Obliquity – Why some problems cannot be solved directly

On March 30, 2017 a large portion of the Interstate 85 (I85) highway in Atlanta, GA collapsed after a massive fire that raged underneath it.

Being a key piece of infrastructure that carries thousands of cars every day, experts predicted severe traffic congestion and delays. Yet, none of this materialized. People simply changes their behavior; in fact Atlanta’s public transportation (MARTA) reported a 25% spike in ridership following the incident.

On the other hand, adding a lane to an existing highway usually makes congestion worse. This is known as Braess’s Paradox. Traffic congestion is one of those complex problems that simply cannot be solved with a direct solution of building more roads.

Have there been times when you tried to tackle a problem head on and failed? Some problems are best tackled indirectly. Why?

In order to understand why this happens we have to first understand a few things about complex systems. As explained in my previous article, there are three types of systems categorized by the level of constraint on both the system and the agents operating in it.

While ordered systems are transparent (simple systems are transparent to everyone and complicated systems are transparent to experts) complex systems seem transparent but are in fact opaque. We simply cannot know everything that happens in these systems. We think we know, but we usually have a very limited understanding of the complexity inherent in these domains.

John Kay calls this phenomenon Obliquity and explains it in detail in his book by the same title. He writes:

The environment—social, commercial, natural—in which we operate changes over time and as we interact with it. Our knowledge of that complex environment is necessarily piecemeal and imperfect.

The human mind is programmed to look for patterns and to seek causes, and this approach is often valuable. But that programming leads us to see patterns in random events and to attribute intentions where none existed. We believe we observe directness in obliquity

Because of this, direct solutions almost never work as intended and usually have unforeseen consequences or adverse effects, like the increase in congestion when more roads are open. 

A good example of this is the so called cobra effect which is based on an anecdote about a bounty program created in British colonial India where the government tried to fix the problem of venomous cobras by offering a bounty for every dead cobra. 

This worked initially but then people started breeding cobras for income. When the government found out, the scrapped the program causing the breeders to release their worthless cobras making the problem worse.

It is because of this that I believe the first step in tackling any problem is to get a sense for the type of environment we’re dealing with. 

If the environment or domain is simple, the solution should be self evident. We simply sense what’s happening, we categorize, prioritize and solve the problem. 

If the domain or system is complicated, like a car’s engine or a software system. we hire experts to analyze the issue, get a sense for what the problem is and solve it.

 If we’re dealing with a complex domain or environment, we cannot solve the problem by analyzing. We have to adopt a more experimental, discovery based approach. We have to try things and see how they work; we have to probe, sense and then respond accordingly.

You assess the situation quickly, form a hypothesis, design and carry out a small-scale, safe-to fail experiment and analyze the results, Then you reassess your hypothesis and figure out if you’ve solved the problem. Other times you can leverage what’s already there, what you sense and see that’s already working.

Why plans are useless but planning indispensable

“Plans are worthless, but planning is everything”
-Dwight D. Eisenhower

“Failure to plan is planning to fail”
-Benjamin Franklin

We all have the fantasy of the perfect plan that goes without a hitch. Heist movies, like Ocean’s Eleven (Twelve and Thirteen), The Italian Job, The Bank Job, etc. all fuel that fantasy that you can be a mastermind capable of seeing all the angles, predicting everyone’s behavior several moves ahead, getting the timing right down to the second and achieving your goal exactly as you planned. In the real world however this is rarely the case. Why?

We live in a complex, interconnected world. Every action we take can cause ripples of unpredictability in the system. Complex systems are by their very nature unpredictable because there are no universal laws that govern them. Even if every agent in the system were to have simple rules by which they make decisions, the overall system behavior that emerges is unpredictable.

To account for all the possible scenarios quickly exceeds the capacity of even the most powerful of today’s computers. Just look at the weather patterns. Despite all the advances in computational power and simulation capabilities, we still can only forecast the weather with any level of accuracy a few days in advance. The complex behavior of the water molecules, the air temperature, atmospheric pressure, initial conditions and other factors make it nearly impossible to analyze and predict what will happen.

There are however systems which are highly predictable even if they seem very complex. A computer program’s behavior for example is very predictable (most of the time anyway) A car’s various systems: the engine, transmission, brakes, electrical systems, etc. are also very predictable even if they are interconnected and interdependent.

