Concave, Convex, and Nonlinear Fragility

Nassim Nicholas Taleb’s book, “Antifragile,” is a wealth of information. I’ve returned to it often since first reading it several years ago. My latest revisit has been to better understand his ideas about representing the nonlinear and asymmetric aspects of fragile/antifragile in terms of “concave” and “convex.” My first read of this left me a bit confused, but I got the gist of it and moved on. Taleb is a very smart guy so I need to understand this.

The first thing I needed to sort out on this revisit was Taleb’s use of language. The fragile/antifragile comparison is variously described in his book as:

  • Concave/Convex
  • Slumped solicitor/Humped solicitor
  • Curves inward/Curves outward
  • Frown/Smile
  • Negative convexity effects/Positive convexity effects
  • Pain more than gain/Gain more than pain
  • Doesn’t “like” volatility (presumable)/”Likes” volatility

Tracking his descriptions is made a little more challenging by reversals in reference when writing of both together (concave and convex then convex and concave) and mis-matches between the text and illustrations. For example:

Nonlinearity comes in two kinds: concave (curves inward), as in the case of the king and the stone, or its opposite, convex (curves outward). And of course, mixed, with concave and convex sections. (note the order: concave / convex) Figures 10 and 11 show the following simplifications of nonlinearity: the convex and the concave resemble a smile and a frown, respectively. (note the order: convex / concave)

Figure 10 shows:

So, “convex, curves outward” is illustrated as an upward curve and “concave, curves inward” is illustrated as a downward curve. Outward is upward and inward is downward. It reads like a yoga pose instruction or a play-by-play call for a game of a Twister.

After this presentation, Taleb simplifies the ideas:

I use the term “convexity effect” for both, in order to simplify the vocabulary, saying “positive convexity effects” and “negative convexity effects.”

This was helpful. The big gain is when Taleb gets to the math and graphs what he’s talking about. Maybe the presentation to this point is helpful to non-math thinkers, but for me it was more obfuscating than illuminating. My adaptation of the graphs presented by Taleb:

With this picture, it’s easier for me to understand the non-linear relationship between a variable’s volatility and fragility vs antifragility. The rest of the chapter is easier to understand with this picture of the relationships in mind.

Team Composition

When a potter begins to throw a pot, she picks up a lump of clay, shapes it into a rough sphere, and throws it onto the spinning potter’s wheel. It may land off-center, and she must carefully begin to shape it until, it is a smooth cylinder. Then she works the clay, stretching and compressing it as it turns. First it is a tower, then it is like a squat mushroom. Only after bringing it up and down several times does she slowly squeeze the revolving clay until its walls rise from the wheel. She cannot go on too long, for the clay will begin to “tire” and then sag. She gives it the form she imagines, then sets it aside. The next day, the clay will be leather hard, and she can turn it over to shape the foot. Some decoration may be scratched into the surface. Eventually, the bowl will be fired, and then the only options are the colors applied to it; its shape cannot be changed.

This is how we shape all the situations in our lives. We must give them rough shape and then throw them down into the center of our lives. We must stretch and compress, testing the nature of things. As we shape the situation, we must be aware of what form we want things to take. The closer something comes to completion, the harder and more definite it becomes. Our options become fewer, until the full impact of our creation is all that there is. Beauty or ugliness, utility or failure, comes from the process of shaping.Deng Ming-Dao, '365 Tao - Daily Meditations'

Building a high-performance team from scratch is just as difficult as turning a low-performing team into a high-performing team. However, there are very different reasons why each of these scenarios are difficult.

Like the potter beginning with a lump of clay, when forming a new team we must understand what we have to work with and have a clear idea of the outcomes we want. As we shape the team, we have to be mindful of how the individuals on the team are changing – or not – and whether those changes are moving toward the outcome. If not, we either need to change the desired outcome or alter the material we have to work with, that is, change out one or more people so that the shape of the team is better suited to reaching the desired outcome. It is also important to monitor the speed at which the team is formed or shaped. Too fast, and the team may not coalesce in a way that is healthy or productive. Too slow and they may not coalesce at all, they may “tire” of the slow pace and disengage.

