The Mathematics of Scale [Math Mondays]

Economies of scale and Tech solutions go hand in hand.

Jun 07, 2022

Happy Monday my amazing reader,

I just got to New Jersey from Detroit. Will be staying with my brother for a week before going to India to visit my parents. If you happen to be around the NJ/NYC area or in India, give me a shout. We can meet up and discuss your plans, and targets and come up with a concrete step-by-step plan for you to ace your interviews and get your dream career.

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With that out of the way, let’s get into the idea that many engineers need to understand. This foundational idea is borrowed from Economics and is a great explanation for why Tech and Software Engineers have become such a dominant force in the economy today.

The Highlights

This post will cover the following ideas

Economies of Scale- The idea is relatively simple. Costly operations run at scale become much cheaper. This is why Tech Companies like Google put so much money chasing incremental gains in performance. To learn more about Google’s Economic Future plans, read this article. At their scale, it makes sense.
Why Tech goes hand in hand with Scale- Simply put, Tech allows us to operate at a very large scale. This is why VCs put so much money into prospective but risky startups.
How to leverage this principle for your own career gainzzz- Build basics, understand more aspects of your solutions, and you will be DAA BOMB.

This post will cover some extremely important ideas, so make sure you read through this. To understand this, remember the following equations

1^365= 1
0.99^365= 0.03
1.01^365= 37.8

Compounding + Time (number of operations) will make or break you.

Economies of Scale

If we go by the definition,

“Economies of scale are cost advantages reaped by companies when production becomes efficient. Companies can achieve economies of scale by increasing production and lowering costs. This happens because costs are spread over a larger number of goods. Costs can be both fixed and variable.”

In simple words, when we start producing more of a good, the per-unit cost of production falls. This is why Factory-Made art is cheaper than handcrafted art, even though the Factories themselves are much more expensive than a workshop.

In my domain (machine learning), we can build massive pipelines for handling large amounts of data. There are some techniques we can implement to filter and parse through large amounts of data. At lower numbers of samples, the extra complexity added is not worth it. With Big Data, these filters pay off in spades. I’m sure you can think of examples in your domain. Make sure you share them with me. I’d love to learn from you.

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Tech benefits from this along with another amazing concept. It is called the marginal cost of replication. Imagine a company has already created an item that is successful. They already have the requirements to recreate the bag. They don’t have to put money into rebuilding the product. To recreate the product is very easy and they only need to pay for materials for the new product. Tech is on steroids when it comes to this.

Take the business of creating and selling digital software and solutions. Take video games for example (Finance Friday on the industry this week, so be hyped). People/Teams put a lot of investment into creating games. However, once the game has been created, it can be sold over and over again with no problems. All digital solutions also don’t require extra materials. So they can be sold at extreme scales.

Why Tech is so powerful today

Keeping these principles in mind, it’s not hard to see why tech has become such a money maker. Tech is uniquely well suited to the two phenomena (scale + replication) that drove the industrial age.

Getting the right software job will boost your career earnings by multiples. Don’t miss out.

This is also why tech puts so much money into R&D and constant improvements. Many people are shocked when they find out about the Billions of Dollars that are poured by Big Tech companies chasing incremental improvements. 1% edge done over their millions of operations snowball hard. Remember the 3 Math Equations we did earlier? Imagine raising 1.01 to 100,000 instead of 365. Check this in Google. You will see for yourself how powerful compounding is at a large scale.

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How to use it for yourself

So how can you use this amazing principle for yourself? First, learn to think in scale. Envision everything you work on in terms of how the solution will fit into the big picture. Will it be something that is used a lot? Used occasionally but requires a lot of input? Will the results from this be kept longer or will they be updated a lot? Keeping such factors in mind will help you design solutions for the long term.

Clearly, this will require an understanding of a multitude of areas, beyond your traditional job. However, building a multi-base foundation will allow you to truly hit the next level as a developer. That is why this newsletter on multiple aspects of tech and software engineering, not just the Leetcode Style coding like other products online.

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Happy Prep. I’ll see you at your dream job.

Go kill all you popular pal,

Devansh <3

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