Measuring Maturity Development

One of my favorite mental pastimes is reducing complex concepts into algorithms or metrics. One recent item I’ve been thinking about is how to measure maturity – specifically as related to the concept of child rearing & personal development.

The topic is simple – there is a clear difference between a mature adult and a child. There is also a notable difference between adults; one that ‘really has it together’ and another that is ‘immature for their age’. The complex part is defining and measuring that in a consistent way. How would you quantify mature? How would you program a computer to recognize it?

What is most interesting to me is to find a way measure maturity development and then use that measurement to set goals for how I raise my children. Benchmarks to help me see if I’m doing a good job introducing them to new challenges. Tools to facilitate conversations I have with my wife about how we can better serve our children.

The Metric Prototype

The concept I’ve come to is a simple three number measurement showing: independence interdependence and dependents.

Lets look at each.


The concept of being able to live your life without external input; financially, physically, emotionally, etc.

I would measure this on a scale of zero to one. 1.0 meaning an individual could operate completely independently and 0.0 meaning they could not do anything for themselves.

For example, my two week old baby girl has no independence. She can not do a single thing without help from (mostly) mama: nourishing her body, cleaning herself, protecting herself from the elements, even going to sleep often requires a lot of help. To give her independence a number, it would be near-zero.

In contrast, my two year old is becoming somewhat independent. He is potty trained, except for wiping after #2. He can climb into his high chair and feed himself, given someone provides and prepares the food for him. He can take off his shoes and is learning to get undressed by himself. If I were to give him a number for his independence, on a scale of zero to one, it would perhaps be in the 0.15-0.25 range.

A well adjusted adult could, in theory, eventually hit 1.0 when they were living in a house paid for by income they generated, able to take care of themselves through a basic day, able to react appropriately to environmental and social inputs and manage their emotional health, etc.

I will note that I use the would ‘could’ which might be different that what is actually observed, this is due to the next item.

One item of quick note is that I assume a 1.0 of independence to be an adult taking care of themselves, but there is clearly a difference between scraping by and thriving. There is also the interesting case of hedonistic adaptation where an individual that was once independent might increase what they depend on, thus eventually falling below their own 1.0.


The concept of living with shared dependencies.

I didn’t originally think about this concept, but as a started to test various straw men against the other two factors, I realized that it is in an important piece of context. Many individuals chose never to strive for full independence for very good reasons. The positive aspects of this type of joint relationship are what I would measure as interdependence.

I am not yet able to make a value claim about this aspect, how much is ideal and/or which pole is better. For today I simply want to find a way to quantify its existence.

I would measure this on a scale of zero to one. 1.0 meaning an individual was completely dependent on one or more people, but was equally contributing to those people. 0.0 meaning the individual operated with no interdependence. Note that interdependence and independence are orthogonal. A person operating with zero interdependence could be completely independent, completely dependent, or anything in between.

As an example of interdependence, my wife and I have chosen to divide tasks in our lives, creating a division of labor within our family unit. This allows us each to focus on certain things we are best at. It also, by definition, creates interdependencies. Specifically, I work for a salary that provides our house with the majority of our financial income. My wife is dependent on me for that currently, though she can and has done so independently in the past. She, (among many other things), manages much of our social lives, corresponding, coordinating, hosting and remembering to send birthday wishes. I am dependent on her for that, though at one point I was able to do so myself. At this point in our lives I might measure our interdependence somewhere around 0.2.

In contrast to that, I know some married couples that essentially continue to operate completely independently on many levels. They each maintain their own professions, finances, schedules, social relationships, etc. They might measure much closer 0.0.

At the other extreme are cultures that live in a community of high interdependence. The example that comes to mind for me is a commune where everyone has a task, but no one exchanges money – some farm, some clean, some cook, some entertain, etc. Individuals in those communities might have a very high level of interdependence, perhaps 0.5 or higher.

I can not think of a true example of anything near a 1.0, though I would be delightedly surprised to find one.

I would like to note that a close relative to interdependence is ‘codependence’, which is often used as a term to describe unhealthy relationships. From what I’ve read, the key difference between the healthy state of interdependence and the unhealthy state of codependence is that the individual retains the ability to be independent. It sounds like this is an issue of debate in the profession of physiology and I suspect biologists would weigh in as well.


The number of other people sustained by your input.

I would measure this on a scale of zero upwards, with the maximum being somewhere around the population of the earth, plus or minus.

The common example is having children. A naive approach to measuring dependents would be to assign each child one point and divide it across those that take care of them. That might be 0.5 to each of two parents, it might be a full point to a single parent, or there might be some smaller fraction taken on by grandparents, other family members, the state, etc.

My naive approach above assumes a binary which is in fact not true. There is such a thing as being a bad parent and similarly there is such a thing as being a mediocre parent or only partially caring for dependents. Acknowledging that, it wouldn’t affect the metric’s template, only an individual metric – so this is something I will defer to a later time to think more about.

