Building Inspectors and Strategy Scholars: Reaching Further than MBAs

By Victor Bennett

Lori asked me to write up a blog post about increasing the scholarly impact in our community. It is a topic I’ve been thinking about a lot recently, so I happily agreed.

The poetry of the request is that I get to use this non-journal forum to raise a possibly provocative idea, using non-journal forums for our impact. Well, more accurately, using our journals to support creating materials for a community much larger than those that can be reached by the journals directly.

For much of my time in Strategy academia, the question of how to have more impact has often been assumed to be the same as asking “how can we get consultants and managers to read our journals?” To paraphrase Eli Cash, what this post presupposes is, what if it isn’t?

There are certainly practitioners and consultants who read Strategy journal articles, or at least who have absorbed material taught in Strategy courses and used that. Even the sum of consultants and MBAs is a tiny fraction of the number of people doing business. Realistically, our frontier research is often complex and requires enough background that it is inaccessible to most of even that audience. How can we influence practitioners who don’t have time or training to read a journal article, don’t have the time or money to get a business degree, and can’t hire a consultant?

I asked myself which practitioner professions were able to make decisions informed by deep theoretical understanding without needing everyone to be trained. Perhaps because I’m doing some renovations to my house, one profession that came to mind was building inspectors.

There are a huge number of buildings built around the world that get the benefit of being evaluated by building inspectors. Those inspectors are not, themselves, the sources of the knowledge they apply. There is essentially a flow of lessons from the most theoretical research through more and more applied research to where it gets applied “on the ground” (literally). Mathematicians and physicists have developed models of fluid flow and the physics of statics and deformables. Those tools are taught to degree-holding mechanical and civil engineers who translate them into science-informed applied engineering. Those findings get taught to soil and professional engineers who are certified and well-educated, but may not have a traditional college education in physics. Committees of those engineers create standards that are applied by building inspectors. At each level, the guidance becomes coarser, but that is by design. The profession can work like Garicano’s model of organizations (Garicano, 2000). In the vast majority of situations, a coarse rule-of-thumb from construction guidelines applies. There are well-defined edge cases, however, where a building inspector will require that builders get a certified engineering plan. In even more nuanced situations, a certified engineer might look to academics with even more sophisticated tools to understand the situation. In this model, theoretical insights are applied much more widely, even if they are not applied directly by those who developed the original insights.

Another example is antitrust enforcement. The most sophisticated and general models tend to be developed by industrial organization economists at universities and laid out in academic journals. Some specialized scholars work to translate those insights to policies like the Horizontal Merger Guidelines. Those guidelines are, in turn, interpreted and used by practitioners at firms, their legal advisers, or regulators like the DoJ and FTC who are brilliant, but more likely to have industry expertise or legal training and less likely to have doctoral training in antitrust economics. In cases that are particularly nuanced, and possibly outside of the general merger guidelines, both regulators and firms will hire IO economists working at the frontier to hash out the specifics of the edge case.

Perhaps Strategy scholars should aspire to a leveraged model of impact like these. In my short stint as a VC, the thing that I got asked for most when people heard I had a PhD was "playbooks;" like a "playbook for a SaaS business." My initial reaction was that something like that wasn’t possible. If there were a generally-correct formula for how to build a SaaS business, it couldn’t possibly be a source of competitive advantage. But maybe I protested too much.

Porter’s Five Forces are an example of (an intentionally oversimplified) summary of decades of Strategy and Economics work. There are certainly cases where the framework misses important details. Perhaps instead of trying to cover richer models with practitioners, we could work on clearly articulating the boundaries. For example, someone running a small business on a shoestring could easily find a video about the Five Forces on YouTube. What if that video said, “these work most of the time, but in the following situations things are a little more complicated and you might want to reach out to an MBA for advice?” In the classroom we might cover models of Value Based Strategy which nest the Five Forces but allow for richer insights that are useful in some situations. For example, the Five Forces only tell you about your customers and suppliers, but Value Based Strategy can help you understand how changing the value added of business far up or down the supply chain can affect your profitability. For example, the Android operating system looked like it faced a challenging set of Forces when it was launched, but it wasn’t meant to be profitable on its own. Android reduced the value added of the iPhone, likely reducing what Google would have to pay to Apple for the privilege of being their primary search supplier. That is a complicated dynamic that not every business owner needs to, or might even want to, understand. There are likely even more complex situations for which an MBA might want to go back to their professor and ask questions about the specific nuances of the situation.

