In engineering, we’re taught that we can simulate certain physical processes using equations—but only within limited conditions. This limitation exists because there are simply too many variables to model every possible situation.
Stephen Wolfram refers to this concept as “pockets of reducibility”—specific areas where we can model our world with some success. Outside of these pockets, the complexity becomes overwhelming.
In essence, this means that while we can simulate aspects of our world, most of it remains too complex to fully predict or replicate.
This idea aligns with theories like the computational theory of the universe and simulation theory, which suggest that simulating a universe with the same level of detail and complexity as our own would require computational resources equivalent to the universe itself.
These concepts highlight an important truth: we can never account for every variable, no matter how hard we try. In the workplace, this is where process standardization becomes valuable. When you standardize a process, you reduce variability and create consistent inputs and outputs. But some activities have too many variables to standardize—this is the domain of the knowledge worker.
Only a limited portion of our work can truly be standardized. The rest involves navigating complexity and managing unpredictable factors.
Consider this: when we think, “I wish I could just do my job,” what we often mean is, “I wish I could focus only on the part that’s been simplified and planned.” But dealing with variables—the unknowns, the messiness—is the real reason we’re paid to do the job. If it were easy, someone else would be doing it.
For us who are leaders, we need to ensure we’re reducing complexity where it makes sense, so our employees aren’t constantly stuck managing chaos. Standardize what can be standardized—and support people where it can’t