Writing

Being an engineering graduate you come to notice a very common theme amongst everyone involved in the profession. It is a coalition of problem solvers that use their extensive knowledge to solve the most problematic issues of society. It is definitely correct to say that each specific discipline of engineering has its own methods and way of thinking. However, the beauty of the profession is the principles, methodologies and approach used by anyone who is an engineer.

From this I came to notice that all potent engineers share a core belief of essentialism. That is to say, that they approach engineering without numbers, formulas and diagrams right from the jump. This means that they take a very simple and almost philosophical approach to engineering no matter what the problem is and what field of engineering they are in. The amazing thing about this is that the best engineers do this subconsciously. I am about to go through this subconscious and essential thought process.

No fame

Excellence in any profession can lead to fame and monetary gains. But the best at any profession do what they do out of pure joy in their work. Think about athletes, actors and musicians. Engineers are no different. They do not want exposure. Often the best work is produced when they separate themselves from the idea of exposure.

Social, political and economical footprint

The impact and reach of engineering is immense. So it comes as no surprise that there are far reaching footprints. The creation of different technologies to ease life, from apps to bridges, means that there will be social, political and economical footprints. It is an engineer's job to make sure that as much as possible, these footprints are impactful in a positive way. It is an engineer's job to work in a space between creation and operation, pivoting towards any problems that may arise and maintaining high functionality.

Learning from the past and others

The best teacher of the future is the past. This most definitely is prominent in engineering. The history of past designs, inventions and theories are widely used to this day. This could be to improve past engineering endeavours or to build new ones. To solve the most prominent problems of today, engineers use influences from the past a lot more often than people know. To add to that, other fields can also be great influences in engineering. The history of medicine, literature, philosophy, art and law are all influential to the success of the engineering discipline.

Engineering essentialism lies in the simplicity of its thought process shared by the best in its profession. The thought process is the desire of no fame, the pursuit of positive footprints and using history and other fields as an influence when needed. The beauty of this is that all these essentialist principles can be used at any stage of an engineering process.

This is the idea of accepting a new technology (product and/or service). There is a sort of oscillation that happens. The start to finish is a story of conception an adaption. Untested technology usually always creates a group of reluctant people. More and more people jump on board as more evidence surfaces that the new technology actually works. Let's look at the cycle.

The main message of the cycle is that it is not smooth. After a few successes the tech is quite overhyped and then the tech is used/implemented into situations beyond the inventor's intent - the peak. Then the idea is finally accepted to a much lower level than expected.

Economic example

• New positive info about a stock —> Price + Hype increases
• Stock prices are over-hyped and overpriced —> Price + Hype dies down. Time goes on
• Reasonable value for the stock is reached

Explaining the cycle

There are two ways of explaining this cycle:

1. Mathematical approach
2. Example based

Whichever appeals to you more you should read first - best way to understand.

Mathematical approach

System described by parameters. The system is described by parameters - up to n parameters.

$x_1,...x_n$

The rate of change is shown below

$ẋ = f_i(x_1,...x_n)$

Taylor expansion for the first approximation. The approximation for the first few terms

$ẋ = Σ_j a_{ij}x_j$

The solution to this system of linear functions is a linear combination of terms $exp(λ_kt)$ where $λ_k$ are possible eigenvalues of the matrix $a_{ij}$. These are the roots of the following equation

$P(λ)=0$

When the imaginary portion of $b_k$ of $λ_k = a_k + i· b_k$ is non-zero the expansion becomes

$exp(λ_k·t) = exp(a_k·t)·(cos(b_k·t)+i·sin(b_k·t))$

From this we get oscillations as is shown by having both the sin and cos functions. However, why do we always get oscillations? More parameters are needed to analyze a larger data set. This means $x_1,...x_n$ has to have a larger $n$.

Knowing that any polynomial can be shown as a product of real-valued quadratic terms. Some of these quadratic terms have real roots also (they can have 2 max roots). Of course roots can be real or imaginary. So with $p_0$ is the probability that both the roots are real the probability function becomes:

$p≈p_0^{n/2}$

When the the $n$ is large it means that the function is practically 0. Larger and more complex systems (which is basically all system in technology) the higher the probability of this function being 0. Hence, all systems have oscillations and follow the Hype Cycle.