So what’s the difference?

David Snowden’s Cynefin framework (pronounced kun-ev-in) recognizes three types of systems: Ordered, Complex and Chaotic. The difference between them is the level of constraint in each system.

Ordered systems are highly constrained and as such their behavior is very deterministic and predictable. You can easily determine cause and effect and the patterns you find are very likely to repeat in the future. Ordered systems are further divided into Simple and Complicated. A highly structured business process for example (like getting a loan) is a Simple system. It’s highly constrained and relatively easy to fix or optimize. Cause and effect relationships are clearly visible and you can predict with very high accuracy what will happen.

A car is an example of a Complicated system. It’s still Ordered because it’s highly constrained (there’s little to no variation beyond what’s been specified by the system designer) but the level of detail in the design makes it much harder to understand and notice cause and effect relationships. This is why you need highly trained professionals (experts) to analyze the system and figure out cause and effect relationships.

Complex systems on the other hand are only partially constrained. Complexity science is still actively being studied and discovered but we do know a few things that can help us understand how these systems work. Complex systems are made up of agents that interact with each other and with the system based on their own rules and strategies and the constraints imposed by the system.

In the example above we saw that cars were Ordered systems because of the high level of constraint in every aspect of their design; traffic on the other hand is only partially constrained and as such it’s a Complex system. There are rules in the form of laws and guidelines such as speed limits, traffic signs, traffic lights, highways, ramps, paved roads, direction of driving, etc. but these rules do not fully constrain driving. You can choose to dive fast or slow, change lanes frequently or not at all, slow down or speed up, turn left or right, etc.

This creates unpredictable emergent patterns such as accidents, traffic jams, traffic congestion or sparsity, etc. On top of that, the traffic patterns from moment to moment, from day to day are completely novel and unique. There’s no way to know for sure when an accident will occur or when the traffic will become congested. Even though you may know exactly why an accident happened, it doesn’t help you fully predict future accidents.

Chaotic systems are highly unconstrained. Imagine for a second that one day none of the rules of driving applied. You could drive in the middle of the road if you wanted, drive backwards, go through red lights and stop signs, drive on the opposite side of the road, cut through lanes at will, make sudden u-turns, break and accelerate as you wished, etc. What would happen? Complete and utter chaos. It would be impossible to predict anything.

Side Note: Temporarily removing constrains in a system is an excellent way to unclog bureaucratic gridlock in an organization and spur innovation. Dave Snowden calls this “shallow dive into chaos” but that’s a topic for another day.

So how does this relate to planning?

Most planning is done under the assumption of Ordered systems. We assume that the future is predictable from past events so making plans is easy. Planning comes naturally to us as our brains function like cybernetic (goal seeking) systems. We set a goal and immediately our brain provides ways to achieve it.

Now if the system you’re dealing with is highly constrained, these plans are very likely to succeed. For example if you wanted to buy a house you’d need a bank loan and since getting a loan is an Ordered system, given certain criteria, you can predict with very high accuracy if you will succeed or fail.

If we’re dealing with a complex system however, or a chaotic system, we would be unable to account for all the possible future scenarios and contingencies and our plans would be at best incomplete. Before the advent of GPS and turn-by-turn navigation systems with up the the minute traffic data, it was impossible to plan a route down to the minute and be very confident you would arrive at a particular time.

So the reason why plans are useless is that more often than not they are incomplete and don’t account for all the possible contingencies in the complexity of today’s systems.

Why then is planning indispensable?

The process of planning gets us to think through many of the possible futures and scenarios that can unfold and help us be better prepared if any of those futures scenarios were to happen by creating contingencies. Of course we can’t cover every single scenario and we need to be agile and capable of course correction. The measure of true agility is the ability to ditch your plans halfway through when the situation has changed and made your plans obsolete even if the sunk cost might be high.

Always have multiple theories for explaining and understanding things

When trying to understand or explain something that’s happening, like a certain behavior pattern in your friends or significant other or a trend in fashion, technology, etc, it helps to have more than one hypothesis (theory), (even better if it’s more than two) and assign each one a probability of being right.

