My 10-year vision: Systematizing decision-making

High-level summary: My 10-year vision centers around creating a company or series of companies aimed at improving decision-making on 1) an individual level, and 2) an organizational task/process level.

I believe that when we actually set an intention and write things down, that significantly increases the chance that they will become reality. I’d like to write out my 10-year vision for the future, as it stands right now. I recognize that this is still quite broad, but I wanted to write it down nonetheless.

I. What I would like to focus on

One of the biggest challenges that I have in my own life is making decisions – deciding what decision to make, criteria by which to make the decision, and when to actually stop deciding and to consider the decision made and locked. As such, my 10-year vision focuses on improving decision-making, both in an organizational and in a personal context.

I envision doing this in two main ways:

1. Systematizing personal decision-making at an individual level

2. Systematizing decision-making and automating complex tasks at an organizational level

II. Improving personal decision-making at an individual level

I envision simplifying decision-making at a personal, individual level. Human beings are inundated with information and decisions everyday, and it can get tiring and overwhelming at times. I believe that if we didn’t feel like every single decision was so uncertain and unclear and novel, it would minimize a lot of the stress we face, because we would realize that we have done this many times before and have an approach for dealing with this sort of problem.

Thus, I would like to create tools that enable people to sort through the chaos of this information and recognize the similarities in the situations that they face, and therefore, the similarities in the decisions that they must make. I would like to provide and facilitate the self-creation of frameworks to help individuals analyze the pattern of their past decisions and approach new decisions in an informed and clear way – by understanding what they did before, why they made certain decisions, why it did or did not work, and what they can do now that they are faced with a slightly different, but still archetypically the same, sort of decision. That is, I would like to provide individuals with the tools and frameworks to make new decisions in a confident manner.

Of course, this goes hand-in-hand with increased personal awareness and understanding of our emotions. After all, how can we know what the “right” decision may be, if we don’t know what tends to drive our personal happiness or unhappiness? (if we are solving for happiness, that is)

In order to make good decisions, we need to be very aware of our own personal strengths, weaknesses, sensitivities, biases, and more. We can only understand our emotions through careful reflection of our reaction to certain situations and decisions. We need to be aware of who we actually are. Therefore, part of the process of facilitating personal decision-making also involves a heavy element of facilitating increased personal awareness.

III. Improving decision-making and automating complex tasks at an organizational level

As I have written previously in some of my posts, I believe that there is significant opportunity to systematize certain complex tasks and decisions, many of which are currently done by humans, but which could be simplified and automated by embedding sets of logic into the workflow.

I would like to start a company, or maybe series of companies, to drive innovation in decision-making and knowledge work systematization. I could see this taking place in several ways.

1. Systematizing/automating complex knowledge tasks: As I wrote in one of my previous posts (linked here), I believe that when we think of the bigger picture of complex tasks (e.g., writing memos, making certain types of presentations, making financial models, eventually other even more complex tasks), there is opportunity to take a bigger-picture lens and identify the “archetypes” of certain types of the task (e.g., type of memo, type of presentation, type of model, etc, all further codified based on context and situation), identify the common elements across them, and create a system or process that creates an ~80% version, based on the archetype, customized as needed. I envision creating something in this space, likely for complex knowledge work-based organizations, such as consulting, investment banking, private equity, and other such firms. The starting step for this would be to pick a specific task and create a very robust logic-based system creation for this particular task. If this worked, others would follow.

2. Systematizing work-related decisions through prediction and recommendation engines: As part of this, I also envision systematizing decision-making and prediction in some of these areas. I believe that this includes

1. Stipulating what sort of data will be necessary to consider when making a certain type of decision (e.g., if making an investment decision, identifying what will be most important to consider in making the decision)

2. Gathering data on these elements in previous such situations (e.g., previous similar investment decisions of this “archetype”)

3. Gathering a record of the relative success/failure of these past decisions.

This would help to build a predictive engine for this type of decision, based on analyzing the factors and variables that led to success or failure in past such situations, with the output being a recommended decision and prediction of outcome/level of success (as per defined “success” criteria) based on the decision taken. From there, it would be a matter of, every time this type of decision came up again, gathering these data variables, incorporating them into the model, and reviewing the recommendation that would be provided (while, of course, applying human decision-making and judgement in parallel). As more and more decisions are run through this decision-making engine and the feedback is looped back in (positive, negative, etc, and why), the engine itself would be continuously refined and improved. Of course, there would sometimes be situations of mismatch between human/system recommended decision or prediction of success, and we may realize that there are further variables that would need to be built into the system for better decision-making. As we continuously built in new logic, variables, and information, the questions to be asked and refined include:

-How important is this information?

