It seems a bit silly, but I was super excited when I first learned the concept of Net Present Value. On the surface, the concept that money today is more valuable than money later seems incredibly straightforward. But have you ever wondered why a $136 million lottery only pays out $108.3 million in cash? It is a function of the discount rate and time. How you get to a discount rate itself requires consideration of risk factors, future uncertainty, and so much more. It really is very cool when you think about it. To be able to quantify the time value of money is sexy (and powerful). For financial analysts and CEOs alike, it is also a valuable instrument to make smarter future-looking business decisions. NPV is a little thing that pop’s open a new line of thinking in your mind, and you’ll never think of future money (or variables of risk) the same way ever again. I love these little brain unlocks. Today I want to share a collection of them with you, in the hope that they’ll unlock new ways of thinking for you.
Opportunity Cost. We tend to think that the cost of doing initiative X is only financial investment that goes into it, to get, say, more revenue. But, that is not entirely true. In doing initiative X, you give up the opportunity to do initiative Y which might have delivered more happiness (or ROI). That’s the opportunity cost. A personal example. With a team spread out in NY, London and Singapore I take many long flights. I work very hard, I have at least 2 jobs, should probably take the 15 hours non-stop to Singapore to watch some movies, read a book (or five), talk to my bestie Michael who’s on the seat next to me, etc. etc. But. I feel terribly guilty that I have all this time where I can really think and get a lot of work done. That’s the opportunity cost. So what do I do? I give in to my guilt and work non-stop for 12 hours (3 hours for lunch, breakfast, walking up and down the plane for some exercise). I write three newsletters and complete one major presentation with original thought. It is the burden of the opportunity cost computation that makes me work all my hours on flights. 🙂 I’m not saying you should do as I do. But, next time you decide to take on a new assignment to solve a problem with digital marketing for your company, consider the opportunity cost (what you give up by not spending your time doing something else). Or, if you are considering investing in buying a home, what’s the opportunity cost of investing that money doing something else. It is amazing how differently you think of the cost of doing anything once you get opportunity cost – and over time you become a sharper critical thinker.
Diminishing Marginal Utility. In English: There are few straight lines in life, every line dips. If you currently make $60k per year, doubling your salary to $120 might make you 10x happier. But, doubling your salary again to $240 might only make you 2x happier. That’s basically the concept of diminishing marginal utility. You can apply it to the enjoyment you get from one gourmet hamburger you eat at lunch to eating two or three. Diminishing marginal utility. Let’s apply this concept to your business, and flip to diminishing marginal utility’s cousin diminishing marginal returns. You look at your data and find that the Cost Per Click is $40 to sell 10k Samsung S20 phones (total cost of $400k). You go to your boss and ask for an additional $400k budget and promise to drive another 10k phone sales. What are the chances you are going to be reprimanded? Super high. You see getting 2,000 additional sales will have a CPC of $45. The next 5,000 will have a CPC of $60, and the last 3,000 phone sales will have a CPC of 170. Diminishing margins of return. Diminishing margins of utility (consumption) and diminishing margins of return (production) are all around you. Understanding this concept will ensure you make smarter decisions about how happy you will be in life (consumption) and at work (production). 🙂
Causal Inference. You’ve heard this one before, correlation does not imply causation. Causal Inference is the science (and art!) of figuring out that one thing did cause another. Examples of spurious correlations are everywhere. Let me share a personal favorite. A long, long time ago I’d read the article that men who kiss their wives goodbye before they leave for work live longer. So, before I was married, I’d decided I’m going to kiss my future wife goodbye every day. 🙂 It is only later, much later, after a few years of kissing goodbye, that I realized the act of kissing goodbye was a correlation. The causal factor that I loved my wife deeply, this made me happy, and happier men have fewer health issues and as a side effect live longer. Two decades-plus of marriage, I still kiss my wife goodbye before going to work every day… But, not to live longer. In business, causal inference is an incredible tool for powering smart decisions. What really drove that increase in sales of 2x? Why has the innovation pipeline in your company dried up? Does TV really drive long-term brand value that results in repeated purchases? Was requiring a Masters degree for all Manager positions responsible for decreased employee happiness? Causal inference allows us to identify that one thing caused another, and very often allows us to answer questions that have not been answered in the past. Some of the most exciting work I do as an analyst is in this space. It is often deeply satisfying.