Then as you get more evidence for any one of your multiple theories, you adjust the probabilities of what the correct explanation could be. You might also run multiple experiments to cover all your theories. This will lead you to a more accurate understanding of people or the world around you which then leads to more accurate forecasts, better decisions, more confidence and decreased levels of stress.

I believe that there’s always more than one way to explain things, there’s always more than one theory that fits a situation and I’m not attached to any one of them at first. This doesn’t mean that I like being wrong, in fact this means that I want to be even more accurate so I want to cover all my bases. As I gather more data, I eventually converge on a single theory, while still keeping an open mind that it could still change in the future.

As humans we’re addicted to being right, it’s a compulsion that threatens to derail our friendships and our relationships. We want our intuition to be the correct one. It’s very easy to get emotionally attached to certain explanations that benefit us, make us feel smarter, more confident and more proud, or that ensure that we keep our jobs.

When you have multiple competing theories for why something is happening you keep yourself open to possibility, and as a result you understand the world better. You might not look as smart or as confident or as self assured as the person with a single theory, but more often than not, you will end up having more accurate predictions and be more confident than them in the end.

Patterns of Strategic Thinking – The Secrets of Exploiting Leverage


I’ve recently been obsessed with strategy and have been reading a variety of strategy books in a variety of fields such as psychology, economics, business, military, etc.  I noticed that while few people really understand strategy (even though they think they do) there were certain patterns of strategic thinking that show up over and over again in these works. These patterns can easily be abstracted out of their respective fields and used in their everyday life.

Game theory is one of the fields that studies some of these patterns from the perspective of games where you and an opponent take turns making moves. According to Wikipedia game theory is: “the study of mathematical models of conflict and cooperation between intelligent rational decision-makers.”

Your objective in these games is to be able to predict what moves your opponent will make for every one of your moves and choose the most optimal one for you to win the game (however winning is defined)

Personally I’m not a big fan of game theory for two core reasons. First it limits your thinking to a frame of move-countermove when in real life things are a lot more dynamic and complex. In fact, in many cases you can build quite an advantage without worrying about what your opponents or competitors are doing. Second it utilizes a model of the “intelligent rational decision makers” which according to many studies in behavioral economics is incorrect.

I first started to notice these patterns while I was studying psychology and influence, however I saw them as specific techniques within those fields. It wasn’t until I started reading books on strategy that I was able to generalize them and abstract them out of those fields and I started to see them everywhere. The techniques were different of course but the patterns were eerily similar

For example you can leverage certain skills you have to get a higher position in one company than you’d be able to get in another company. In another setting, say in business, you might be able to leverage big cash reserves to invest in R&D to move your company beyond the current trends in technology and be able to actually shape the future rather than be shaped by the future.

In both cases you’re leveraging/exploiting certain assets, that are only available to you, to put yourself in a better position to succeed. What else can your leverage that puts you in a position of advantage against your competition? More on that in a bit.

This is the first in a series of posts on the patterns of strategic thinking. My goal with this is to create a collection of these patterns that can be used as a toolkit for making smarter decisions both in business and in personal life and who doesn’t want to make smarter decisions?

In this post we will explore the vast and unending ways you can exploit and make use of leverage.

Using Leverage

“Give me a lever long enough and a fulcrum on which to place it, and I shall move the world.” – Archimedes

Leverage is simply a way to multiply the force used to a greater effect or to achieve a specific objective. It’s a type of advantage that is context free and not rooted in any particular field.

You can get or use leverage in one of two ways:

  1. by exploiting certain patterns that exist in a system either innate to it or by design
  2. by creating and accumulating assets which can be used at a later time

Let’s explore these two in depth.

There are three categories of patterns you can notice and exploit in systems:

  1. Predictive Patterns
  2. Pivotal Points
  3. Focused Effort

Part 1 – Exploiting Patterns

1. Predictive Patterns are patterns that allow you to predict what might happen in the future through the use of trends in the industry, momentum, routines, habits, biases, social dynamics in a given context, psychological models of behavior, inertias, etc.

In game theory a lot of your leverage and advantage comes from your ability to predict other people’s responses to your moves and figure out the countermoves to that anticipated behavior so you can win the game in the end. The farther you’re able to predict, the more likely you are to win the game.