-What specific factor would it impact?

-With what magnitude would it change the decision?

-In what direction would it impact the decision?

-Would it change the decision or not?

Of course, I know that variants of this are already being done across a variety of different fields. Nonetheless, it is still not systematically applied in a majority of work situations, and I could envision that tools such as this begin to be embedded in a much wider array of situations, down to more daily tasks (e.g., writing certain sales emails, determining strategic priorities based on market sizing/growth rates, etc). This definitely needs to be made more specific in order to be successful (i.e., down to the very specific decision level). I would begin by focusing on something more concrete, and once again with this, I would start with something that I am more familiar with (e.g., consulting/banking/private equity contexts), and expand from there.

IV. Post-10 year vision: Creativity using data

Later on (not necessarily within the next 10 years, but still part of a longer-term vision), I also envision expanding my decision-making facilitation to more creative endeavors. As I have mentioned in a previous post, I would like to enable the development of novel creations based on something like comprehensively tagged databases of “building blocks,” (e.g., such as in dance, figure skating, art, cinema, music, etc) which could then be used to develop something new through unique combinations of these building blocks, aimed at optimizing for what the creator chooses to optimize (e.g., most likely to succeed with certain type of audience, or optimize around a certain style, etc) and along certain parameters (e.g., certain length, budget, etc), with the predictions of success being based on the success of past combinations (contingent upon a large enough database having been created).

This would be a decision-making framework applied in a unique way to more creative fields. Even though on the surface it seems very different than solving for things such as highest-success investment decisions with predicted success based on financial metrics, this would, in some ways, be the parallel to that for creative endeavors (except that it would be decision-making for creation, rather than just for the purchase/sale of existing assets). For example, these proposed creations could optimize for things such as highest expected ticket sales, highest expected audience attendance, etc, which would be similar to the “highest ROI” sort of decision-making done in financial settings.

V. My own path and role in all of this

I’m at the very beginning stages of doing all of this, but the above is a high-level version of what I would like to work toward in the coming 10-15 years. Of course, I recognize that I will need to get much more specific with my vision each of these areas in order to pursue it, and I would do this by picking very specific, discrete problems to solve and beginning there.

I also wanted to think through how I could go about doing this in the next 10-15 years. I would start by creating a company in one of these areas, focused on solving something relatively specific (i.e., a thin slice of a much larger problem). I imagine that this may start more on the individual decision-making side, as that is the more easily accessible challenge to solve, given that I don’t have technical skills in the area. I imagine that my first company would be a challenge, but I’m also sure that it will provide a variety of lessons.

Over time, I would also like to start several other companies, all related to certain areas of decision-making. Through multiple iterations, I would like to learn the skill of creating something from nothing and building it up to success. I imagine that I’ll fail many times in the process of this, and I accept that as part of the learning journey. The failures will be inevitable, but the important point will be to simply get up and continue toward the longer-term goal and vision.

Ultimately, I envision creating some sort of growth ventures fund, in which my team and I start, incubate, and grow  companies in these spaces (task-based decision making/automation and personal decision-making). I could envision it being organized a bit like the below:

Decision Fund [growth ventures fund]

Branch 1: Personal/life decision making

Branch 2: Task/process/automation decision-making

Some of what I would like to build into the culture of my company/companies includes (as a first hypothesis, as I’m sure this may adapt as I get actual experience):

  1. Being ruthlessly results-oriented
  2. Building a learning organization (always learning and iterating)
  3. Building a meritocratic organization in which the best people can thrive, grow, and continue gaining opportunities

In the meantime, a couple of skills that I also want to learn include: data science (at a high level) and investing (in-depth – I think this will come partly through the experience of starting/running companies, and partly through the trial and error of actual investing, both before and during my envisioned growth ventures fund).

