Asymptote analysis using customer-vendor loop

Another potentially useful source of insights is using the customer-vendor loop for asymptote analysis. If we indeed desire for our loop to compound, we likely need to consider the upper limits of the compounding. Every growth has a limit, and studying the structure of the customer-vendor might help discern it.

Roughly, the idea is as follows: since the customer-vendor loop has four stocks and four flows, we start by reasoning about the limits that are imposed by each. Since compounding loops are sequences, the stock or flow whose limit we will encounter first will point at the asymptote in our growth. More than likely, there will be other factors at play, so treat this exercise more as a homemade compass rather than a precise instrument. Still, even the fact of engaging in such exercise might open up a space for building shared mental model space about limits to growth.

To look at the limits of the four stocks (Customers, Products, Vendors, Interactions), think of them in terms of capacity. Imagine them as containers. What is the size of each container? Why can’t it get larger? What are the factors that stand in the way?

One common mistake I keep making is imagining Customers as “all people”. That’s one massive container, right? Sky’s the limit. However, in reality, the slice of “all people” actually interested in my Products is typically much smaller, and is limited in many distinct ways. If I own an ice cream shop, I am limiting my Customers to those who like or can eat ice cream. I am also limited by access: how many people can see my shop and walk to it? Sometimes — and this tends to happen frequently in software adventures — I only have vague hypotheses about the existence of my Customers, in the “if you build it, they will come” fashion. In such cases, it helps to be conservative about the guesses. Keeping the sky as the limit may lead to unproductive self-delusion.

In software engineering loops, typical Vendors limits are going to orbit around budget, engineering capacity, depth of expertise, and the like. Products will bump into limits like feature richness, accessibility, stability, etc. Interactions will likely face scale as well as various conversion-related limits.

It also helps to recognize that all limits are dynamic. If another vendor opens an ice cream shop up the street from mine, my Customers limit will change accordingly. Limits are as much of a study of future trends as understanding the current situation. If we are to be strategic about our enterprise, we need to do both. This is what the continuously integrated strategy piece was hinting at.

To study the limits of the four flows (Vendors build, Products attract, Customers engage in, Interactions attract), it is helpful to imagine flows as faucets that connect the two stocks. What would it mean to open the faucet all the way up? What is the current setting? Usually, the words “friction” and “performance” enter the software engineering vocabulary when discussing limits of flows.

The “build” flow limits are typically about the effectiveness of tools and processes. Conversations around engagement flow limits will mention bandwidth and latency. Both “attract” flows will circle around incentives, compensation, recognition, and somesuch. 

Sometimes, understanding that there is a limit to the flow can lead to a candid conversation about compounding loop viability and the need to rethink the current hypothesis. I may assume that since I have a great connection to the Internet, all of my Customers will also have it. I may assume that since I have a multi-core machine that is happy to chew on any CPU load I throw at it, all of my Customers have access to the same computing bandwidth. In the long run, both of these might come true. However, my compounding loop is here and now, and making these assumptions might prevent me from seeing the flow limits, leading me to imagine a compounding loop that isn’t there.

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