Long-term ≠ ∑ Short-terms – Complex systems are not reductionist. Along time dimension too.
“Unlike with turbines and engines, businesses and economies cannot be broken down into neat constituent parts and causal relationships between parts. We can understand messy world as a whole, without being able to fully understand inner workings or explain every little facet. One can make sense of it only at a higher level of abstraction.
Non-reductionism extends to time dimension as well. Attempting to break down a decade into years or a year into quarters is not merely tricky but counter-productive. Oddly, far future can be more predictable than near future. Surest way to get long-term wrong is by analysing it as a series of short-terms. Hence, inequality sign in my equation. We’re better served by working with a fuzzy sense of long-term prospects, without cascading the same into a series of explicit, precise short-term forecasts. Let me explain using the past.
For over a decade, my consideration set has been better companies in decent, slow-changing industries. Imagine we travelled back to the beginning and you forced me to forecast growth by threatening me with dire consequences (“no nendrankai chips ever”). For simplicity, let’s stick to non-cyclical businesses. My best attempt might have been: system has grown for decades at low double-digits in nominal terms; better companies are unlikely to do worse; steady industries won’t let them do much better either; so, organic business growth in same ballpark.
How does my hypothetical growth prediction fare, across industries. Consumer staples? Low double-digit. Consumer durables? Ditto. Building materials? Ditto. Auto? Ditto. Pharma? Ditto. Chemicals? Ditto. Traditional media? Shade lower. For-profit internet? Shade higher. IT? Low double-digit. BPO? Ditto. Last two aren’t even tied to same system. Across my consideration set, the story is eerily similar. While there are outlier companies or companies having outlier years, range of long-run outcomes is remarkably narrow.”