Now that I have put it out into the world, I hope that it’ll help me get there by keeping this clear vision in my mind. 

Creating order out of chaos: Archetypes and systematization

How can we create order out of the chaos that is our disorganized world? Recently, I’ve been thinking about two concepts that can help us to do this, related to organizing ideas, systems, and businesses: archetyping and systematizing.

I. Identifiying Archetypes

A couple of years ago, I read Ray Dalio’s book, Principles, which detailed his principles around life and work, and among many topics, one stood out to me in particular: his focus on finding patterns, or archetypes, in the world around him. He explained that he applies this principle across much of his work and life, including hiring, investing, and making predictions. For example, Dalio applies personality testing in his hiring process at Bridgewater in order to determine what potential hires’ natural strengths and weaknesses are, and what sorts of roles people are best-suited for. As another example, he studied the history of the rise and fall of empires to determine what the high-level patterns are that take place before, during, and after an empire’s rise and fall, thus being able to apply forward predictions for our world today.

In his belief, most things in life can be categorized into archetypes – people, problems, situations, and more. The concept is that even though problems/people/situations in our lives may seem unique to us, once we have enough experience or information over time, we can see that certain sorts of these problems are actually repeated multiple times, many people fall into certain archetypes of personality, and patterns of events and situations repeat over time (ex: debt crises, rises and falls of empires, etc).

Once we realize that these patterns exist, it opens the door to actually start looking for these patterns in our own personal work, interactions, and experiences. This concept was quite interesting to me, and since then, I’ve been looking at things from that perspective as well. Around me, I see various experiences, but I constantly ask myself – what is the big picture behind this? What is the bigger pattern underlying this? How can it be systematized?

We can take the chaos that is the constant influx of ideas, situations, conversations, work, events, and more, identify a pattern, and then create a narrative and understanding of it.

For example, I’ve recently been looking at my own work and trying to identify areas that may seem different and varied, but actually have a variety of similarities. What came to mind was due diligence work. Private equity firms often do a large number of diligence efforts as they analyze a variety of acquisition targets, and they often hire consulting firms to run them. Although each target and diligence effort may have differences, when we zoom out and look at the bigger picture, there are actually a variety of similarities. For example, they often require building a market model, doing a customer survey, running ex-employee/ex-competitor interviews, identifying trends/growth areas, and more. When we think about these elements, there are many opportunities to standardize and maybe systematize. I’ll continue with this analogy in the next section.


II. Systematizing

Building upon a concept in Michael Gerber’s E-Myth Revisited, it is important to build in standardized sets of practices and systems for conducting certain processes. Once an order or pattern has been identified, I believe that this is where there is a lot of opportunity to address it by creating systematized solutions for the situation at hand. For example, let’s say that we have identified a set of archetypes for a particular problem, situation, or type of person that we may interact with. Once we have the archetypes laid out, we can determine how to go about appropriately addressing each archetype based on the bigger picture and unique circumstances/requirements of each, and can create a more standardized solution approach.

Let’s return to the due diligence example. As we said, there are often a variety of types of analyses that need to be run in due diligence settings, regardless of the type or topic. Let’s go deeper into one of them – conducting interviews. There are often a variety of types of interviews that need to be run, for a variety of topics. However, maybe if we think further into the types of interviews that we need to run (e.g., ex-employee, ex-competitor), the particular topic (e.g., understanding competitive landscape, understanding key buying factors, understanding trends, etc), we can think of the types of questions that may need be asked for each, and how they would differ (by leveraging past successful examples of each type). We could then construct a base set of questions that would be asked based on the particular type of interviewee, topic, and add further specificity as needed.

Now, we could argue that this wouldn’t be useful because we would need to adjust the questions that we are asking in real-time as per the interviewee’s response. However, maybe we could actually build that in. Let’s say that we anticipate that a particular question would have response type A, B, or C – we could then actually create a set of follow-up questions based on the response that the interviewee provides, dig deeper into that area with several questions as long as needed (maybe as long as we have specified as per the parameters), and then go back up several levels to the overall set of questions.

