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.

The Data Science Pyramid

Data-Science-Pyramid

The data science pyramid represents the importance of data and methods for analyzing it to a business. There are several ways to read this chart.

If I’m a business and I understand the importance of data, I view this chart from the bottom to the top in terms of low value to high value. Rungs 1 through 4 are very important, which is why they are at the bottom. Without them no analysis is even possible, but as a business I still see it as an investment and as cost of doing business. Rungs 5 and 6 are ultimately what I as a business really care about. Insight is slightly lower on the pyramid because while important, ultimately the business truly cares about how that insight informs and shapes strategy.

As a data scientist my main concerns tend to be about the lower rungs, 1 through 4. Given that many data scientists are technologists they care deeply about platforms and tools: (which language do we use R or Python, which database SQL or NoSQL?) about methods and algorithms (do we use linear regression or do we use random forests?) and about data products (do we build a dashboard?, which statistical measure do we use?)

It is important for us to understand that for a business those questions are largely irrelevant. As such there’s a fundamental tension between the first four rungs and the top two with respect to how data science related to business. Our job as data scientists is primarily to solve business problems that have to do with insight and strategy, to inform and help decision making rather than bog them down with detailed calculations.

This tension became very evident to me when I recently interviewed a candidate for a an analyst role. Contrary to the typical interview, he decided to give a presentation to the VPs to showcase a paper he had written on a unique method of doing analysis. It didn’t take long for me to see that he cared deeply about the methods he was using and the brilliant calculations he’d come up with to solve this particular problem. It was also very evident to me that he was really smart and knew his craft very well.

However he didn’t think above rung 4 on the pyramid. He could not translate his findings into insight and ultimately into strategy for the business. He ended up alienating the VPs who had very logical and business related questions while he kept thinking in terms of calculations and analysis. To him rungs 5 and 6 didn’t exist, but to the VPs they were all that mattered.

If we’re going do solve the projected 50%-60% talent gap [1] in data scientists we’re not going to do it by focusing on how to do deeper analysis and number crunching but instead by being aware of the ultimate value of data science, insight and strategy.

  1. http://www.mckinsey.com/features/big_data

How to Build True Agility With your Team

Agility as a term has been overloaded with multiple meanings, especially from the software development perspective. I define agility simply as the ability to change your perspective, your worldview (or orientation as Boyd would put it) and your actions to adapt to what’s happening in the real world. There are two key ideas in that definition. The first one is about change and the second is about adaptability. You need to be able to do both if you have any hope of being agile.

So how do you create agility in your team so that you can respond quickly when the situation changes? Suppose a disgruntled customer tweets something negative about you, and then on top of that he buys an ad that will promote that tweet to 20,000 twitter users. How long will it take you to respond?

It happened last year when a British Airways passenger, unhappy that the airline lost his father’s luggage, sent out a promoted tweet about their customer service being “horrendous” It took BA more than a day to respond to the customer. By then, the tweet had been picked by several media and news outlets. How would you have handled this if you were running the social media team at BA?

If you’re like most companies, you’d have to first find out. if you don’t have the necessary tools in place to get notified when something like this happens, you will unfortunately find out too late. This is the Observation stage of the OODA loop which I wrote about here. Assuming you find out early enough, you might have to go through a lot of bureaucratic red tape getting approval and sign off from everyone involved before a response is set in motion. Not very agile.

If your team was agile, you’d be able to respond a lot quicker and nip that negative publicity in the bud before it starts to spin out of control. Lets take another example. Suppose you notice a problem on your company’s website that is severely affecting conversion. You enter a support request. How soon can the problem be fixed?

If the web development team was agile (and I don’t necessarily mean that in the sense of following agile project management practices) someone can be pulled off of whatever they’re working on to fix the issue quickly. More often than not, the issue will go unnoticed for weeks, if not months and even then, it will take more time to be properly fixed.

So how do you become more agile?

Here are some of the principles of the agile software development manifesto. Let’s analyze them and see if we notice a pattern.

  1. Your highest priority is to satisfy the customer through early and continuous delivery of valuable software.
  2. Deliver working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale.
  3. Business people and developers must work  together daily throughout the project.
  4. Working software is the primary measure of progress.
  5. Build projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done.
  6. The most efficient and effective method of conveying information to and within a development team is face-to-face conversation.
  7. Welcome changing requirements, even late in development. Agile processes harness change for the customer’s competitive advantage.

What do you notice?

What do you get by satisfying the customer through delivering continuous valuable software on a regular basis? What do you achieve by working together with the business? What do you get when your measure of success is working software?

You get Mutual Trust!

What do you achieve by working with a team of motivated individuals who have the environment they require and the support and trust they need to get the job done? What do you get by communicating face to face and welcoming last minute requirements changes?

You get: Mutual Trust and Cohesion

And what do you get when your single point of focus is delivering quality software at all costs?

You get true Agility!

