Logic for Leadership: Why Executives Should Study Math (Part 3)
Congratulations: you’ve reached the last part in this series! If that statement doesn’t apply to you, go back and read Part 1: Mathematical Misconceptions or Part 2: How It Helps.
In this final section, we will discuss why the methodology and patterns of thinking taught by mathematics (and symbolic logic) are of particular importance to business leaders.
Why does this all matter for business?
Business leaders are tasked with making a wide variety of complex decisions, often operating under incomplete information. Strategists and others are asked to predict trends, anticipate market response, and design for the future. These activities all require a significant amount of assumptions, incorporate numerous sources of input, and necessitate iterative evaluation.
Business strategists and their peers face questions that would benefit from a clear structure requiring them to define their assumptions and inferences, alleviating the mental gymnastics they undoubtedly perform. Yet, critical strategic decisions continue to be fought out verbally in boardrooms or via complex, compelling PowerPoint decks, both of which have their merits but neither of which holds the speaker to an inherently structured argument.
It is important to create cogent arguments proving your conclusion, but this is difficult to do when words linger in the air or are jumbled within the confines of Smart Art. We should hold ourselves to a higher standard, wherein we both (1) seek to convince others, and, in the process, (2) rigorously interrogate ourselves.
Argumentation that imitates mathematical structures is stronger than its boardroom equivalent for two key reasons:
- It forces you to define your premises upfront, clarifying your assumptions
- It forces you to outline your argument step by step, allowing for no logical ‘leaps’
As a result of these two attributes, logical systems of argumentation reveal any gaps in your thought process.
Now, using a strictly logical process, particularly one that involves citing the rules at play, is not the most rhetorically compelling method for the same reason that a data set is necessary and useful but not pretty. You can use a data set to reach your conclusion and keep it in your back pocket as proof, but you do not walk an unsuspecting bystander (or your CEO) through the entire spreadsheet.
In fact, I didn’t use an explicitly deductive structure in this article! But, I could have, and this is what it would have looked like, using a loose framework that belongs to either of logic or math:
Premises
A. People benefit from understanding their assumptions and inferences in arguments
B. Logic and math force you to keep track of premises
C. Logic and math teach systems of creating inferences
D. Businesspeople make complex decisions
E. Complex decisions make it difficult to create strong inferences
F. Complex decisions have a lot of unspoken premises
Sub-conclusions
G. [D&E] Businesspeople may not create strong inferences
H. [D&F] Businesspeople may not define their premises
I. [B&H] Logic & math could help businesspeople keep track of premises
J. [C&G] Logic & math could help businesspeople create strong inferences
K. [A] It’s important to understand your assumptions and inferences in arguments
Conclusion
L. [I&J&K] Therefore, businesspeople would benefit from learning/using logic and math
The point here is not that you need to painstakingly outline every step in your C-Suite recommendation simply to prove that you are right about something obvious. Rather, if you stand by a conviction to be rigorous in your deductive reasoning and apply this sentiment wherever possible, you are truly embracing the value of math.
Ultimately, if you’re already out of school, you don’t need to go back and redo your degree.
If you can take a continuing education class, great! If not, think about ways that you can incorporate these principles into your daily work and routine. Can you do basic logical puzzles before bed to encourage mathematical pathways to form? Will you be stringent with your internal logic when arguing complex topics? Should you encourage more math students to apply for vacancies on your team?
No matter what you choose to do next, keep this in mind: you’re not bad at math. You’re not bad at computation, or programming, or whatever other quantitative skills you’ve been avoiding. So, next time the opportunity arises to explore one — just do it.