Ideally, we could create this base skeleton of questions to be asked as per several parameters set at the beginning (i.e., length of interview, type of interviewee, type of topic, level of detail desired which could govern the depth we enter for follow-up questions, and more), with certain data plugged in to customize to the situation (e.g., name of competitors trying to assess, key buying factors we are assessing between, etc).

In this way, we could actually create a customizable skeleton of questions for conducting interviews across a variety of situations. Of course, all this isn’t to say that we can create a perfect guide 100% of the time. However, what we can do is at least minimize level of effort expended to create new solutions every time, and rather, get the team ~70-80% there with little effort by creating a base case version customized to the situation, which can then be further adjusted.

This is a very particular example, but the concept is applicable in a very wide variety of ways. For the diligence example, we can create 70-80% skeleton versions for the other areas as well, including for building a market model, building a survey, and finding growth opportunities. Outside of the diligence example, we can think more broadly within consulting about the archetypes of projects that come up, and the standard elements that may be included within each.

Thinking more broadly, we can also find countless examples in other domains, from writing an essay, to putting together a brief, to designing a building as an architect, to doing a company valuation, and more. In every single situation and domain, there are currently many complex tasks that require a great deal of mental energy because people often start from scratch for the creation process, when in reality, there are countless past similar creations to leverage, and complex thought from scratch may not be necessary. If we could create 80% versions as a first step with very little effort and then only some minor adjustment required thereafter, we could take out the requirement for heavy thinking in these areas, and instead focus our and our employees’ mental energy on more complex tasks.

III. What this means

I think that as we progress as a society and continue in our desire to grow and enter into new areas, thinking about our work and experiences from the perspective of archetypes and systematization can be immensely powerful in simplifying much of our current mental load.

I’m going to continue thinking through this in my work, experiences, and daily life, and I encourage anybody reading this to do so as well, because there is an immense amount of potential within this.

Thoughts on creating a database of fundamental building blocks

I believe that many of the most unique ideas come at the cross-section of disciplines, often from those who have some level of depth across several areas. In my case, I recently had an idea at the intersection of movement-related activities, organization, and business/technology that I found quite interesting. I haven’t thought through this in great detail, but wanted to share my initial thoughts.

The idea was sparked a few months ago, when I was at a lyra (aerial hoop) private lesson, and I was working on flow, the smooth transition from one move to another. My instructor decided to try an exercise with me – she asked me to list all of the moves that I knew (which weren’t many, since I had only recently started taking lessons), wrote them down on a piece of paper, ripped the paper into tiny pieces with each move written on one, and placed them inside a bag. She then drew them out, one by one, and that was the order in which I was to do my newly-created sequence. The exercise brought me back to an concept that I had been thinking of for some time: building block categorization.

I. Fundamental building blocks

I believe that there is significant opportunity for further categorization of a variety of topics into the fundamental building blocks of what they are. When I was thinking through aerial silks combinations (another activity that I practice), I thought of the fact that although there are many options and variations, nothing really exists to break down the overall possibility of all moves that exist. I thought that there could be an opportunity to create a database of every single move, thus breaking down the art into its core building blocks, going down to the to the foundation of all combinations and sequences.

However, I think that this could be possible for many other areas, not just aerial, even though that is the first idea that came to mind because it is more physical and less widely-practiced, so there does not exist a widely-published body of knowledge on its fundamentals. Nonetheless, I could envision this being useful for all movement-related activities (i.e., ballet, contemporary dance, gym exercises, yoga, acroyoga, acrobatics, barre, figure skating, sailing, skiing, snowboarding, and more). Everything can be broken down into its component pieces.