Building this kind of knowledge supply chain requires taking up a new kind of research. In addition to trying to understand our phenomena of interest, we would need to come up with new abstractions, and test them in pedagogical settings to understand whether they are useful. This could look like research in Education where scholars develop and test specific curricula. The curricula need not be “provably optimal,” but rather have to be shown to be useful. Those papers would look very different from some of our current work. Even in the empirical studies that describe the results of particular training exercises, very little space is dedicated to describing the curriculum. Consider, for example, some of the important work on teaching entrepreneurs to act as theorists (e.g., Camuffo et al., 2020), training entrepreneurs in developing countries (e.g., Gonzalez-Uribe and Leatherbee, 2018), or the impact of Strategy curriculum (e.g., Heshmati and Csaszar, 2024). Most of the space in those papers goes to describing prior theory and the empirics for testing impacts. A scholar looking to build on that work by reusing that curriculum, or an educator looking to implement the curriculum, would have to go well outside of the paper and reach out to the authors directly to get details of the curriculum. Also, right now, those studies don’t look at the boundaries of those curricula, nor do they test a combination of the curriculum and guidelines on when a student should seek advice from a specialist. This is not a criticism of that important work. Rather, it is a call for our journals to consider, if not solicit, studies of that type.

While I know that a paper that says “here is a curriculum that I made up and it works pretty well” may not feel satisfying, it is important to note that some of the tools we have come to rely on most are not provably ideal, but work pretty well. How many of us have used the F-statistic>10 threshold for the first stage of an IV estimate? That comes from a set of simulations that argue that it tends to work pretty well, for some definition of “pretty well.” In situations where your first stage does not rise to that level, you likely go to an econometrician in your school to ask for suggestions.

Perhaps we can use our rich theories to come up with defensible curricula and then test those rules in particular settings and maybe recommend experts in exceptions settings. Like building inspectors!

Consider Mitchell and Capron's Build-Borrow-Buy framework (Capron and Mitchell, 2012) that appears in a book rather than a journal. Many of us teach the framework even if it isn't theoretically optimal or even empirically validated. It captures some of the insights of empirically validated research, but also abstracts away a lot; intentionally. Imagine empirical papers running the gamut from qualitative studies about whether an actual decision making process looks like that framework, Randomized Controlled Trials (RCT) with small businesses testing the (admittedly not perfect) tool's impacts on small businesses, simulations based on retrospective data looking at whether actual M&As followed the framework, and maybe finally statistically-sophisticated analyses using instruments or natural experiments aimed at further validating and improving the tool. All of these could help us delineate the boundaries for these simplifications that can be part of what we teach.

Research like that would help us produce means-tested curricula for teaching future business people, without the requirement that they spend the time, or have the capability, to understand the full richness of our most sophisticated tools. It would also let us articulate the boundaries of the general “rules of thumb” and guide practitioners to know when they need more specialized expertise, and to whom to reach out. This would allow us to scale our impact to a much larger group of business people than just those able to get business degrees, let alone keep up with and consume our frontier research.

References:

• Camuffo, A., Cordova, A., Gambardella, A., & Spina, C. (2020). A scientific approach to entrepreneurial decision making: Evidence from a randomized control trial. Management Science, 66(2), 564-586.

• Capron, L., & Mitchell, W. (2012). Build, borrow, or buy: Solving the growth dilemma. Harvard Business Press.

• Garicano, L. (2000). Hierarchies and the Organization of Knowledge in Production. Journal of political economy, 108(5), 874-904.

• Gonzalez-Uribe, J., & Leatherbee, M. (2018). The effects of business accelerators on venture performance: Evidence from start-up Chile. The Review of Financial Studies, 31(4), 1566-1603.

• Heshmati, M., & Csaszar, F. A. (2024). Learning strategic representations: Exploring the effects of taking a strategy course. Organization Science, 35(2), 453-473.