Written by: Jonathan H. Spadt
Leaders today understand that the best outcomes are the result of informed decision making. But what exactly constitutes “informed”? Is a decision “informed” when it is based on empirical evidence? Is it informed when it is based on multiple viewpoints? Can a decision be informed if it disregards certain information or considers certain viewpoints as less important than others? Much has been written on the “science” of decision making. Most modern decision makers agree that collaboration and cross-disciplinary communication is important to any major decision. But do standards or models exist that establish a framework for that collaboration? Is the team makeup dynamic, and thus a function of time throughout the development process or is the team of collaborators the same throughout the life of the process? Of course to a large extent these questions can only be answered in the context of the type of decision or development process that is the subject matter of the collaboration. And perhaps most importantly, does each member of the collaborative team understand not only their role but also the roles of each of the other members?
The need for collaboration on a scale larger than ever before is driven primarily by the rapid acceleration of the integration of data and technology into all aspects of our lives. This integration brings together areas that, until recently, were able to exist as more separate elements of society. Scientists and engineers developed technology and new products. Law and legal policy set rules for how the products could be sold and used. Economic theory defined the impact of those products on our economy and drove business decisions downstream. Academics focused on research to be picked up by the private sector and commercialized or otherwise adopted on a broader scale through the application of that research. Of course today, we know that much of what was cross-disciplinary 20 years ago is now defined as a discipline, and that today’s cross-disciplinary collaboration is much broader and more inclusive of larger world viewpoints. So how is collaboration different today and how should it be refined to still further accelerate economic and social development?
Let’s examine the situation where an industry is attempting to define standards and best practices for an emerging technology that has the potential to impact daily life in a meaningful way. A good example is the automobile.
30 years ago, cars were essentially a combination of the combustion engine, mechanical controls defined by some electronics, some hydraulic fluid systems, and mechanical forces. The user interface consisted of a seat with a brake pedal, accelerator, steering wheel and basic controls disposed within an environment defined by the physical human form. A cross-disciplinary team working on a 1990 automobile included chemical, mechanical, electrical, and industrial design engineers. And maybe someone with some physiology expertise. And for context, CDs were the state of the art music media. The only thing wireless in a 1990 automobile was the AM/FM radio and cup holder.
The modern automobile, however, is a data producing, data consuming, wirelessly connected, battery hauling computer that can receive, process, and transmit massive amounts of data, including information associated with the desires of the user, who may not even be present in the car during that data flow. And the data can be received by the automobile through a human voice or even simply the movement of a human eye or nod of the head. This data is used for a host of purposes, with the primary goal of transporting the owner or occupant to a destination while simultaneously providing a multitude of other services. And it does all of this among large numbers of other such cars all doing the same thing for their users. In some cases the automobile won’t even have a human occupant as it goes about beneficially moving from its source location to its destination where a human occupant awaits. Who designed all this? It’s obviously a technological marvel. But besides technology, what else goes into the implementation of this dramatic change to our society?
Let’s start by defining the main categories of contributors. Not surprisingly, engineers are a major player as the technology in the modern automobile and supporting infrastructure is fueled by the work of nearly all engineering disciplines, including at least electrical, software, chemical, mechanical, materials, industrial, environmental and civil engineering. Then there are the legal and ethical issues. These are defined by legislatures, agency regulators (both legislative and executive), judges, and the legal profession generally. Still other stakeholders include private sector investment entities and businesses. And an important fourth group, which to a large extent umbrellas all of the first three, is the academic community, which provides important contributions to all of these areas.
Each of these four primary contributors has unique cultures and characteristics. Understanding these differences is important so that each can be positioned to maximize the benefits of their contributions.
First, engineers. Engineers predominately spend their time on the edge of the unknown looking to create a new known, thereby redefining the boundary to a new place. Engineers are perfectly comfortable working with unknowns, developing solutions to problems and innovating to create solutions that have never before been known. On one level this is in contrast to the legal side.
Although many lawyers are also problem solvers, and the legal profession has solved many significant societal problems, the law goes about problem solving somewhat differently. Lawyers, for the most part, try to apply known legal principles in new areas in order to effectuate change. Lawyers are somewhat suspect of major new changes happening too quickly. This cultural difference is routed in the fact that, unlike engineers who can prove their solutions work through empirical evidence, lawyers effectuate an incremental change which then has to be tested over time and developed further by other, often higher authorities, such as legislatures and appellate courts, through additional incremental tweaks. Furthermore, the driving force of legal thinking is that one applies the facts of a case to known legal principles, and that leads to a known outcome. Put simply, engineers thrive on figuring out outcomes that didn’t exist before, and lawyers succeed when they successfully predict known outcomes.