With existing teams, we may have a limited range of options to change the roster. This is more like the an existing piece of pottery that has been fully set.

Estimating Effort – Adaptation

I’ve been running the informed intuition (or if you prefer, “disciplined intuition”)  approach to estimating effort for close to nine months now. For the most part, it has gone very well. The primary objective – inspire and support a conversation around the effort needed to complete a story – has most definitely been realized. Along the way the process has shifted to better support both the conversation and the team’s ability to internalize the process.

Originally, it was proposed that teams rate each of the effort characteristics on a sliding scale – 1 to 10 or 1 to 15, or whatever the team decided was most useful. Feedback from the teams lead to the discovery that it is easier to evaluate each effort characteristic using the modified Fibonacci scale rather than a sliding scale. This provides continuity across the method in that everything about a story’s effort value is considered using the same scale. It also reinforces the rationale behind the use of the Fibonacci scale and seems to facilitating the team’s ability to internalize the method. They are moving more quickly when deriving effort values.

A second adaptation is the use of several sets of characteristics, depending on the type of story, the predominant functional area represented by the team, and the nature of the work. For example, a story that involves the development of a computer board has a different set of criteria from stories that involve the creation of firmware for the board or the UI/UX features of the hardware product. The sets usually contain 3 or 4 common characteristics, such as “complexity” or “dependencies.” However, the hardware board may include something like “part sourcing” or “compliance testing.” This illustrates the importance of having the team deconstruct what “effort” means in the context of their world. When they determine the characteristics, the follow-on conversations about the effort are much more robust and meaningful.

In essence, this method is a reflection of the product owner’s responsibility for the “what” of the story and the team’s responsibility for figuring out the “how” of the story. “What I want,” says the product owner, “is an estimate of the effort involved to complete this story.” The teams effort criteria demonstrate to the product owner how they arrive at any particular value.

Intuition and Effort Estimates

In his book, “Blink,” Malcom Gladwell describes an interview between Gary Klein and a fire department commander. A lieutenant at the time, the firemen were attempting to put out a kitchen fire that didn’t “behave” like a kitchen fire should. The lieutenant ordered his men out of the house moments before the floor collapsed due to the fire being in the basement, not the kitchen. Klein later deconstructed the event with the commander and revealed a surprisingly rich set of experienced-based characteristics about that event the commander used to quickly evaluate the situation and respond. The lieutenant’s quick and well-calibrated-to-the-situation intuition undoubtedly saved them from serious injury or worse.

Intuition, however, is domain-specific. This same experienced-based intuition most probably wouldn’t have served the commander well if he suddenly found himself in a different situation – at the helm of a sailboat in rough water, for example, assuming the commander had never been on a sailboat before.

In the context of a software development environment, a highly experienced individual may have very good intuition on the amount of work needed to complete a specific piece of work assigned to them. But that intuition breaks down when the work effort necessarily includes several people or an entire team. So while intuition can serve a useful role in estimating work effort, that value is generally over-estimated, particularly when it needs to be a team estimate.

Consider work effort estimates when framed by Danial Kahneman’s work with System One and System Two thinking. System One is fast, based on experiences, and automatic. However, it isn’t very flexible and it’s difficult to train. This is the source of intuition. System Two, however, is analytical, methodical, intentional, deliberate, and slower. Also, it’s more trainable. It’s when the things that are trained in System Two sink into System One that new behaviors become automatic. With work effort estimates, we must first deliberately train our System Two using a method that is more deliberate about estimating before we can comfortably rely on our System One abilities.

Once calibrated, any number of changes could signal the need to re-calibrate by employing the deliberate process. Change the team composition and the team will need some measure of re-training of System One via System Two. Change a team’s project and the same re-training will need to occur.

