our collective innovations don’t significantly improve the functioning of the broader legal system. Cf. Gillian K. Hadfield, Rules for a Flat World 79 (2017) (“People who feel as though the rules don’t care about them don’t care about the rules”).
The stakes are high. Fortunately, there is an empirically validated body of science to guide our efforts.
Application of the worksheet requires some basic knowledge of diffusion theory. The absolute basics are summarized below with links to more in-depth explanations and examples. After covering the theory, this post will move section by section through the worksheet. I also have some brief closing comments at the end of the post.
A. The social system
The core insight of diffusion theory – which is embedded into the worksheet – is that the diffusion of innovation is a process that occurs through a social system. As shown in the figure above, the social system has five “adopter” types that fit a normal distribution. The adopter types move from left to right over time in order of adoption: (1) innovators, (2) early adopters, (3) early majority, (4) late majority, and (5) laggards.
The adopter types move in this progression because each type has attributes that make it more (or less) open to change. Obviously, innovators are the most open, and laggards are the least. With the exception of the innovators, each group adopts an innovation by observing experiences of the adjacent reference group. As favorable observations and testimonials accumulate, adoption spreads through the entire social system.
In the graphic above, innovators and early adopters are in light blue because their collaboration, which is the most rigorous in terms imagination, reasoning power and risk taking, is essential to setting off a domino-like adoption process that flows throughout the rest of the social system. For additional information, see Post 004 (“What is the Rogers Diffusion Curve?“).
One more thing: a social system is a highly flexible concept. Adopters can be people in a market (adopting LegalZoom), people in your law firm (adopting a new workflow tool), law firms that serve people (adopting a matter management software), law firms that serve organizations (adopting AI and automation technology), corporate legal departments (adopting law companies to replace traditional law firms), or a state (passing first-of-its-kind legislation). Who do you want to adopt your innovation? The answer to that question reveals if your target adopter is a person, organization, jurisdiction, or something else. See Post 007 (“Units of Analysis and Adopter Types“).
B. Rate of adoption model
Below is the Rogers rate of adoption model, which is a visual summary of the results of hundreds of empirical studies that use regression analysis to identify factors (“independent variables”) that influence the rate of adoption of an innovation (“dependent variable”).
The left side of the model contain the levers we pull if we want to influence the rate of adoption of a specific innovation. The levers (variables) are organized into five distinct categories (I, II, III, IV, V), which are the same categories used in worksheet. As discussed more below, the three blue categories (I, III, V) are areas where the efforts of innovators can directly influence the rate of adoption. In contrast, the two orange categories operate more as constraints that we need to accept and work around. Because of these orange factors, change in legal generally requires more time, money and patience than other industries.
The right side of the model contains the dependent variable — i.e., the rate of adoption of an innovation. Rate of adoption could be the percentage of adoption within the social system, the speed of adoption, or some combination of the two. It doesn’t matter. The levers on the left remain the same.
The Rogers rate of adoption model is the analytical workhorse of diffusion theory. The entire worksheet is built around this model. For additional information, see Post 008 (“Variables Determining the Rate of Adoption of Innovations“). Also, let’s not delude ourselves into thinking that all worthy innovations diffuse quickly. Slow innovations are often the most socially and economically valuable. See Post 011 (“Fast versus Slow Innovation“) (providing examples from medicine that account for our modern first-world living conditions). This worksheet is likely to be the most helpful for innovations that are economically valuable but slow to diffuse, as speeding the process up reduces business and execution risk.
C. Change Agents and Opinion Leaders
All the early diffusion theory research was focused on the adoption (or the practical problem of lack of adoption) of science-based agricultural methods. This goal was to increase agricultural yields, as a nation with a secure food supply is a nation that can fully defend itself during a time of war.
During graduate school at the Iowa State University in the early 1950s, Everett Rogers joined a team of researchers trying to understand why it took nearly three decades for U.S. farmers to adopt hybrid seed technology. Because hybrid seeds delivered such enormous benefits to farmers (more bountiful, disease-resistant, and drought-resistant crops), slow adoptions chafed against conventional economic theory. Rogers answered this question with a theory that he soon realized could be generalized to other innovation contexts. After the publication the first edition of Diffusion of Innovations (1962), Rogers spent the next 40 years updating his book with more and better examples of how the theory was being used to solve real-world problems. Eventually, Diffusion of Innovations became the second most cited book in all of the social sciences. See Arvind Singhal, “Introducing Professor Everett M. Rogers, 47th Annual Research Lecturer, University of New Mexico,” April 24, 2002.