Lawyers do this through the concept of precedent. If the law is clear then parties should know their options because they can determine, through legal counsel, what a court would ultimately decide. This framework, when on solid footing, provides the ability for a decision maker to apply the facts defining the choice to be made to known law and determine a known outcome. The predictability associated with this makes for sound decision making, and, in many cases, disputes can be resolved without involving any court at all. This maintains a certain order and predictability on which business decisions can be made. Lawyers are all about stability and predictability. An engineer, although wanting technological developments to be repeatable, thrive on changing the status quo and shaking up past ways of doing things. Are these two characteristics at odds with each other?
It is possible to see that these two cultures of problem solving are not at odds. But there is an interface between them and it is at that interface where the value of each culture can be harnessed for good. Law has a dynamic – when should it change and how quickly? Many innovators would answer, “more often and faster.” But as noted above, much of the value of the law is that it is predictable. Too much change too quickly is counter to that stability and predictability. But where the change in law results in better reliability, the two are completely aligned. How can courts, law makers and policy makers know when change is necessary to enhance the reliability of an area of law, and when it would do damage? The answer lies in education. And that education can only come from interactive collaboration with the stakeholders.
Businesses make decisions based on the work of both engineers and lawyers. It is this combination of new technology, the use of which is stabilized by the application of the law, which allows strategic and investment decisions to be made with some degree of confidence. Of course many market factors outside of this simplistic model come into play, such as supply chain disruptions due to trade disputes, tariffs, non-tariff barriers to movement, and other geopolitical instabilities. But even these issues can be somewhat mitigated by applying known law to the facts defining the context of the business decision to reach some sort of educated prediction, even if some assumptions need to be integrated into the rationale. The main point here is that business and investment decisions are made based on the expected return which is a combination of the value of the technology itself and the ability of the producer to charge certain prices for the market’s use of that technology.
One clear example of this is intellectual property protection. A patent on the new technology allows the owner to exclude others from using the claimed technology for a legally limited time. This legal instrument, along with a huge body of jurisprudence defining it, provides a relatively certain legal framework upon which an economic decision can be rationalized for a given piece of technology. As something of an aside, this example also illustrates what can happen when the predictability of IP rights is weakened through judicial missteps, as has been happening in the U.S. for about 15 years. Less defined legal principals which change too often – less predictability of the impact of the law on the use or exploitation of the technology – less investment.
Academia is the fourth area that is crucial to economic development. Cultural aspects of academic research are uniquely valuable but in some ways different than those noted above. Often, academic research, although in need of funding, is not profit driven. Academic researchers can sometimes be more tolerant of bureaucracy and longer lead times. There is generally a different set of motivators in academic circles, perhaps because CEOs and board members are not pounding academics for increased speed to market. This is not to imply that academic research is in any way slow or unmotivated – to the contrary, the diligence and associated integrity of academic work is one of its greatest strengths. But speed to publish is driven by factors other than those driving speed to market. A broader look at industry/academic collaboration, which is one of the most important developing sources of prosperity, will be the subject of a future article.
Leaders in all of these four primary categories of collaborators should continue to seek ways to increase the communication and activity between all of them. The interactions between these areas in the past were often linear in time and not significantly encompassing. Today those barriers are almost disappearing but the cultural aspects and mindset of each group remain an obstacle to complete integration. There can be more done by innovators (business and academic) to help guide the law. There can be heightened appreciation by law makers and judges that commercial decisions are made at seemingly light speed today but the slowness of the law to change, although a valuable aspect of law on the one hand, can also be a detriment when the sought after change would increase predictability. Business can also do more to work with universities while still understanding and respecting the different driving forces for academic research. All groups agree on the goal: a better society and a stronger, more prosperous economy. When everyone agrees on the goal, the next step is to align everyone in a manner to maximize the benefit of their contributions to the achievement of that goal.
One great example of the increasing awareness of this modern collaboration model is found at Pennsylvania State University. Last year saw the launch of Penn State’s Law, Policy and Engineering initiative (Penn State LPE). This initiative is a three-way collaboration between Penn State’s College of Engineering, Penn State Law, and the Penn State School of International Affairs. The purpose of the initiative is to develop interdisciplinary education and research between these three categories of professionals to increase research and scholarly collaboration through dialogue among key leaders. This model is leading the way in what should be developed nationally on a larger scale.
In today’s world, it is increasingly important that all segments of our society work together in a more integrated way than ever before. Like any team effort, understanding the differences in background, cultures, and historical perspectives driving each contributor is critical to maximizing success.
About the Author:
Jonathan H. Spadt is an attorney, engineer and CEO of RatnerPrestia. He is an expert on global innovation, intellectual property law, trade-related aspects of IP, and global supply-chain IP strategies. With an established worldwide reputation as more than an attorney, but a counselor and policy developer, he has a broad view of economic and trade policies that interact with intellectual property law and policy. He routinely writes and lectures throughout the United States and Europe in both the private and public sectors, and actively participates in policy discussions relevant to trade and IP law.