Email latency is a proxy for the founder’s OODA loop, the externally visible signature of internal decisionmaking… As organizations scale, this becomes the binding constraint… A slow executive forces the whole org to idle against their queue.
The hypothesis is broadly plausible for at least some organizations, but I want to flag that email latency could be causally decoupled from decision making rate while still being correlated with it. We’d expect a competent exec to respond quickly to a key funder’s emails, regardless of how quickly they make decisions.
Your framing implies that business progress is inevitably bottlenecked by the decision-making rate (“As organizations scale, [the executive decision-making rate] becomes the binding constraint.”). Yet we can think of situations where this is clearly not the case, at least within a span of time.
A small biotech company whose lead is in the middle of a clinical trial is in a “dead zone,” bottlenecked not by executive decision making but by practical or regulatory constraints on the rate at which patients can be dosed and evaluated.
A company that selects an overly complex problem may be unnecessarily bottlenecked by decision-making rate. If the executive had chosen an alternative strategy, perhaps by taking more time on a single, critical upstream strategic decision, they might have been bottlenecked by other factors, such as the rate at which a factory could be built or customers acquired.
Finally, in order to study decisions empirically to test these hypotheses, it would be necessary to operationalize them, which requires defining the dimensions of a decision, establishing the context that lets us evaluate the similarity of two decisions.
For example, is it reasonable to compare the rate at which two different types of companies—Apple and Lego, for example—finalize product decisions? Apple makes a relatively small number of high-tech products, while Lego makes a large number of different toys, including both individual blocks and lego sets. How could we evaluate the question of whether a company that has a similar decision-making demand to Lego makes decisions slower or faster than Lego, and whether or not it leads them to better outcomes?
If we can’t tractably evaluate these hypotheses, then how do we know that the rate of decision-making is more important than quality, or that it’s commonly the binding contraint on progress? Or is the claim more limited: that, ceterus paribus, making decisions more quickly is useful?
The hypothesis is broadly plausible for at least some organizations, but I want to flag that email latency could be causally decoupled from decision making rate while still being correlated with it. We’d expect a competent exec to respond quickly to a key funder’s emails, regardless of how quickly they make decisions.
Your framing implies that business progress is inevitably bottlenecked by the decision-making rate (“As organizations scale, [the executive decision-making rate] becomes the binding constraint.”). Yet we can think of situations where this is clearly not the case, at least within a span of time.
A small biotech company whose lead is in the middle of a clinical trial is in a “dead zone,” bottlenecked not by executive decision making but by practical or regulatory constraints on the rate at which patients can be dosed and evaluated.
A company that selects an overly complex problem may be unnecessarily bottlenecked by decision-making rate. If the executive had chosen an alternative strategy, perhaps by taking more time on a single, critical upstream strategic decision, they might have been bottlenecked by other factors, such as the rate at which a factory could be built or customers acquired.
Finally, in order to study decisions empirically to test these hypotheses, it would be necessary to operationalize them, which requires defining the dimensions of a decision, establishing the context that lets us evaluate the similarity of two decisions.
For example, is it reasonable to compare the rate at which two different types of companies—Apple and Lego, for example—finalize product decisions? Apple makes a relatively small number of high-tech products, while Lego makes a large number of different toys, including both individual blocks and lego sets. How could we evaluate the question of whether a company that has a similar decision-making demand to Lego makes decisions slower or faster than Lego, and whether or not it leads them to better outcomes?
If we can’t tractably evaluate these hypotheses, then how do we know that the rate of decision-making is more important than quality, or that it’s commonly the binding contraint on progress? Or is the claim more limited: that, ceterus paribus, making decisions more quickly is useful?