As I mentioned above, one of the issues I have with it is that it assumes that you’re dealing with intelligent and fully rational human beings. However, as Daniel Kahneman and Amos Tversky (and later Dan Ariely in Predictably Irrational, Richard Thaler and Cass Sunnstein in Nudge and many others) have repeatedly pointed out, humans deviate from the so-called “rational behavior” but do so in relatively predictable ways.

So you can either use the “rational model” of behavior, or you can use the biases model that behavioral economics has put forth. In fact a lot of the techniques that are discussed in books about persuasion and influence focus specifically in telling you the various patterns of behavior that humans tend to follow which can be used for leverage.

Here are a few examples.

-In investing/business, if you notice a trend towards cloud computing and anticipate growth, you can invest in a company that owns and operates a lot of data centers.

-In your career, if you notice that everyone is talking about data science and big data and anticipate a big demand for people who know data analysis, you can start to learn statistics, if you already know programming or programming if you already know math/statistics.

-In your personal or social life, if you notice that when you call yourself a statistician people stop wanting to talk to you, next time you can call yourself a data scientist and get them more interested.

2. Pivotal Points are things like imbalances, inefficiencies, weaknesses, and so on that magnify the effects of effort. They are either innate to the system or are put there “by design” and once noticed can be used over and over again until the system is either corrected or corrects itself.

I put “by design” in quotes to highlight the fact that in many cases the weakness that are exploited in certain systems, (for example networks or websites that are hacked) are usually not there on purpose but through design they were introduced in the system as bugs probably through oversight or just faulty construction.

Imbalances exists when a small shift in the system results in relatively large effects. This can be for example pent-up demand for an item that nobody thought would be there. In war/conflict an imbalance would be a perceptual difference between say the number of soldiers that the enemy says they have and their actual numbers.

Inefficiencies are usually extra steps that one has to take to accomplish something in the system and are the most easily noticed form of leverage. Google for example noticed that the big search engines operating in the late 90’s all had the same inefficiency. They would provide irrelevant search results and as an advertiser you might be able to buy yourself into the top of the results list and stay there as long as you were paying.

Google exploited this inefficiency by introducing their PageRank algorithm and later their bid-style PPC ad buying platform. This not only had the effect of millions of users switching over to Google as their default search ending but also leveling the field for everyone so the little guy could compete with the big advertisers on an even footing.

Notice that this was both an imbalance (search engine users wanted to see relevant results so there was pent-up demand) and an inefficiency (users had to scroll through many irrelevant search results to get to what they were looking for sometimes never finding it)

Weaknesses are areas of lack of competency by an opponent/competitor that can be exploited and used by someone who has that competency. Of course the actual competency needs to be in demand in order for it to be worth exploiting. Again this is another common way that leverage is used in business or even personal life.

A good example of this is choosing a career. We’re all good at some things but not others, so for example if you find yourself in an organization that has really poor processes that are hindering growth and you are good at project management, this is a weakness you might be able to exploit long enough to either become an expert in project management or get promoted within the organization.

The examples above should be plenty to stir your imagination so let’s move on to the third pattern.

3. Focused Effort is a pattern where you limit your application of effort into a concentrated area of the system and you get larger payoffs from it. This pattern relies on constraints and threshold effects within the system.

A threshold effect is like a tipping point. There’s some point in the system that you need to reach before you see any payoff. This is something that happens for example when you launch a new product. It can take a lot of effort to get to the threshold/tipping point of awareness about that product but once you’re there things start to become easier and you just need enough effort to maintain the effect.

The threshold effect can be understood through the concept of inertia from mechanics where it takes a lot of initial effort to get an object moving, but once it has momentum, you just need enough force to counteract friction.

Another application of constraints and threshold effects is when you go after a small market and seek to dominate it before trying to take on a bigger market. From a strategic point it is a lot easier to dominate a smaller market fully than to claim an equal slice from a bigger market.

A perfect example of the threshold and focused effort patterns is the strategy that Tesla Motors has used to take on the giants of the automotive industry. In a recent article in FastCompany.com, Tesla Motors founder Elon Musk stated that his plan for introducing the electric car was really simple:

1. Build sports car
2. Use that money to build an affordable car
3. Use that money to build an even more affordable car
4. While doing above, also provide zero-emission electric-power generation options

One of the investors in Tesla explained in an answer on Quora why they chose to first build the very expensive Roadster (the sports car) then the Model S (the affordable car) and the plans for what they’re calling the Bluestar (the more affordable version). The reason for this is that you can’t penetrate the automobile market from the bottom up, it has to be top-down.