I provide this background because the hybrid seed story is such a useful way to illustrate the theory, yet without this broader context, many legal professionals would be quick dismiss any example based upon agriculture or farming.
In addition to the five adopter types, there are two other characters who are indispensable to diffusion theory:
- Change Agents, who were the university-trained agronomists who educated farmers on how to use hybrid seeds;
- Opinion Leaders, who were the farmers who had the intelligence and patience to comprehend the technology and its benefits, and the stature within the social system to set off a chain-reaction of adoption among their peers.
Below is graphic from Chapter 7 of Rogers book, which I’ve slightly modified with the addition of the light-blue highlighted section.
The light-blue section roughly corresponds to the time period (~7 years) when adoption of hybrid seeds was limited to innovator and early adopter farmers. During this time, the extensive service agronomists (aka change agents) were conducting intensive outreach efforts to Iowa farming communities. Eventually, opinion leader farmers started to use the technology and enjoy success that was widely observed and communicated within the social system. Aided by social proof, over the next seven years, the rest of the social system rapidly adopted hybrid seeds.
In the graphic above, the top line, which represents the cumulative social system adoption, has the classic S-curve shape that enables venture capitalists and private-equity investors to enjoy such outsized returns. What makes that financial success look easy, however, is the work performed during a relatively long period of uncertainty. If one doesn’t understand the science, many innovators (and their financial backers) are likely to run out of patience.
“All that’s needed to complete the worksheet is 3rd grade math skills”
If you can do simple addition with two-digit numbers (and it’s fine to use a calculator), you can leverage the insights of very sophisticated regression analysis research.
Over twenty years ago, when I worked at a firefighter-paramedic for a suburban Cleveland fire department, see Post 070 (discussing career history), I learned the APGAR method for scoring the medical condition of newborn infants. Different scores set in motion different protocols. Everyday at work I kept a laminated card in a pouch on my belt that, among other things, reminded me how to calculate an APGAR score. APGAR is a classic example of applied research. Although there are more precise methods of assessing a newborn infant, what’s gained in precision is lost by the inability of act quickly. See Daniel Kahneman, Thinking, Fast and Slow 226-27 (2011) (discussing APGAR and noting, “an algorithm that is constructed on the back of an envelope is often good enough to compete with an optimally weighted formula”).
Likewise, we can use the same methodology to guide the judgment and actions of legal professionals seeking to accelerate the rate of innovation adoption. Below is the top portion of the worksheet used to tabulate an overall innovation adoption score.
All that’s needed to complete the worksheet is 3rd grade math skills, knowledge of your target market, and objective reasoning skills. On this last point, I would strongly recommend completing this worksheet in a team environment where multiple views are heard and considered. In addition to obtaining buy-in for any subsequent action, such back-and-forth is bound to improve the quality of the team’s overall strategy and execution.
I. Perceived Attributes of Innovation
In the entire worksheet, this is the most important section. This is because it is used to evaluate the overall quality of the innovation. All too often, we underinvest in innovation design and end up blaming the end-user when they fail to appreciate our vision. According to Everett Rogers, “Most of the variance in the rate of adoption of innovations, from 49 to 87 percent, is explained by five attributes: relative advantage, compatibility, complexity, trialability, and observability.” Diffusion of Innovations at 221.
We score Section I using a simple 7-point scale that runs from -3 to +3.
For the sake of simplicity, I am going it illustrate this section using the hybrid seeds example.
Relative Advantage and Observability are the two factors that most favor adoption (+3). Not only are the yields more bountiful and more likely to survive adverse conditions, but neighboring farmers will see the superior output with their own eyes.
Triabability (+1) also favors adoption because any farmer could try out hybrid seeds on a portion of their land. However, it is not a high score because it requires farmers to ascend a learning curve and entails risk they may not be willing to bear.
Cultural Compatibility (-3) and Complexity (-2) are fairly significant impediments that work against adoption. Basically, farmers are being asked to break with the past and use technology they don’t understand and that is being promoted by outsiders who come from a different social class. Long before the superior corn shows up, the farmers have to process feelings of awkwardness, uncertainty, and indecision. In my work with lawyers and innovation, this identical dynamic is presence with lawyers presented with new methodologies based in data, process, people management, and technology. In each case, the lawyers are prone to attack the efficacy of the innovations rather than endure feelings of a novice who just lost his advantage. Breaking down this resistance is the work of change agents, which is analyzed in Section V.