Beyond this, I could also see this being useful for other disciplines, which may already be broken down – like principles of economics, biology, chemistry, psychology, languages, games (e.g., chess moves, poker plays), and more – but could at least be incorporated into this database of building blocks. Of course, for some of these, it would not be as simple as saying “this is a russian climb,” “this a footlock,” “this is a hipkey,” as it would be in aerial silks, but rather, it would likely be broken down into categories – for biology, it would be broken down into cell organelles, cells, physiology, ecology, etc, and within that, there would be sub-categories (i.e., cell processes, cell structures, etc), and it would go through the basic foundations of everything (or, at least, the goal would be “everything” – it would still have to be built up slowly). It could also be used in art and design, such as for architecture, fashion design, interior design, and more (e.g., in architecture, types of door designs, types of window designs, types of roofs, etc).

Of course, we could argue that for some of these disciplines, things like this already exist – Wikipedia, encyclopedias, textbooks, websites, etc. This may be true, but is there something in existence that has it all aggregated, broken down into categories, sub-categories, and pure fundamental building blocks? I’m sure there is some variation of this, but not fully consolidated like this. There are “databases” (consolidations of information) for certain disciplines, but not interlinked for all disciplines. And for arts and movement-related activities, which is where I first began with this train of thought, there exist many lists and sequences and performances and videos, but I especially don’t think that for all of these, there truly exists a database of core, fundamental building blocks.

II. Where this could be useful

Now, why would this be useful? I could envision several reasons why. To simplify, let’s go back to the core idea I had, a database of the fundamentals of aerial silks, lyra, and other movement-related activities.

  • Creating a “menu” of building block options: I think that, as the simplest step, this could help creators, choreographers, and anybody else wanting to create a series of movements, go to the database and just be reminded of all of the “building blocks” that exist. They could search by type (e.g., for silks, they could search “climbs,” “drops,” “inversions,” etc), and they could see the full possibility of all of the fundamentals (of course, this idea is contingent upon the database being as comprehensive as possible). This would not only spark ideas, because there may be building blocks that they simply hadn’t known about before, but beyond this, this would enable them to use this list of building blocks to develop new creations in ways that have not been done before.
  • Recommendations based on past success: If we take this further, imagine if there was an AI-based system underneath all of this that could actually analyze all that was in this database, as well as combinations that had been historically created from the database, and even past combination that already existed in the world (i.e., analyzing existing videos, films, and performances, breaking them down into their fundamentals, and storing the data as a combination), and provide recommendations. That is, the system could actually provide recommendations based on what has worked well together, what has been done many times before, and what has not – so that if someone were trying to create something, the system could recommend that “after move A, xx% of combinations have followed it with move B, and yy% of combinations have followed it with move C.” This could provide valuable data and recommendations on what to create, and people could also use it to get ideas on what may work well together.
  • Predictions of future success: I could envision that we now also overlay an additional layer of data onto this, such as past views, likes, or earnings – some measure of popularity or success. I could envision this then being used to actually determine and predict what may be popular based on what has been successful in the past. For example, the system could determine that certain combinations of moves, maybe at particular points in the overall performance (e.g., end, middle, beginning), and of certain lengths, are highly correlated with high number of views, likes, or earnings (earnings in the case of actual performances/films that sold per ticket or per view). This could then provide valuable information for choreographers to create new works that may have a high chance of popularity.
  • Specific optimizations: Alternatively, as more data is added and overlaid into the system, the creator would have the option to become even more specific in terms of what he or she is optimizing for (e.g., most popular combinations for certain age groups or countries, based on past views/likes/earnings data), or maybe optimize for something else, such as focusing on a certain type of move (e.g., a sequence optimized around most number of jumps, or certain types of turns, in the case of ballet).

III. Additional considerations

Of course, I could see some potential downsides to this as well – maybe, paradoxically, it could lead to a lack of creativity because the system is now recommending simply what has worked well in the past, rather than encouraging people to think for themselves and come up with their own creations. Nonetheless, even at its very core, I could still envision this being useful, simply as a database of fundamental building blocks of a variety of disciplines. 

Overall, I believe that there is significant opportunity to further organizing the world around us. This is simply one example and train of thought, but I think that there are many things that can be further broken down into their fundamentals or core ideas, which could then be used as data to analyze and reach conclusions or make predictions. I’ll explore this further in some of my future posts.