The Roadster provided Tesla with many benefits they wouldn’t otherwise have if they started with an affordable car. They got money from sales to be able to sustain themselves, they created a brand image, they showed the world they could build a high-performance electric vehicle, and they learned a lot from the engineering challenges, lessons they can now apply towards making more affordable electric cars for everyone.

Part 2 – Building Assets

Now that we covered the patterns you can exploit in a system to gain leverage, let’s cover the other side of the coin which covers the assets, competencies and advantages that allow you to exploit those patterns.

There are three types of assets you may innately have or can build:

  1. Positions
  2. Resources
  3. Competencies.

1. Positions are a type of asset that has to do with either a physical location in space or a more abstract perceptual position in the mind. The first one is obvious. In real estate for example you know that the key is location, location, location. Where you are located with respect to people’s movement patterns can make you or break you. In war/conflict certain positions are more advantageous than others and thus become mission critical to get and to hold. Good examples are bridges, hills, trenches, etc.

The second one is more abstract in that it represents a position in your mind (or as Al Ries and Jack Trout in their seminal work Positioning – The battle for your mind call it cherchez le creneau). The central idea is that a product, a service or a company should occupy a very well-defined and simple concept in the consumer’s mind. For example when you’re thinking about a refreshing drink, Coca Cola wants you to think of Coke.

One of the key insights in the book is that you should not try to compete with a position that’s already been taken by a competitor but rather try and create a new position and place yourself, your company or your product there as the sole owner. You do this by inventing a category and becoming the only provider of products/services in that category.

Tim Ferriss (of the 4-Hour Work Week fame) didn’t want another book on “career advice” so he created a new category called “lifestyle design” and put his book as the first one there.

This doesn’t just work for brands and companies, it’s the same for people too. In a company for example you might be the “go-to guy” whom everyone calls in a crisis, or you may be the “recluse but brilliant scientist” whom nobody has met but everyone knows about. This position can make or break a career and should be chosen very carefully otherwise people will just slap some disadvantageous label onl you that will hinder your career.

There’s a lot that can be written when it comes to perceptual positions. I may do a full post on this in the future. Suffice it to say that how you position yourself will greatly affect your success in life.

2. Resources are a type of asset that represents concepts like money, connections, physical things like real estate, factories, farms, machinery, weapons, personal things like looks, height, weight, age, etc. They can be created, acquired or innate.

This is the most common type of leverage you have or can build because it’s really obvious when used. If you’re astute you will notice that resources can be used directly on one of the three patterns mentioned above (anticipation, pivotal points and focused effort) If you’re not using some kind of advantage to get ahead in life or in your career, you’re really being left behind and missing out. All those successful people you see have some kind of secret advantage they’re using, connections, physical features (height, weight, looks), competencies, etc.

3. Competencies are assets that reflect things you or your company are good at or have expertise in. They represent strengths but they’re slightly different than resources, although they can be called resources and just like resources they can be built (like skills), acquired (like experts) or innate (like talent)

A really good example of the use of competencies to exploit an advantage is the case of IBM getting out of the PC market and focusing on providing their customers tailored information processing solutions to their problems under the IBM brand name. They sold the PC business to Lenovo and moved their entire business into IT consulting knowing that they had the necessary competencies in place both software and hardware. That allowed IBM to keep growing while the PC business commoditized.

Putting it all together.

Competencies, resources and positions are at the mercy of the market forces of supply and demand as well as the three patterns we discussed above in part 1. They dictate whether or not the assets you have can be used as leverage.

The patterns of leverage are vast as you can see. I hope with the above I’ve been able to make a dent in this subject. Please note that this post doesn’t discuss the morality of how you use leverage. As with any power tool it can be used for both good and bad. My goal here is to simply make you aware of the various patterns of strategic thinking that we humans use to reach our goals or solve problems and hopefully help you by structuring it into something more usable.

Note: A lot of the ideas in this post came from Richard Rumelt’s book Good Strategy, Bad Strategy