One of the most power tools that economics have brought to the world is cost-benefit analysis and really assessing what is the constitution of cost or benefits at various levels: individuals, firms, regional government, national government, countries.
Where it fails is the ability to properly ascribe who cares about what. The assumption around rational, selfish agents cannot possibly hold in reality. On the other hand, there is radical inconsistencies when you perform such optimisation on behalf of “government” which is staffed by human agents and with politicians have their own agenda. Over the years, these poor assumptions have made room for more colourful, richer analysis of agents, decision-making units at different levels.
Now if we move our attention to the dimension of time rather than perspective of our agents, we realise another issue. We can assess somehow the cost and benefits of today if we use our imaginations but to stretch it to the future would require even more manipulations. And the uncertainty make render the exercise less fruitful than one may expect.
Alas, we continue to use these tools expecting them to work while not having proper assessment of whether they work or not when the outcomes play out in reality. It is not the issue of calculating those figures but how we incorporate them into our judgment that matters. Yet with limited budgets and resources, most have chosen to opt for a semblance of the exercise, paying a smaller cost but getting almost none of the benefits.
In my line of work as a strategy consultant, I sometimes work on techno-economic studies. Using a combination of statistical analysis, forecasting techniques and calculations, we estimate various different cost trajectories, and examine the economics of something. It could be a project, a technology, or a decision that a company is trying to undertake which has some cost impact and some benefits somewhere else.
In economics, we can only perform estimates when we assume all else equal. That’s the only way to perform proper sensitivity analysis. When you change more than one parameter, then you’d call it a scenario analysis. There are infinite possible scenarios when there is infinite parameters to shift or parameters with continuous range of possibilities. So when we model the economics of something, we’d always be varying something that we think we have control over, or that we expect will be changing in the near term, and see the effects on the economics.
Yet we often think that the economics of a technology or something will remain the same unless something drastic happens. More often than not, economics of technologies shift when various players in the market make different investments, either in the underlying technologies, manufacturing capacity for the gears and components, or simply into research and development. The actions of many different parties can have a collective impact of making the economics work when at first it doesn’t seem to work.
When we critique the economics of a new innovation or project, we often forget we are comparing them against the status quo where many are already very well-invested into. The years, decades and even centuries of using a technology, manufacturing it, creating complex supply chain and auxiliaries around the status quo. It is naturally hard to beat. But what is critical about a new technology is that the incremental investments can make a large impact, small changes to scale can also make a difference. Coordination and changing expectations play a big role.
Will the economics of new innovations change overnight? Unlikely, but they typically change faster than you and I can work out the math for the economics of it.
Through the Linkedin learning course by Bob McGannon, I became acquainted with the idea of intelligent disobedience. I think the premise that he lays out is pretty interesting. That the human world is made of many rules and usually, 95% of the time, these rules work but then there is always 5% of the time when it doesn’t. This is when circumstances are extraordinary, when the situation is not as expected by the rule-makers and so on.
The exceptions are what calls for intelligent disobedience. After all, the reason that a person should be put in a job is not because he knows all the rules on the job. He needs needs to be able to follow, but more importantly, he needs to know when to break them. If rule-following is all it takes, then the cockpit of most commercial aircraft technically don’t require pilots. It is the need to take exceptional actions that we need professionals to take certain roles.
Talents are basically known to be the ones who break rules. They don’t get punished for them; in fact more often than not, they are celebrated. Philip Yeo is a good example of that in Singapore. In fact, he probably exhibited most traits of intelligent disobedience in most of his stories of defiance that he recorded in his book, “Neither civil nor servant”. To a large extent, risk-taking involves a lot more nuanced thinking than the manner our Singaporean culture allows for.
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