Of note, we are talking about measuring maturity and the issue of children presents an interesting case. There is no maturity requirement involved in the act of creating children (despite that depictions of it are described as ‘mature’) and certainly for some, the way they ended up with a child is a sign of the opposite. Raising children always requires maturity though. For some the child is a forcing function, their maturity rapidly increases to meet the bar. For others their lack of maturity is evident and someone else must raise the child.

It is really important to me to stress that having children is not the only form of dependents and is in fact not be the best for everyone. The world has been blessed in many ways by those that have not had children and as such were able to invest more energy in other efforts.

For some this might come in the form of taking care of elderly parents or other family members. Another example that comes to mind for me is volunteers who tutor, mentor or help those not related to them. A few people in my circle right now are investing a lot of time helping a family of refugees transition to life in America. This is certainly a situation that creates a partial dependent.

Someone that always has energy to help those around them might in fact have a larger impact than those having children. Ra

The Metric

As I described above, I would display this as a simple three number measurement showing: independence interdependence and dependents. To be displayed in the following manner: 0.7 : 0.3 : 0.2

What this gives us is a quick glance to see development or arrested development.

My newborn for example would measure at: 0.0: 0.0 : 0.0

A young child would develop to something around: 0.3 : 0.0-0.2 : 0.0

At some point in adolescence we would expect: 0.8 : 0.0-.03 : 0.0

Until the child became an independent adult: 1.0 : 0.0-0.5 : 0.0

And ultimately when they began caring for others: 1.0 : 0.0-0.5 : 1.0-5.0


As I’ve stated, my intention is to create a tool to allow me to better think about child development. The above is my current prototype, something I intend to explore further. I will certainly need to refine the concept and to date the measurements are inexact, meaning a rubric is needed. Creating that will require a much broader exploration of the topic.

What I love about this project is that even if the metric is useless as a tool, the research I do to come up with it will require me to learn a lot more about child development, which will certainly benefit the initial goal.

Passing My Athletic Peak

In a few months I will turn 30 and while that number has no particular significance to me, I started to realize while watching the Olympics that, physically speaking, I am hitting my peak.

While competing at Rio earlier this month, Michel Phelps described himself as a ‘mature athlete’ and commentators made note of how much effort it took for him to climb out of the pool after one of his races, describing it as ‘gingerly’. He announced his retirement this year. After 16 years of racing at the Olympic level, he is ending his career. He is 31 years old.


30 tends to be when people stop being able to compete at their athletic peak. There is some variance per athlete, but the trend is pretty consistent.

Here are some data I grabbed from the Association of Road Racing Statisticians (my new favorite association) that shows the fastest marathon time recorded by a runner with a given age. The chart goes from the age of 5 (wow) to the age of 93 (WOW!). You can check out the actual times on their website, but I made a quick heat map to show the trend. The fastest time ever recorded was by someone that was 30 years old (text in red) and you can see a clean normal distribution around that.


There are certainly a few athletes that have performed excellently past the age of 30, some even as Olympians. Anthony Ervin, the 35 year old swimmer from the USA took two gold medals home from Rio and swam his fastest race ever. Bernard Lagat, a runner, at 41 years old runner won the 5k in the USA Olympic Trials, though his time was slightly slower than his personal best.

Even including those outliers, it is apparent that the human athletic peak, with the technology we have today, hits somewhere in the range of 30, plus or minus a few years. That means for me it is fast approaching.

The Optimism Of Youth

It wasn’t that long ago that I watched Michael Johnson run at the summer games in Atlanta – his gold shoes reflecting the camera flashes as he set world records for the 200m & 400m. He was my running hero, and I knew that if I worked hard enough I could be on that same stage some day. Everything was in the future and everything was possible.

Year after year I improved. My times got faster, I grew stronger, I learned more about the sport and dedicated myself more. Forward progress plays a funny trick where as long as you are improving, anything seems possible with the fullness of time. There is always a future that is faster than today. There is optimism as long as there is progress.

This eventually stops being true. At some point soon I will run the fastest race that I will ever run. Perhaps it was my marathon last month. It is a strange shift to realize a constant that has been true your entire life, athletic improvement, will no longer be the a rule. What comes after that?


There are two options that I see and that I am beginning to prepare myself for – changing the activity and changing the competition.

Changing the Activity

What I’ve been discussing so far are mainly pure athletic events – running & swimming.

While I focused on the age of 30, it is important to note that 30 isn’t the peak age for every race distance. Some shorter events have a younger peak age, the 5k is at 18 for example, the 10k at 22 and the half marathon at 28. This is why many runners increase their distance as they get older – they can’t run quite as fast, but they can deal with pain for longer.

Perhaps the 50 mile or 100 mile race still hold something for me after 30. By changing my event, I might find new life, similar to what I found when switching from the mile to the 5k or the 5k to the marathon.

Another option is changing sports altogether. While athleticism does peak at around the age of 30, it turns out that the decline isn’t immediate or dramatic. As we can see in the heat map above, it is very gradual. This means that if someone is improving in their knowledge of the activity, efficiency, dedication, etc. it is still possible to improve. Now for running, it is unlikely I’ll have a breakthrough of those sorts, I’ve simply done the sport for too long and honed many of the aspects. (But that doesn’t mean I’m not willing to try a few crazy experiments to hold on – more on that soon.)

