This blog post summarizes the book titled “The Formula - The Science Behind Why People Succeed or Fail”

Introduction

The author has spent his entire life looking and studying Networks. In the introductory chapter, he mentions the way he and his researchers stumbled on to this topic. His team was initially working on applying network science methods to disaster relief methods and tried to publish their findings in many journals. They failed. The team then changed their research direction to the topic of success. There found some patterns in the set of successful people they had chosen to analyse and subsequently wrote a paper about it, which was published in the Science journal. Motivated by the outcome, the author and his team set out to quantitatively analyze and cull out patterns across the lives of successful people. The result: They have culled out certain variables that show up across vast majority of cases. The book is an exploration in to these variables that characterize success

Before delving in to the variables that define success, the author starts off by giving the definition of success

Success is the reward we earn from the communities we belong to. They are external, not internal; collective, not individual

Does the above definition bother you ? Well, if you put yourself in the shoes of a research scientist, then the above definition makes perfect sense. It is impossible for someone to look at personal fulfillment metric as such as thing is not readily quantifiable. If you look at vast amount of self-help literature/movies that try to capture success, most likely there will be a heavy dose of personal fulfillment piece to it. But to study something, it must be observable, which by default takes us in to the realm of external and community recognized metric.

The author has distilled all his work on this topic in to five rules, i.e.

1. Performance drives success, but when performance can’t be measured, networks drive success
2. Performance is bounded, but success is unbounded
3. Previous success \(\times\) fitness \(=\) future success
4. While team success requires diversity and balance, a single individual will receive credit for the group’s achievements
5. With persistence success can come at any time

The Red Baron and the Forgotten Ace

The author contrasts the lives of two German military personnel, Manfred Von Richthofen and Rene Fonck. Both were great fighter pilots who had gunned down many planes during the war. However Richthofen became successful and has been mentioned in several articles, media outlets and has captured the imagination of many, over several decades following his death. Rene on the other hand, despite his performance is forgotten. Why is that the case ? The author distinguished between performance and success.

Your success isn’t about you and your performance. It’s about us and how we perceive your performance

Performance, in the context of the book, relates to all the hard work you put in, all the hours you toil in order to get better at something. It is the main reason your are able to give a performance, be it writing a piece of code, creating a start up, writing a book etc. Success, on the other hand, is different. It is contingent on external world realizing your performance. Success is a collective measure, capturing how people respond to our performance.

Richthofen was successful because he was useful to his network/community, while Fonck, despite giving a great performance, was not useful to his network and has faded to oblivion.

The chapter raises an interesting question:

How do success and performance relate to each other ?

Let’s say you are toiling away at becoming better at something, is there something that you need to pause and reflect? Are you paying attention to the networks that you are part of ? Are you useful to the network that you are part of?

Grand Slams and College Diplomas

The author analyzes two distinct fields - SAT scores of kids attending various types of colleges AND tennis players. In the case of tennis players, an analysis based on truck loads of data suggests that Performance is a driver of Success. However, in the case of college admissions, the data shows that given a reasonable performance level, the college which a kid attends has little bearing on his success levels. More importantly, data crunching showed that the biggest variable contributing to the success of the kid was : Whether he or she had applied to top colleges ?. It did not matter whether the kid got through. This goes on to show that Performance and ambition*, working in tandem, seems to determine success

The $2 Million Urinal

The author focuses his attention on Arts, a field where performance is very difficult to measure. By a chance encounter with one of his friends, the author manages to get hold of a vast repository that contains details about various artists across several decades. Using his network analytics toolkit, the author sees the following patterns

• There are network hubs across the world, that play a big role in setting the price of an art piece.
• There are certain islands too, that comprise dense connections, but are not at all connected to the major hubs of the world
• Value in any piece of art lies in the network around it

By analyzing a set of artists who are far removed from the hub centers, yet have made it big, the author sees a pattern that all such artists avoid the comfortable and common route of exhibiting repeatedly at the same galleries. Their secret to their artistic success hinged on their ambition and eagerness to shop around.

Performance needs to be empowered by opportunity. We need to re-frame the all-too-frequent assumption that aiming for the top means scraping our way up from the bottom. Our collective definition of success requires us to think about the ways that our work impact others. If we want to bring the world-up-there nearer to our doorsteps, we need to find the hugs that can accelerate out trajectories and reach out to them. We need the ambition to aim for the top right away.