Explaining the stages

Refer to the graph above

1) Innovation trigger:

• Has an early proof of concept, media interest and significant publicity
• There is no usable/commercial product
• Use a lot of first principle to utilize and maximize technology

2) Peak of inflated expectations

• Early success stories
• Followed by a lot of failures (a lot of companies fall)
• The fall from this place is when investors want to play it safe (go for established tech)

3) Trough of disillusionment

This is best done by an example

Netflix —> Failed early with competitors like Blockbuster already owning the market. Cable and video on demand was big back then too.

• Investments continue only when there are signs of improvements
• If creators cannot provide this then they often fail

4) Slope of enlightenment

• More examples of benefits show from the tech
• More users are found
• 2nd and 3rd gen versions

Netflix delivering movies —> Netflix being a TV studio

5) Plateau of Productivity

• Mainstream adoption takes off
• Everyone sees the convenience of the tech

The above was a cycle that is seen by many tech products/services that are brought into production. From startups to major companies - this is always apparent to a degree.

Sources: Gartner and Research Gate

The economic impact of COVID-19 is unmatched. Governments around the world have created multi-billion dollar bailouts - having to keep intact social infrastructure and maintaining necessary institutes like hospitals, banks and business (conglomerates and corner shops alike).

Bailouts mean that there are huge injections of money that is being put into the economy - usually by creating new money. However, there is a disproportional flow of money after that injection. I will try to explain why this is through the economic term known as the Cantillon Effect.

The disproportionate flow of money

Often small businesses and normal people cannot gain access to unemployed insurance and lending programs - this is a global issue. Questions like the following arise:

• Why is it harder for middle/lower class people to attain this new money injection?
• Why is there a 'flow path' of new money?
• Why is there an injection point of the money and why it at the top? (Asset owners vs working class)

The economy is set up in a way that money benefits those with higher assets. Therefore, those with higher assets are the first to be affected by an economic boom or economic collapse.

Analogy

To better describe this, here is an analogy to show you better the flow of money.

Say there is a hypothetical island that produces goods and brings in goods to sustain life. There is a grand ship that is owned by an individual named Warren Buffet. He is responsible for the islands greatest incoming and outgoing resources - thanks to his ship. I also happen to live on this island but I am a regular fisherman. Now follow this thought process:

• Buffet has a large ship full of goods
• I have a small fishing boat with all my belongings
• Buffet is out in the rough sea ocean, away from the island one day. Large oil containers, food and medical supplies etc.
• I am closer to the shore but still quite a bit into the ocean
• A storm creates waves that rock Buffet's ship and it could tip over. The ship is carrying a lot of goods
• The same waves come towards me. They rock my boat and I am in danger
• However, rescue is for Buffet's ship first, naturally, because the assets on that ship is much greater than my meagre wooden boat. It has essential supplies for the island
• When help eventually comes to me it could be that I was able to salvage some remains, others helped and rescued me or my boat was lost

This is the Cantillon Effect. Poor naval analogy but quite a good economic one.

Richard Cantillon and his essay

Richard Cantillon (1680 - 1734) was a banker and philosopher who wrote "An Essay on Economic Theory" from 1730-1734.

In his essay he explains that early recipient of new money entering a new economy will enjoy much higher standard of living - compared to those it trickles down to. They can buy goods and/or services at a much lower price before the market realizes the trend. Then the demand (everyone wants the goods/services) and the prices increase (sellers of the goods/services know this).

Money benefits those that are wealthier and have more assets. The further away you are to impacting the economy through your assets the more harm could be dealt to you.

The Cantillon Effect

When increased printing happens the distribution is uneven. People closer to the money (banks, companies, etc.) and people who are heavily invested to these institutions access the money first. Think of this in terms of the rescue for Buffet's ship. His ship was rescued first because he had the far greater assets compared to me.

Central Banks

Central banks play a huge role in this. They are the ones that are responsible for printing this money. The injection of money is then used to make investments and other asset attaining acts.

This is mostly to ensure that if another financial crisis is to happen (disease, political instability, warfare etc) they would be safe.

Simple example: With loans investors start buying property/land.

By the time that Person B has received the new money, Person A has already bought 2 houses. By the time that person C is looking for a house Person A has a 3rd house and Person B has their house. Noting that Person A receives the money first (A > B > C).