What this means is that I can find improvement in activities I’ve never been good at. Basketball, rowing, cross country skiing, etc. By changing the sport I focus on, I’ll open myself up to all new possibilities of progress. Though my new peak might never be what it would have if I’d taken up that sport earlier, at least I’ll get to experience setting new personal bests again.

When thinking about changing activities, one point of note is that not all activities require the same degree of athleticism. If you were to break down activities into building blocks, you would find a wide set; skill, knowledge, strategy, reaction time, grace, etc. Not every activity requires that same ratio. This is great because not every one of those building blocks peaks at the same time.

Skill and knowledge are something that can continue to improve much longer. Therefore an activity that requires more skill and less athleticism, can sustain a higher peak age. Consider Peyton Manning, known for his strategy and knowledge, who played quarterback in the NFL until he was 39.

I was going to pull some data on peak ages at different activities, but as always, beat me to it. They look at median age for Olympic events and you can see a few stand out as sustaining older athletes: equestrian, shooting, beach volleyball & golf particularly.

Those activities require more skill and less pure athleticism than running or swimming, which means it is possible to enjoy a peak later in life.

That is the first option, changing the activity.

Changing the Competition

The second option is to change the benchmark you compare youself to.

Competition is truly relative. Many athletes compete only against themselves, trying to improve. Some compete at a local level, trying to improve their spot on a school or club team. A rare few compete at a national or global level.

I’ve found the key to competition is finding goals and competitors that are challenging enough to push you but realistic enough to periodically beat.

We’ve established that at some age, athleticism peaks and so it will no longer be possible to set personal records in events you’ve excelled at. It will also no longer be possibly to compare yourself to athletes at their peak. But there are other options.

Age group awards are one of the best ways to change the competition. What they do is level the field by comparing individuals to those similar to them. Comparing a 55 year old man to a 30 year old is unfair, but comparing him to other 50-55 year old men is much more reasonable. I recently spoke to a few runners in their late 60s who said that they move slow, but fast enough to get top spots for their age and they enjoy that.

As I cross my peak I’ll be able to look forward to being on the podium again. I’ll have the new challenge of trying to age more gracefully than my peers, but as knees wear down and injuries build up, if I can maintain my health, I might be able to do things that are impressive for my age.

In a similar vain, if you will recall the peak age chart above, you’ll remember that it resembles a normal distribution, a slow build before a peak and a slow decline. What that means is that on either side of the peak are points that are somewhat similar. For example the fastest time by a 35 year old is very similar to that of a 26 year old, even though those times are 10 years apart.

As you go further out, eventually you will hit a point where two similar peak performances are 27 years apart. That happens to be the age gap between my oldest son and I. That means at some point on my decline, he will be on his incline and pass me. While I don’t know if he’ll be a runner, (though his current love of it certainly suggests he might), if he becomes one, there will be a point where we are similar in speed.

Another way to change the competition might be to see how long I can go before my children pass me. That one seems particularly exciting, because though I will work hard to delay it, it will be a great moment of joy for me when they do eventually best me at whatever it is they chose to do.


Product Management and Collective Action Problems

Bringing a new product to life, either as a product manager or co-founder, ultimately amounts to solving a collective action problem.

That is a problem that often occurs when a group of people is trying to accomplish something that is in their collective best interest but that none can accomplish alone.

Encyclopedia Britannica has the following to say about this type of problem:

“However, it has long been recognized that individuals often fail to work together to achieve some group goal or common good. The origin of that problem is the fact that, while each individual in any given group may share common interests with every other member, each also has conflicting interests. If taking part in a collective action is costly, then people would sooner not have to take part.”

The result is a set of decisions by individuals to participate or not. If everyone acts then the result can ultimately happen. But if instead, each individual decides not to act, the result can not happen. Managing those individual decisions on a large scale is what determines success or failure.

Apply this to creating a business around a new software product. There are two distinct groups of individuals, builders and commercializers. The former must believe there is revenue potential in order to spend the time to create it and the latter must believe the product is useful in order to spend energy distributing it.

If either stops believing in the other, their actions will reflect it and their doubt will become a self fulfilling prophesy. If all of the individuals stop acting or even just put in a mediocre effort, the result will not be possible.

Conversely a product that sells well will attract the attention of builders who want to be a part of something successful. A product that is built well will garner the attention of distributors who will focus on it, thus increasing the revenue.

Managing the collective action is the difference between a death spiral and a pinwheel. The former in which things get worse every day, the latter in which success begets more success.

There are plenty of instances where an inferior product won because the collective action was better managed. There are plenty of cases where someone had the correct vision but couldn’t make it happen because they couldn’t bring together the right people to make it happen.

Managing collective action is the chief goal of a the person at the center of the new product – the person who is responsible for making sure it succeeds. They must paint the vision for the future, gain the trust of those around them and work to ensure each success begets more success.