Often, I found myself deciding between taking an act that has relatively high upfront cost or something with gradual cost over time. I agonize over the pros and cons because of the upfront cost, even if gradual cumulative cost is cumulatively more.
For example, currently, I am deciding if I should remove my wisdom teeth. The upfront cost is high, but the gradual cost is higher. It is literally shifting my teeth, causing more problems in the future with higher cost. Yet, I’ve been delaying it for years now, and finally decided at 22 to get them removed.
I wonder why I decided to delay. I am fortunate enough that the cost wasn’t a material difference between 18 and 22, so why didn’t I remove them. Well, for some reason and I don’t think I’m atypical, the sense of loss from the upfront cost seems higher than the cost in the future, even if in reality the gradual future cost is more.
Now, I am not a fanatic about teeth (although I’ve been obsessing over them recently), but I am more interested in this upfront cost vs over time cost dilemma and how it influences my decision making and others. Specifically, is this bias affecting how startups are run?
I’m not sure, but I could envision decisions that could be casted in this dichotomy. We must take in account a startup’s timeframe and scale. Specifically, their timeframes are counted in months rather than decades and the scale is rather small. Below are some examples that lie in this dichotomy.
What cloud platform provider should we use? Typically, a company is deciding between Infrastructure as A Service (IAAS) like AWS, where all the core tools and servers are provided and it’s up to your team to efficiently glue them together and set deployment processes, or in contrast, a Platform as A Service (PAAS), where all deployment processes are automated, and it’s often set and forget. For startups, the upfront cost of AWS is extremely small, and Heroku is more costly by orders of magnitude, even as they scale. The obvious choice seemingly might be to go with AWS, but the gradual cost of AWS is the startup’s time to serve customers and find product market fit. Customers don’t care about your infastructure, they care about your product. The lifetime of a startup is measured in months, so any fraction of time wasted on not finding product market fit will lead to death.
Who should we hire first? The stellar experienced engineer, asking for large equity and/or salary, or the newbie, low cost, but high drive. At the very first phases, the iteration speed is likely the most important factor in finding a product that your customers love. Because of this, a single experienced engineer can supercharge a company to creating a product that people love. In contrast, a highly driven individual (like myself), who is a newbie, can have much bigger training cost because learning takes time. This could lead to death to an early-stage startups. (As a newbie myself, I think they should hire newbies, when they don’t have existential peril, for their burst of energy and ideas)
I often underestimate the cost of time because its hidden. So, in decision making, I will need compensate for my bias by overweighting value of time saved. Again, I’m not sure how many decisions lies in this dichotomy of upfront vs over time. Though, I’ll keep it in mind when I do have to make decisions.