• Redistribution from rich to poor
• Question of purchasing power
• Question of inflation also involved

Bailouts for large institutions (large banks, private equity corporations, etc) means they later increase assets by trading bonds and stocks - which are high leverage assets.

Central banks (Federal Reserve, European Central Banks etc) are very adept at doing this - they can move trillions.

The flow of new cash:

1. Central banks
2. Private equity firms
3. Land/Bonds/Stocks

It goes from 1 to 2 and then to 3.

This effect described by Cantillon is evident in any and all bailouts. The 2008 crisis saw this take place and the following years saw economists and governments work together to regulate dysfunctional flow of money if a global financial crisis was to occur again. We wait to see how much prominent the Cantillon Effect will be for the global pandemic induced economic stress.

It seems that new products and services enter the market at an ever growing speed and regularity. However, there are only a few that actually become successful. The definition of successful in this context would be an innovation* being adopted (increasing number of users/buyers) and then having a sustained life cycle (being in the marketplace for a considerable time). A clear example would be Facebook.

How do you break these bits of time and success? This can be explained using two concepts that were established in the last century that are still relevant to this day.

*Product, service, tech and innovation will be used interchangeably.

Diffusion of Innovations

Everett Rogers (1931-2004) wrote a book in 1961, named "Diffusion of Innovations", in which he said that every new product/service has an adoption curve. This curve is essentially the rate at which a population adopts a product/service. This is a very simple concept. However, to be able to create, shape, accelerate and dominate this type of curve is hard and it is what makes a product/service potent and possibly last longer.

The early version breaks down the categories and percentages of the types of customers that are interested in the product/service.

• Innovators take a chance on the new product/service before it is widely proven worthwhile
• Early adopters are those that create more buzz/stir the pot for the product/service. They invest early and solve the issues that may cause bugs
• Early majority is termed for those people that wait for the initial cohort to start using the it and certain standards and guidelines are published - fastest rate of adoption is here
• Late majority is termed similarly to the early adopters except that they are afraid of mastering this innovation - they are mass market users
• Laggards are those that are risk averse and like to stick with what they know - they usually only use it when they are forced to

Crossing the Chasm

Geoffrey Moore in 1946 wrote in his book "Crossing the Chasm" that there was a gap between early adopters and early majority that needed to be looked at carefully.

Furthermore, there needs to be tailoring of the innovation to the respective adoption segment. This is broken down into 4 parts which essentially make a life cycle.

• Emerging markets/strategies

This is all about growing the momentum. The key goal should be to make the innovation as scalable as possible. Bottlenecks at this stage should be avoided at all cost. Other aspects such as locking up distribution and finding key partners are also important.

• High Growth Strategies/Markets

This is all about making the most of the advantage that the product/innovation has. Historically, the best way of growth in business is through the word of mouth and that is achieved by creating the best experience for customers.

A good model that tries to understand the basic relationship between the user and potential users is the Bass Diffusion Model, created by Frank M Bass in 1969 in Management Science:

$N(t)$ is the number of adopters at time (t)

$m$ is the market potential, essentially the total number of people who will use the tech

$p$ is the coefficient of innovation

• The probability that someone who is not using it will start using it
• Distribution, advertising etc

$q$ is the coefficient of imitation

• The probability that someone who is not using it will start using it due to word of mouth

This is a really good first assessment tool. This allows for a good idea of the diffusion of the innovation.

• Mature Market Strategies/Markets

Most organizations find themselves in mature markets. Innovation is the key to getting on a steep growth ramp. Differentiation is the essential component of this.

• Decline

This is when the innovation is fully saturated and newer competition have arrived. This doesn't necessarily mean the innovation becomes obsolete;

The above two models allow for a grasp of how successful an innovation may be. Both have withstood the test of time and allow for a better understanding of the economic and social impact of a new innovations.

Sources: Springer Link and Value Based Management

The word timeless is often associated with items that have withstood the test of time. This is not to say that it hasn't slightly lessened in value. The item may have reduced cost of production/purchase. However, through that, it exists and will continue to do so. "Old is gold" is what this epitomizes. This is what is called the Lindy Effect.

The aged veteran

The principle of this effect is that it is perhaps not a good idea to count out ideas/methods/items that were once the centre of innovation. The idea is that the longer a non-perishable item has been around the longer it will stay around.