The trained intuition approach to estimating effort develops what Kahneman called “disciplined intuition.” Begin with a deliberate, statistical approach to thinking about work effort. Establish a base rate using the value ranges for the effort characteristics. With experience, the team can begin to integrate their intuition later in the project process. If teams lead with their intuition (as is the case with planning poker and t-shirt sizes), they will filter for things that confirm their System One evaluation. With experience and a track record of success from training their intuition, teams can eventually lead with an intuitive approach. But it isn’t a very effective way to begin.

This method also leverages the work of Anders Ericsson and deliberate practice. The key here is the notion of increasing feedback into the process of estimating work effort. The deliberate action of working through a conversation that evaluates each of the work effort characteristics introduces more and better feedback loops that help the team evaluate the quality of their decision. Over time, they get better and better at correcting course and internalizing the lessons.

It’s like learning to drive a car. A new driver will leverage System Two heavily before they can comfortably rely on System One while driving. This is good enough for most driving situations. However, it wouldn’t be good enough if that same driver who is competent at driving in city traffic was suddenly placed on a NASCAR track in a powerful machine going 200 miles per hour.

A NASCAR track might be where we would go look for expert drivers but not where we would look for competent delivery truck drivers. For work estimates on software projects, we’re looking for a level of good enough that’s a reasonable match for the project work at hand. And we’re looking for better than untrained intuitive guesses.

We’re Good, Yes?

No.

No, we’re not.

I’m adding this phrase to my list of markers that indicate things in a relationship are still not settled. It’s another form of the “seeking forgiveness instead of asking permission” bromide. A self-printed get-out-of-jail-free card. If not that, it’s a dodge to get out from under the burden of an uncomfortable situation at the expense of leaving things tangled and for the most part unresolved.

Here’s a typical scenario.

A product owner or executive faces a decision that affects the workload on a team. Rather than work with marketing, for example, to defer their request for new features to a future release or shift the delivery date to accommodate the request, the decision maker takes the easy path, agrees to the change without adjusting anything else in the system, and drops the extra work on the team.

To make matters worse, the team is informed by email. The team is understandably upset and more than a little confused about the immediate change in course. It’s left to the scrum master to make sense of the e-grenade and deal with the shrapnel. The expected back-channeling and grousing quickly attracts the attention of a wider audience and a full-on electrical storm ensues.

After way too many expensive people are involved and someone with some skill and authority gets control of the situation, work gets renegotiated, timelines are shifted, and work that could and should have been done by the original decision maker gets done by a cadre of ancillary and executive staff.

The original decision maker circles back around to the scrum master, apologies for the “misunderstanding,” and dashes off with a wave and a “We’re good, yes?”

In all likelihood, you’re not. In fact, the difficult conversation that needs to happen is just beginning. What lead up to this explosion? How could the decision maker handled the situation better? What do they need to succeed at navigating future occurrences like this with marketing? What’s different such that the team has confidence this won’t happen again? Does the decision maker understand the consequences to taking the easy way? The hits to time, money (in terms of salaries), and morale can be significant, particularly if  scenarios like this are a frequent occurrence.

Whether you find yourself about to utter this phrase or you’re on the receiving end, know that the work to resolve the issue and move forward has only just begun. Pick up the pieces, learn from the experience, and build something better.

Haiku #20

A simple framework.
Infinite possible ways.
One step at a time.

Memorial Day, 2020

I have forgotten where I discovered this picture. It was many years ago. I do not know who these men are or when and where this picture was taken. (If you know, please drop me a line.) I’ve copies of it on virtually every chunk of technology I own that’s capable of showing pictures as a frequent reminder and image for contemplation. It is rich in meaning in many different ways.

Judging by the amount of surrounding destruction, I’d guess these men are deep into Europe, perhaps even Germany. The uniforms suggest Spring, perhaps. Not warm enough for Summer, not cold enough for Winter. Perhaps they are toasting VE day, perhaps having survived the liberation of yet another city, perhaps having survived a recent battle, or maybe just celebrating being alive in the moment.

The soldier on the left appears to have what looks like a Thompson submachine gun on his lap, suggesting things in the area are not as casual as the wine bottle and raised glasses might suggest.

To all who have served us in the defense of Freedom and Liberty: My sincere and deep appreciation and most humble thanks.