If you study the OODA loop in my previous post, there’s a part of it specifically about implicit guidance and control. This means that there could be a point where you don’t need a formal process to actually get something done. A coworker recently mentioned that they had gotten so good at working with the developers that they no longer needed to discuss things formally, a lot of design decisions were made and communicated implicitly. This allowed both the designers and the developers to operate quickly and get things done faster.

The first element is: Mutual Trust

In order to get to this level of operation, where the team knows exactly what to do and when to do it, the first element you need is mutual trust, unity and cohesion. Not just any type of trust, unity and cohesion, but the kind that is earned through working together through many different projects.

Of course it needn’t be said that at the same time, the team needs to also spend time together outside of the context of work. This will help them get a sense of how everyone on the team thinks and allow them to build that level of trust.

In order to achieve that kind of unity and cohesion, both parties need to be striving towards the same goal. And so the second element you need is the concept of a single point of focus. The idea with single point of a focus is that all the surrounding activities must support it and everyone involved, not just everyone on the team but also the rest of the company, needs to understand, support and work towards this focus.

The second element: Single Point of  Focus

When team members in different departments do not have a single point of focus, they will focus on creating silos and protecting their department’s turf. This is a sure-fire formula to get organizational politicking, power plays and turf wars and lots of bureaucratic red tape. 

How to destroy agility (or what not to do)

The easiest way to destroy agility is to mistrust employees by not believing in their ability to make their own decisions about what’s right and what they should pursue. When things are going great, there’s lots of trust in the team, but when sales start to shrink, many companies feel they need to pull the controls upstairs and start to manage by directive rather by mission.

One of the ways to communicate distrust is by micromanaging. When you micromanage, you are checking everything your team is producing and if you’re not satisfied, you probably end up even doing it yourself. This is very common and it’s a horrible way to manage people. I’ve been there before and it’s not fun. After a while you lose any desire to produce quality work that you can pride yourself on and you lose any initiative you may have had.

How to Get an Advantage Through Faster Tempo – Time based Competition and the OODA Loop

John M. Boyd was an air force pilot who earned the nickname “40-second Boyd” due to his ability to defeat any enemy in combat air maneuvering in 40 seconds or less. He was very much interested in theory and later on, after he became a consultant he developed a brief called Patterns of Conflict summarizing military strategy from Sun Tzu, to Hannibal, to WWII Blitzkrieg, to guerrilla warfare.

Despite all this, the one concept he’s most known for is the OODA loop. It grew out of his theory of learning which he called Destruction and Creation and is the only paper he ever published. In it he discusses the processes of analysis and synthesis, which later would play a role in the Orientation phase of the OODA loop. 

Destruction and Creation

According to Boyd, through analysis you break down the whole into pieces so you can understand it better, and through synthesis you put various pieces together to create a new coherent whole. The key is to shatter the domains that hold the pieces together in your mind so that they are no longer connected to those domains. The relationship between those parts and the whole is to be destroyed before a new whole can be created.

Boyd’s example was the snowmobile. You take the treads from the tank, the engine of an outboard motorboat, the skis and the handlebar of a bicycle. When you take each of those parts individually and you shatter the links they have to the original concept (tank, boat, bike and ski) you are able to see how you can put them together in a whole new coherent way (the snowmobile). This according to Boyd was creative destruction. 

Fast Transients

After destruction and creation, Boyd set his sites on trying to understand warfare, especially how the US who was better equipped ended up losing the Vietnam War. He started his analysis by looking at why the F86 had more wins than the MiG despite the fact they were very similar in what he deemed energy-maneuverability (another concept he created earlier in his career as an air force pilot).

After working on it for a while he discovered that the F86 was able to go through changes in speed and direction much faster than the MiG due to it’s hydraulic controls vs the MiG’s mechanical controls. The F86 also had a much winder angle canopy which allowed the pilot a better view of the enemy. We’ll come back to that when we discuss the observation phase of the OODA loop.

The ability to quickly switch maneuvers in response to what your opponent was doing, was a key advantage that created a rapidly changing environment and caused confusion, disorientation and panic in your adversary rendering them unable to adapt quickly. This meant that in order to win, you had to operate a faster tempo than your adversary in fact you must operate inside their tempo.

This led him to create a brief called Patterns of Conflict which started out small but then ended up growing to be 8 full hours!. During the slides of the brief, as Boyd is explaining the key concepts of the blitzkrieg and guerilla warfare, he mentions the concept of the OODA Loop, or Observe, Orient, Decide, Act. According to Boyd, if you were able to go through the OODA loop faster than your opponent, you could essentially win without having to resort to attrition warfare.

The biggest misconception about the OODA loop is that it’s a simple step by step process comprised of four distinct steps which you then try to loop through as quickly as possible. Boyd’s concept was much more than that as we’ll see. 

OODA Loop

 Here is a diagram of the OODA “loop”

Image

During Observation you gather as much information as possible through your five senses and unfolding circumstances, unfolding interaction with the environment, feedback from any action or any decision you’ve taken and more importantly implicit guidance and control. Anything that hindered your ability to observe clearly and get accurate information about your environment will hinder your ability to orient yourself properly and cause mismatches between your “reality” and you opponent’s “reality” This was his key insight as to why the F86 was superior. The MiG’s canopy restricted the pilot’s view, creating blind spots that could easily be exploited by the enemy.