This is not to say that it will always carry the same value that it once did. A very common and understandable example would be books. Classics such as Catch-22, Animal Farm and 1984 are prime examples.

However, this effect is used to describe things of robust nature more than just fads/trends that fade with the popularity factor.

Albert Goldman and his article

The origin of this rather simple but far reaching phenomenon is attributed to Albert Goldman (1927 - 1994) who wrote about it in "Lindy Law" in a 1964 article.

In this article he explains what he sees in a New York deli called Lindy's where comedians would gather after performing. The concise summary of this article is that he had hypothesized that the comedian's relevancy was inversely proportional to the exposure/recognition that they would be receiving.

The comedian's last laugh

In today's world of technology it is easy to see that the comedian will have something more than the usual "15 minutes of fame". The creation of social media carries with it a pill of longevity. Even the original example of the comedian can now be extended and so can their career. A quick send of a video or a picture and this creates a chain reaction where hundreds and thousands see the work of the comedian, artist, singer etc.

For me the most notable technology that will test the Lindy Effect, in the coming future, will be blockchain and its uses in comparison to fiat currencies. There is no doubting the technological capabilities of blockchain but the ability to coexist with fiat currencies will be its greatest hurdle. The longevity is the main question. As the Lindy Effect explains, the longer something is around, the longer it will stay around. Currently, it is already on its 3rd generation. That is promising.

All in all, this is an effect that describes the survival of something that is based on persistent longevity.

Risk and reward are on opposite sides of the same coin. Countless times in life we are left with a choice of being satisfied with what we have or trying to gain more. No one decision is better than the other. Making that decision is easier said than done. The hardest thing is knowing when to stop.

What we want most in this situation is to know if going for more is worth it. It’s sort of gambling if you really take a look at it. Thats where the Gittins Index comes in. To help our gambling addiction. A sort of cheat sheet to explain when to quit while you are ahead or when to keep feeding the addiction.

Trial and Error

Unilever, in the 1970s, asked John Gittins to optimize their drug trials. Their desire was to find the most effective compound to fight a disease given a choice of several chemical compounds. Gittins was able to take a couple things away from this:

1) There were multiple options

2) A different probability of reward for each option

3) Certain amount of effort (or time, money etc) to be allocated

The paradox of medicine is that it is always looking for the best treatment but also wants to encourage experimental discovery. Practising doctors and millionaire corporation owners have their own distinct interests in medicine. Doctors want medical breakthrough(s) that will help future generations. Companies want to be relevant for a long time. What they share is the belief that the present is more important for now.

The present has a higher priority. Economists call this discounting. Essentially in a business sense it’s about the profits now rather than later. What happens if there is an economic collapse? What if the banks run dry?

Deal or No Deal

A similar concept to the drug trials is the gameshow Deal or No Deal. Contestants choose 1 of 26 boxes that they carry through the game. The range of the 26 boxes start from $0.01 and go up to $1 million.

A banker calls and offers money to not open the chosen box. The contestant chooses whether to take the banker’s deal or to keep their box. They do not know the value of the box and the deal from the banker could be lower or higher than the box that they have. This is a gamble.

Slot Machines

When you play the slot machines in casinos there is always risk and reward. There is a guaranteed payout rate and every machine has this. Gittins through his drug trial worked out a index which allowed a rough estimate to see how long a player could keep winning. This is known as the Gittins Index (or Dynamic Allocation Index). This shows us the chance of gaining more than what you already have. Just play the arm with the highest index, as simple as it sounds.

Let’s look at a machine that has a future payoff that is worth 90% of a payoff now (table below). With a Win-Loss of 1-1 it has an index score of 0.6346 while a 7-5 has an index score of 0.6212. Thats not a huge difference and an even W-L is better than a +2 W-L. The first indication of the ideology of quitting while you are ahead. A 0-0 record has an index score of 0.7029 which is interesting as it beats out a lot of winning records on the index.

Now let’s look at a machine that has a future payoff that is worth 99% of a payoff now (table below). A 0-0 record has an index score of 0.8699 which is significantly higher than the 90% machine, understandably.

Lessons learned

What the Gittins Index essentially tries to imply is that the unknown is a bit more attractive. However, we need opportunities to exploit the results of what we learn from exploring. It is always safer to back off when you have a winning record and it is always better stop playing when you have had a streak of losses.