Thinking Agile about the Pandemic

[Note: The fact that the SARS-CoV-2 virus pandemic is on everyone’s mind has given me an opportunity to expand the scope of topics I may consider on The Agile Fieldbook. Specifically, relating current events to Agile and systems thinking.]

 

I’ve been thinking a bit deeper on the frequent comparison of flu deaths with highway traffic deaths, total US deaths in the Vietnam War, or any variety of raw number comparisons. I’m  working to get at something that feels to be an underlying mis-match in such comparisons.

Part of the challenge is that self-proclaimed epidemiology experts are popping up like Spring daffodils, busy asserting themselves as consummate experts in statistics and government policy while asserting themselves as enforcement authorities. And the Internet has been an amplifier for the echo chambers created by rabble. In short, finding the signal in the noise has become much harder. I can’t recall a time when there has been this much manufacturing and shoveling of confirmation bias around the world. Alas, it’s one supply chain that has grown significantly more robust.

At the heart of the raw number comparisons is a category mistake. Stopping at an equivalence of mortality across all categories for cause of death gives rise the category mistake. Not all causes of death should be considered equal when searching for a course of action that will affect millions – in the case of COVID-19, billions – of people. There are many differentiating factors that could be considered in the case of viral pandemics and traffic deaths. The principle one, in my view, is agency.

I can choose a robust and enjoyable lifestyle that significantly lowers my risk to death due to highway accidents (to use that number for my analysis.) In fact, I have done exactly that. A four mile commute to the office, all on local streets where the highest speed limit is 45 MPH…for exactly 3 blocks. To those that declare “But, many people can’t do this.” my reply is “Maybe.” There will certainly be outliers for a variety of reasons. But in many of these cases, the individuals are nonetheless making choices. Perhaps they don’t want to move or they don’t want to change jobs or they don’t want to up-skill or… There are likely a confluence of many choices in the mix that make it appear they are stuck or trapped. Frequently, even in the outlier cases, when circumstances press hard enough, they “find” opportunities and make changes, perhaps even subsidized by local and federal governments. But that’s a topic I’ll leave for much more qualified bloggers to tackle.

I can make other choices in the form of the car I drive or the route I drive to my destination. I can chose the time of day I drive for errands or the frequency with which I need to run them. I can chose whether to use my smart phone while driving or engage in some other distraction while driving. Or I can choose not to drive at all and take the bus, train, bike, walk, or a combination of any of those.

With a viral infection – as we are learning now – there is virtually no personal agency. The only way to avoid the adverse consequences is to severely curtail our lifestyle. Now. There’s no easing into it. No evening classes at the college annex to up-skill our ability to dodge the virus. No Ecopass that lets us leave the breathing up to someone else. Not much of any choice for replacing a stalled lifestyle with a different one because they’re all stalled.

Which gets me to the thinking behind “Mass transit kills.” It does so because its an efficient vector for transmitting biological infections. The early studies show how quickly COVID-19 spread due to air travel followed by trains, taxis, and buses in crowed urban settings. A fatal car accident, however, is a local event. First responders and surrounding communities are not at risk of death due to the now static car accident. A viral or bacterial outbreak is dynamic and spreads just by virtue of people moving around. Globally, how long would humans have to drive cars before the death toll matched that of the number of deaths that have been attributed to plagues and pandemics throughout history? And historically, plagues and pandemics moved at the speed of rats, mosquitoes, and ox carts. Today, they can move just shy the speed of sound.

Having read close to a couple dozen COVID-19 related research papers (surprisingly, none of them authored by CNN/MSNBC/FOX/CBS/ABC/NBC/BBC et. al.), the chances that we’re approaching a pandemic that won’t offer much of a lead time are increasing. The growth of human population has greatly increased the adjacent possible for animal virus’ to make the jump to humans. The probability of an asymptomatic contagious period combined with lethal morbidity increases as the adjacent possible horizon expands. If such a viral combination were to occur, mass transit will be that virus’ best friend.

My thinking is probably incomplete on this matter, so I welcome your comments.