Out of a possible score of +15, hybrid seeds score a +2. No wonder it took so long! And it would have taken a lot longer but for the enormous resources and ingenuity supplied by federal and state agricultural agencies, which funded researchers working in public universities, such as Everett Rogers. Much of their work is in Section III (Channels of Communication) and Section V (Efforts by Change Agents).
For additional information, see Post 008 (“Variables Determining the Rate of Adoption of Innovations“); Post 011 (“Fast versus Slow Innovation“) (providing examples from medicine that account for our modern first-world living conditions).
II. Type of Innovation Decision
According to diffusion theory, the decision to adopt an innovation falls into one of three buckets:
- Optional. This is essentially market-based where everyone in the social system is free to adopt or reject. Think smart phones or social media. LegalZoom is a good example of an optional adoption decision in the legal industry; and I would argue it’s the main reason why the company has become so successful. Cf. Dan Primack, “LegalZoom now valued above $2 billion,” Axios, July 31, 2018. Also, it may account for why Y Combinator generally funds only legal innovations in the PeopleLaw space. See Gabrielle Orum Hernández, “The 11 Legal Tech Startups Currently Backed by Y Combinator,” Legaltech News, Dec. 2, 2016.
- Collective. For this bucket, think committees making consensus-based decisions, which is standard operating procedure in most law firms. One of the leading law firm consultants recently told me that most of his time is spend building census among the two or three dozen partners (of several hundred in the firm) who need to be on board before the firm can try something new. Unfortunately, the partners are too busy to climb a learning curve outside their core discipline. Yet, that doesn’t stop them from being very confident in their views. Suffice to say, collective decisions dramatically slow innovation adoption.
- Authority. Somewhere in between Optional and Collective is Authority, which enables an individual or subgroup to make a decision on behalf of the rest of the social system. Think legal department. Authority-based decisions, however, are no panacea because so much hinges on (a) the disposition and technical competence of leadership and (b) willingness to make a sufficient investment in change management strategy and execution, as lurking around the corner is MPR (“massive passive resistant”) by the rank and file. See Post 008 (discussing in context of legal departments); Post 015 (discussing in context of large organizations).
The descriptions above are the basis for the following scale:
We all know the expression, “It is what it is.” That’s what we have here: a constraint that we need to accept and work around.
That said, there is one notable exception. Post 089 presented the career history of Bob Meltzer, the founder of VisaNow, which launched over 20 years ago as an online portal for processing employer-based visas. Because of some early success landing big enterprise clients, the company obtained significant Silicon Valley funding. Yet, the more VisaNow focused on big employers, the longer its sale cycle. Frustrated by the lack of S curve growth, Meltzer made the decision to look outside the Fortune 500 to small and medium-sized companies where the decision to hire VisaNow rested with a single, overworked executive. The result was three consecutive years of 100% growth and an exit that delighted all shareholders.
One important implication of the type of innovation decision is the need to emphasize marketing versus sales. If the adoption decision is optional, a targeted marketing campaign can generate enormous sales. If the adoption decision is collective or authority-based, more resources typically need to be poured into a professional sales team.
Type of Innovation Decision is given a large weighting (-6 to +6) because it is extremely influential. The prevalence of collective decision making, particularly in law firms, elongates the sales cycle. But sales are still possible. See Post 089 for additional details.
III. Communication Channels
Although diffusion theory is a multidisciplinary field that draws upon sociology, economics, anthropology, geography, and various other disciplines, diffusion theory researchers are commonly found in the communication departments of major universities. This is because the advent of mass communication dramatically increased the flow of information across multiple populations. The vividness of mass communications also made it possible to soften and reshape social norms in ways that created new regional and national identities and social systems.
For this section, think of communication channels in two ways:
- Available communication channels. What communication channels can we use to reach our target audience? In legal, this might be email, direct mail, conferences, advertising, social media, professional groups, writing articles (content marketing, thought leadership), in-person consultative sales, etc.
- Content of message. Communications can be broken into three phases that correspond with innovation adoption: (a) Introducing the innovation to the social system, which will cause innovators to self-identify and reach out for more information, (b) educating the target audience so they understand the innovation’s advantages and how to use it, (c) publicizing adoption, which is basically communicating the explicit or implicit endorsement of opinion leaders.
The takeaway on communication channels, however, is simple: optimize! This is impossible to do well without data and feedback loops. Below is a 7-point scale to score your efforts.
In the year 2019, communication channels are a set of levers we can substantially influence.