How Much is a Bottle of Wine Worth ?

The author highlights a very important point that we often tend to neglect; when the performance is nearly identical among a set of people, the one who wins has a healthy dose of luck on this side. It is fair to say that there is immense talent pool available for any job, for any opportunity up for grabs. If you picture yourself as one of those candidates in the pool and imagine a set of experts deciding whether you should be given the ONE opportunity, that you are seeking: you will inevitably come to the conclusion that there should be other factors that determine your success.

The author looks at the following scenarios

• Wine experts judging the best wine from a lot(that are all equally good)
• Music Competitions: Performing artists who are judged by a panel of judges
• Job interviews

In all the above cases, when the performance is almost indistinguishable, there are other human biases that determine the success of an individual. Since there are no stopwatches that can accurately measure the difference between two wines, two music performances, two candidates for a job, it is inevitable that other factors are going to determine the success. How could one prepare for such a situation where one has done his best as far as performance is concerned ? The author is of the following view

If you want to win competitions, you need to enter a slew of them. If you want to get a job, you must send out plenty of CV’s. If you want a starring role, you need to step up for audition after audition. You can’t control whether you’re the first or last to take the stage, but just as you need to buy multiple tickets to widen your odds of winning the lottery, you’re far more likely to score a preferred spot on the roster if you keep showing up

Success can self-generate, growing in proportion to its size. If you win once, you’ll win again. And again. And again.

Superstars and Power Laws

The author draws the examples of superstars in various fields, to highlight the second law

Performance is bounded, but success is unbounded

Most of the world is based on Gaussian law; the heights of various men and women follow normal distribution, the weights follow a normal distribution etc. This means that the probability of seeing an extreme observation is practically ruled out. However when you look at other socio-economic outcomes such as wealth distribution, success, poverty, network clusters: these follow power law. If something follows a power law, then the probability of seeing an extreme event has a small probability, but not an insignificant one.

The reason most of superstars achieve success that seems unbounded is, SCALE.

Exceptional reward only comes from talents that are easily and cheaply disseminated. A performer or author may put out roughly the same effort whether ten or a thousand people show up in the audience or buy the book. To be a superstar economically, your performance must scale.

Exploding Kittens and Sock Puppets

In this chapter, the author explores Preferential attachment, a term coined by the author himself, while investigating the inordinate traffic that sites like Google, amazon attract, as compared to billions of sites that are in the long tail of web. The fact that an initial traffic to the site, attracts more traffic to the site, can be seen in many aspects of our lives. The author gives many examples where field experiments that reiterate this point. So, if this phenomenon is wide spread, how can one take advantage of it ? By paying attention to those first few customers of your service, by paying attention to the first few who sign up, the first few who leave a review of your book, the first few who endorse your cause.

Invisible early birds can play an alarmingly substantial role in the success or failure of a new project

The Era of the Beholder

The chapter delves in to various experiments: Focus was on splitting the factors behind hits in to popularity component and genuine quality component. There were certain authors such as J.K.Rowling who genuinely wanted to find this in her own line of work. Unfortunately even though she published anonymously, the community got a wind of it and her anonymous work catapulted in popularity and sales. These experiments highlight the role of self-fulfilling prophecies that play a major role in the success. All the author’s analysis point out to reinforcing the following equation

\[ \text{previous success} \times \text{fitness} = \text{future success} \]

In the case where there is a massive dose of previous success, fitness component can fall short, and yet produce a massive hit that might be difficult to comprehend. In some cases where fitness dominates, the story is a familiar one; a underdog with vastly superior capabilities walks in to a crowded market and knocks everyone off(Google, Amazon, Facebook, Ben and Jerry). There are many examples where by being an awesome fit can compensate for the lack of previous success. However in majority of the cases, where one might gawk at some of the hits, the result could be combination of both the factors.

Kind of Conventional, Kind of Innovative, Kind of Blue

The author focuses on the way “success” is determined behind collective efforts. Analyzing data, the author concludes that the pattern behind a successful team outcome is driven by

• the team should have diverse skillets
• there should one strong leader to guide the team

On the face of it, the above findings look clichéd. Of course, these factors are obvious. What makes this chapter interesting ? Well the above clichéd statements are backed by big data analytics and network analytics, and thus makes the above more believable.

