Penny, Path, and Pair

Three temporal serendipity patterns

Serendipity revolves around a single unexpected event or a series of events that, when linked in hindsight, make up a serendipity story.

This is the second essay in the serendipity series. Here, I'll share three temporal serendipity patterns. They may enrich the current theories on serendipity or add another dimension to the serendipity taxonomies. More importantly, these serendipity patterns are useful for creating thinking habits and environmental affordances that can increase the likelihood of serendipitous episodes.

In the first stage of my serendipity research, I wanted to focus on experience and experiments without theory and concepts. I was interested in the phenomenology of serendipity unaffected by any theoretical framing and conceptualization. Only recently have I started reading books and papers on the subject. From what I've read so far, it seems that the concepts of serendipity event and serendipity episode are used interchangeably, or when the multiplicity of accidents that cohere into a serendipity episode is recognized, that unity is not conceptualized and compared with cases that qualify as serendipitous with only one accident. I’ll try to show why this distinction is useful.

Let’s start with some working definitions.

A serendipity event is a surprising event that has led to a beneficial outcome on its own or in relation to other such events.

A serendipity episode is the unity of serendipity events that has brought a beneficial outcome.

This means that serendipity events are produced backward by serendipity episodes. One unexpected event is already serendipitous only if it produces a beneficial outcome right away.

Serendipity episodes that span more than one serendipity event are of two kinds, and so together with the episodes made up of one event (or where the events are so close together that they can be taken as one), we can distinguish three temporal patterns. I call them Penny, Path and Pair.

Penny

The penny drops when we finally grasp something. It originated from the older British arcade machines. Then, it took some time between inserting the coin and when it dropped. But while in this original sense of the idiom, the dropping is expected, in the serendipitous penny pattern, the event is unexpected. Yet, the revelation of getting it, of suddenly becoming clear (or connecting the dots), is similar. In contrast to the other two temporal serendipity patterns, in the Penny case, a single unexpected event defines the serendipity episode.

Let's take, for example, the highly popular case of finding a valuable object when looking for another object. That happens to most of us many times a year. Ceratin situation amplifies the perceived value of a piece of clothing, book, key, tool or any other personal object. Then, at another moment, when searching for something else, but the perceived value of the not-yet-found object is still high, you find it. Finding it is unexpected at that moment because we are not looking for it, but the value of the encounter is realized right away.

If that's not an object but a solution to research, engineering, medical, or any other kind of problem, it's still a Penny pattern when the surprising event delivers (the key to) the solution right away.

Path

Serendipity often happens when you get lost, take the wrong turn, miss the bus, or suddenly turn with your coffee and spill it on a stranger. Something makes you take an unexpected path, which leads to a fortuitous discovery.

During a conversation at a dinner table, or when meeting some friends, accidentally, the name of somebody that you haven't seen for a very long time is mentioned. That forgotten person may come to attention in other circumstances like reviewing old photos, emails, address books, and getting notified by LinkedIn that she changed her job, or, as I mentioned in the previous post, the name pops up based on a random algorithm of your note-taking app. Whatever the case, it is some unexpected event that is not a serendipitous event so far, but you act upon it, and in this way, you take a path on which something good may happen, but you don’t know if and what.

Remembering that you haven't seen that person for a while, you make a call to catch up. Through that person, another event happens, which brings unexpected benefits. These two events define a serendipitous episode.

The Path pattern is often but not necessarily related to a person. When looking for a book in a library, a book on a very different subject catches your attention, or — a dramatic effect favored in movies — you accidentally brush a corner of a shelf, and a book drops open on the floor. Whatever the case, it somehow catches your attention, and you decide to borrow it. Then, when you read it, you stumble upon the key to a solution to a problem you did not expect to find in that book. The first unexpected event becomes serendipitous only in relation to the second, where the surprising connection is made.

Pair

One day, you find something that looks interesting but is not valuable by itself. Yet, later, a second finding can be of great value together with or in connection to the first. The name of the pattern is inspired by an old tale in which a man on his way to something found a shoe in good condition. Yet, he didn’t take it since it had no value on its own. Later, he found the other shoe from the pair and regretted not taking the first one.

Pair is there to remind us that the value comes from the pair, like in a pair of shoes. But it doesn't restrict the number of pieces to two. Another way to look at it is finding a thorn piece of the last piece of a puzzle. That last piece can be torn into more than two smaller pieces. Only united can they look like the missing piece.

Of course, the condition to qualify as a serendipitous event is to be surprising and to be a solution to a problem found when not looking for it. Again, the last finding produces the previous finding as serendipitous events backward and only then does the whole connected set of events comprise a serendipitous episode.

The serendipitous episode that triggered the current work on serendipity was a Pair type. You have most likely experienced this pattern yourself. In any case, it should be familiar from detective stories, where it is used frequently.

While being aware of the Pair pattern is important, it shouldn’t be misconstrued as advice for keeping wherever we find on our way.

These three patterns can be used to extend serendipity taxonomies. One way to classify serendipity is by the type of relation between problem and solution. There is a problem, and the solution is found when not looking for it but noticing something else and making an unexpected connection. That’s the first category. Another is when looking for a solution to a problem, a solution is found to a different problem. The third is when a situation brings to attention a problem and its solution at the same time. Christian Busch calls these three types Archimedes, Post-it and Thunderbolt serendipity, respectively. And since the first two are named after a well-known serendipitous discovery, an example is needed only for the last one.

In 1970, Bernard D. Sadow, vice president of a luggage company, was returning from a vacation in Aruba and carrying two heavy suitcases when he observed a worker effortlessly rolling a heavy machine on a wheeled skid. He made the connection, and when at work, he cobbled together a prototype by taking casters off a wardrobe trunk and mounting them on a big travel suitcase. The prototype worked; it led to a patent for “rolling luggage,” and today, suitcases without wheels are extinct.

Now, if you imagine a matrix where one dimension is the problem-solution dimension, with Archimedes, Post-it and Thunderbolt, and the other is the temporal dimension, Penny, Path and Pair, then you get nine types of serendipity. We can discuss each of the nine types and how plausible they are, as well as find examples for most of them, but let’s leave that to academics and taxonomy enthusiasts.

The main practical value of the Penny, Path and Pair patterns is to be aware of them. Research shows that opportunities for serendipitous discoveries are often missed or ignored. My conjecture is that it is even more likely to miss an opportunity for a serendipitous episode of the Path and Pair type than of the Penny type. That’s why distinguishing them is important for training attention. It should also be useful to all software makers, workplace designers, and urban planners who are willing to make our environment more conducive to serendipity.