Lump of Labor Fallacy. We are at this unique moment in technological evolution. Narrow AI is upon us, even that will have an impact on labor markets. Quantum computing will expand what might be possible, I believe it’ll contribute in meaningful ways towards Artificial General Intelligence and then we are in for a ride. Life, as we know, will evolve to something we don’t know. One dimension I worry about is what happens to work as we know, to employment. Many believe there will be mass unemployment as “machines” take over and there will be a catastrophic impact on society. The reality is, of course, nuanced and complicated. The cleanest explanation, for me, comes from understanding the lump of labor fallacy. The lump of labor fallacy is the notion that there are a fixed number of jobs in the world (a finite amount of work to do). So, if more work is being done by machines or by immigrants or in overseas factories or more women entering the workforce… Then we will run out of work. Beyond the worry about machines/automation, believers of the lump of labor fallacy are active protectionists, often anti-immigrant, and live life (and politics) as a zero-sum game. The reason it is called a fallacy by economists is that the amount of work (jobs) flexes over long periods of time. Prof. David Autor has a great example to internalize this reality: A hundred years ago 70% of every dollar was spent on food, clothing, and housing. Now, this number is around 40%. With 30% of the income freed up, people eat out more, they take yoga classes, they are partaking in a lot more travel and entertainment, etc. etc. All of this does something magical: It creates new jobs that never existed before. The number of jobs, the amount of work to be done by humans, expanded – even as massive automation came online, immigration increased, loads more people were employed in China and pulled out of poverty, and, while nowhere nearly at sufficient levels, more women became business leaders. As you contemplate the next 100 years, consider the fallacy of believing in a lump of labor. It leads to low-quality thinking. BUT. Everything’s not roses. It rarely is in life. While the long-term trend is clear, there are short-term implications we have to thoughtfully address. When these changes happen, not everyone will have the skills or easily apparent opportunities to make the transition to these new jobs being created in the economy. Our government, policymakers and influencers (not the Instagram kind) will have to put programs in place to ensure a smoother short-term transition. Lump of labor is a fallacy, but there is still something we have to do (and it is not activating protectionism as that is only giving false hope). When it comes to automation and artificial intelligence, there will be lots of jobs that will change, some will cease, but a whole lot more new jobs we can’t imagine will be created. We will have to ease the short-term transition.
Comparative Advantage. This is a complicated idea, but one with immense practical applicability. If Person X is the best at doing something, they are said to have an absolute advantage. President Obama. Simone Biles. Alan Mulally. Gustavo Dudamel. In their respective fields, it can unquestionably be said they have an absolute advantage. It is possible that they are all also brilliant at Web Analytics. Even if they were, they can’t do Web Analytics more cheaply than me! If they did Web Analytics, they would be giving up a higher paid job (president, gymnast, CEO, conductor) to do something that would pay them a lot less (as is the case with me!). What I have over those four incredible people is a comparative advantage at Web Analytics. (To tie it to item #1 in this newsletter…) What it costs Person X to do something is the opportunity cost – and often they can use that opportunity to do something far more productive/enriching. An individual may have an absolute advantage at one or two things, but comparative advantage at many fewer things. The cool thing is that everyone has a comparative advantage at something! Your action item from this economic concept? Find people’s comparative advantages, rather than compare their absolute advantages. Consider their opportunity costs. Here’s a personal example. My wife is better at pretty much everything that needs to get done in the house. Cooking. Cleaning. Managing our finances. Planning incredible family trips. Everything. How should we decide who does what part of the household work? My wife is exceptional at cooking, but only somewhat better than me at cleaning. She has a comparative advantage at cooking, and I have a comparative advantage at cleaning. Hence, I should do the cleaning even though she is better than me at it. The gap between us is small. A business example. It is sort of ingrained in us that the person who is always the best in your team at something should do the task. Except, that is not efficient. What matters is the gap. For some tasks, there’s someone else who’s almost as good as you and they should do the task. In our team, I always consider the comparative advantage of each individual for a given task and then assign the person with the best comparative advantage. Often this means, considering opportunity cost, I could have done task Y better and yet it does not make sense for me to do it. It is an unintuitive concept. But, once you get it you’ll see incredible benefits from executing against comparative advantages.