Because the key to the OODA Loop is how fast you switch maneuvers, you don’t want to be spending too much time Observing, you want to quickly move on to Orientation. 

Orientation is the key to the entire “loop” What Boyd meant by orientation is in a way the opposite of disorientation. Your goal is to bring about things like previous experience, new information, analysis/synthesis, genetic heritage and cultural traditions to create a complex integration, or as I like to call it a mental model of the situation. What Boyd means here, is that you should be able to read a situation in such a way that is as close to reality as possible and keep it that way so that you don’t get disoriented. When you do that, you’re able to dictate and shape the mind of your opponent in such a way as to bring about disorientation and confusion and inhibit their ability to make clear decisions.

In the Decision phase, you create a hypothesis of what the orientation suggested and you test it by taking Action.

The most important thing to note here is that these stages do no need to occur in this order. Notice the arrows for implicit guidance and control between orientation and observation/decision/action. What this means is that there’s a point where a you can achieve an intuitive sense for how the events are unfolding. You get an insight and it happened to match reality perfectly. Once this happens, you no longer need to go though the stages one by one, they begin to occur simultaneously. You can now begin to dictate the tempo of decisions and shape the mind of your opponent. This allows you to win more easily. 

Fast Tempo Offense in Sports

I don’t like sports metaphors in general (since not everyone is a sports fan) but they illustrate the OODA loop perfectly. In the American NFL, NBA and in other sports, the idea of a fast tempo offense is starting to become more common. There will be a stage during the game where the coach will notice something in the defense, the game situation , the score, etc. and decide to speed up the tempo of the game in order to catch the defense off-guard or to dictate the tempo and score more easily.

The coach will observe for example the certain set up of the defense, how tired they look, their energy level, how much attention they’re paying in the game, take into account the score of the game, the clock, how well his team is advancing, game film that he’s seen previously of this particular defense in this situation, the type of defense he’s dealing with, plays they ran in practice, etc. and orient himself to the situation by creating a mental model of the reality. During orientation, he will get an idea that maybe by switching to a faster tempo, he can spark the offense, disorient the defense, advance faster and score easier.

He makes the decision and calls for quicker/higher percentage of success plays. Given how accurate the read of the situation was, how successful the play was, how the defense reacted, (this is feedback that will shape his orientation) he will go through the loop again and decide whether to continue the quick tempo while the defense tries hard to adjust. It’s very important that this fast decision making tempo be kept up in order to keep the defense guessing and delay/inhibit their ability to orient and adjust to the faster tempo. If the read of the situation was accurate, the coach will start to get an intuitive feel for the game and know exactly which plays to call in order to be successful.

Fast Tempo in Business

In business, if your orientation doesn’t match reality, for example when you’re clueless about what the customers really want, you will end up slowly declining and eventually go bankrupt. A good example of a company who operates at a fast tempo is Google. When Google first launched, AltaVista was the most popular search engine (in fact Google founders Larry Page and Sergei Brin, actually tried to license their search technology to AltaVista but they refused).

Internet search engines had a problem. They would display results without any sort of relevance, making it hard for you to find what you were actually looking for. One can say that their orientation to the marketplace was off. Google invented an algorithm called PageRank which assigned a rank to a website based on how many other sites linked to it. This was an insight that Brin got while he was working on a project to digitize papers. He noticed that the best papers had the most references from other papers.

People started to switch to Google as their main search engine and sites like AltaVista didn’t adjust so they headed for a decline. Not willing to adjust they slowly went out of business. But Google didn’t stop there. They monetized search by placing text based ads next to the search results. If you wanted your website to show up as a top search result in Google for certain search terms/keywords, given that most people didn’t go beyond the first 2-3 pages of search results, you needed to outbid your competition for those specific search terms/keywords.

However the natural search results were free! So people tried to figure out how Google’s PageRank algorithm worked by reverse engineering the search results (since this information is proprietary to Google) and then try to optimize sites or game Google’s algorithm so their site would appear on top for the desired search terms/keywords. The SEO (search engine optimization) game is still being played to this day. The problem isn’t that people try to figure out Google’s algorithm, the problem is that unscrupulous marketers were using unethical techniques (also known as “black hat SEO” from the popular term “black hat hacker”) to try and game the search results and have their sites show up on top undeservingly.

Operating at a fast tempo, Google began periodically updating the algorithm in order to stay one step ahead of these “black hat” SEO hackers. If Google didn’t operate at a fast tempo, they would soon start to lose credibility in their search results.

This is only scratching the surface of what the OODA Loop can do. Some of the more interesting applications of it can achieve the ability to shape the marketplace, shape the mind of the customer and the mind of the competitors to keep them at bay. For more on John Boyd, check out Robert Coram’s excellent biography “Boyd: The Fighter Pilot Who Changed the Art of War”