The chapter talks about Brian Uzzi, a professor at Kellogg, who looked at Broadway data and saw a pattern: tightly knit teams didn’t do well and on the other extreme loosely linked teams did not perform well. All the hits on Broadway seemed to desire a careful balance between convention and innovation, which is best offered by a mix of collaborators.

Another research study mentioned in this chapter is the analysis of GitHub projects, that showed

Balance was nowhere to be seen. Instead, in many cases, the lion’s share of the programming was being done by a single team member. And the bigger the team was, the harder that major contributor worked. In other words, each team had a naturally emerging leader. And as the number of team members increased, the more the leader dominated the team’s output

The Algorithm that found the overlooked Scientist

I found this chapter very interesting. It highlights the credit allocation that all of us would have witnessed at various points in our life. If a piece of work is done by a team, who walks away with the credit ? Is it a fair allocation ? How is allocation done in the first place? The answers to the question vary based on the context. However this chapter focuses on a few patterns by studying this problem across diverse examples and interesting questions such as:

• Douglas Prasher was the first to spot the possibility of GFP, but the Nobel went to different set of scientists
• How does the Nobel committee allocate credit to the work done by a bunch of researchers working on a problem collaboratively ?
• Musical bands: credit is disproportionately allocated.
• Should you collaborate with a leading researcher in a field, so that you can get a paper published with him/her ? Is it good for you ? Will you get the credit at all ? Will the leading researcher get all the credit and you are forced to oblivion?
• If you are an invisible player and want to come to limelight, is there a way ?

Ignorance of the laws governing credit allocation and human nature can make all the work we put into a project vanish. understanding the processes behind the law that single individual gets the lion share of recognition is crucial. #+end_quotecd

#+begin_quote Credit is often assigned by invisible networks, not by individual arbitrators.

One of the takeaways from this chapter is that it is good to work with a leading researcher/ leading firm / leading whatever for a certain period of time. If you are after success, it can only come if you break away from the initial association and master your performance in such a way that the network around you rewards the performance.

Einsteins Error

The final chapter delves in to the mysterious nature of creativity. At the outset, it appears that our creativity atrophies as we age. Our general productivity levels go down. Looking at the brilliant contributions of scientists, it looks like the brilliance of any person is in his/her early years. So, are we to just accept the fact that nothing can be done as we age and we are destined to be a deadwood as we age ?

This chapter liberates you from that thought. The author and his team work for two years to put together a dataset that looks at scientists and their success, measured in terms of citation count. The “aha” moment came, when the author had his team decided to separate the analysis of live and dead scientists ? They came to the conclusion that Creativity has no age. If that is the case, why do many people peak in their early careers ? The reason is productivity. Most of us tend to lean towards becoming less productive as we age. The author gives the analogy of lottery ticket. Each work that we do in any year can be compared to that of a lottery ticket. Each has an independent chance of being recognized by our network. However if in a specific year, we buy 30 lottery tickets, we increase the odds of success. The analysis of success of various scientists showed that success came around periods of high burst of activity. This means that it is not age but your persistence in continuing research is what determines the success. With persistence, success can come any time

Your chance of success has little to do with your age. It’s shaped by your willingness to try repeatedly for a breakthrough.

The author synthesizes all the findings in to a concise equation \[ S = QR \]

where \(S\) stands for a project’s ultimate success, \(Q\) stands for the person’s ability and \(r\) stands for the as-yet-unknown merit of the idea. The findings also point to a harsh-truth - Q factor for any person is constant and does not change. The finding also says that \(Q\) factor is dependent on your vocation. This means that by sampling various fields, you can get a reasonable estimate of your \(Q\) factors. One can then make a wise decision on your vocation. This is the same argument made in the Range.

Conclusion

The author concludes the book reiterating the five laws of success by analyzing the life of Einstein. Of course, not everyone is Einstein. But the takeaways from viewing his life from the perspective of the 5 laws is very illuminating.

Takeaway

When I reached the end of the book, I somehow did not want the book to end. It was amazing to learn to view “success” from the standpoint of five laws. We are usually bombarded about success of any individual based on his/her performance. The book is a refreshing perspective on the science of success. Thoroughly loved it. I wish I would have had access to the content of the book, many decades ago.