IV. Nature of Social System
Social systems with modern norms are more open to innovations than social systems with traditional norms. Legal is a traditional social system. Likewise, interconnected social systems adopt innovations faster than isolated social systems. Because of Rule 5.4, law is an isolated social system.
Below is the scoring system for nature of the social system.
In general, this is a factor we don’t control. For the universe of law firms, the score is a -6. However, if the social system is an individual law firm considering adopting a new internal innovation, the score might be considerably higher. This is because some law firms have very forward-thinking leaders who work hard to seek new ideas outside what other law firms are doing. But they are more the exception than the rule.
The main reason I favor changes to Rule 5.4 (the prohibition of nonlawyer ownership of businesses engaged in the practice of law) is that innovation is most likely to occur in environments where talented professionals can collaborate as co-equals. That rarely happens in law firms, as the allied professionals, who are indispensable to innovations in service delivery, are employees who can be fired if they engage in too much conflict with the owner class. As a result, on a daily basis, facts and data have to be soft pedaled. Even if firms pay these folks a handsome wage, why would A-level talent cast their lot with lawyers?
The Nature of the Social System scores will be higher in law companies, legaltech, and legal departments, because these organizations are comprised of a more diverse array of professionals and a hierarchy that is less likely to privilege the views of lawyers. See, e.g., Post 027 (“A Successful Legal Change Management Story“) (telling the story of how an Australian telecom company won the 2017 ILTA Legal Department of the Year Award). Indeed, Mark Chandler, the GC of Cisco, attributes his legal department’s success to the culture and priorities of Cisco Systems, Inc., which rubs off on Cisco’s in-house lawyers.
V. Efforts of Change Agents
The final section assesses the efforts of change agents. The scoring system runs from 0 to +7 based on the seven factors on the worksheet. Add one point for each factor below.
- Making contact with clients (+). Frequent contact builds familiarity and creates opportunities to establish credibility and trust.
- Client orientation (+). Is the change agent trying to solve the clients’ problem or trying to advance their own agenda (e.g., make a sale)? If the change agent is listening, they can learn ways to modify and improve their innovation.
- Client empathy (+). A change agent is more effective when she or he can see the world through the eyes of the client.
- Homophily with clients (+). Can the change agent look and act like an insider? In the legal industry, change agents with law degrees generally have an easier time because of a common experience and background with most clients.
- Credibility in the clients’ eyes (+). Can the change agent fluidly answer tough questions? If the client must trust the change agents’ judgment, do the change agents possess the credentials and background to understand the underlying innovation?
- Working thru Opinion Leaders (+). Rogers observes, “The time and energy of the change agents are scarce resources.” Diffusion of Innovations at 388. Engaging opinion leaders is the most efficient path to system-wide success.
- Improving technical competence of clients (+). Clients dislike long-term dependency on change agents. Thus, effective change agents often make education the cornerstone of their efforts, which builds trust and enables clients to make future adoption decisions on their own.
Change agents are most critical when an innovation is at odds with existing system norms (low cultural compatibility) and adoption requires significant upskilling (high complexity).
In the legal industry, change agents are consultative salespeople in legaltech and law companies, see Post 034 (discussing team at Thomson Reuters), Post 053 (same at UnitedLex); legal ops professional in legal departments, see Post 068 (Jason Barnwell’s role at Microsoft); and P3, innovation and, in some cases, BD/marketing professionals in law firms, see Post 039 (discussing examples of intraprenuership in law firms).
During my presentation at P3, I showed the graphic below, which contains many familiar faces for regular readers:
All of these change agents have tremendous technical skills that can aid the innovation process. But only half have law degrees. Of the six who are not lawyers, all have been asked the question, “Where did you go to law school?” That means they’ve passed the credibility test in the eyes of the lawyers they’re trying to help.
Law needs an army of change agents. However, effective change agents are both rare and expensive. Further, their lawyer-bosses often have unrealistic expectations because they lack the change agent’s technical skills and lack the time to learn things like diffusion theory. That said, the industry is making progress. Hopefully, with this worksheet, it will go faster.
The worksheet provides two types of insights. First, low scores on a Section I factor or in one of the other Sections help prioritize your efforts (or the decision to pull the plug). Second, you can use it as a point of comparison. For example, score the most successful innovation in your space. As students in my “How Innovation Diffuses in the Legal Industry” courses quickly realize, we are operating with many faulty assumptions. We find this out when we test them.
For those using the worksheet (click on thumbnail to the right), I’d welcome feedback. Please send to firstname.lastname@example.org.