How to solve problems vs. who can do it?
The distinction of complex and complicated
Know the difference to find the right way to solve your problems.
Today every company should strive to add better and better value to its customers by extending existing or offering new services. Obviously, some competitors are better than others. Those are the ones that are often said to be "smart", "fast growing" and roll up the market quickly.
What is their secret?
Even though there is no silver bullet for being successful as a company, one can observe some aspects that could be generalized from a bird's view.
In this article I want to share a very important distinction between two kinds of problems that should be solved differently to be successful.
Different kinds of problems
A problem here is another word for "challenge" that the business needs to overcome. David Snowden divided the problem space into five areas with the Cynefin framework. Here I want to focus on only two of them as they have much relevance for business and are unfortunately mixed up with each other with severe consequences I talk about at the end of this article.
These two kinds of problems are totally different to each other: complicated and complex problems.
Complicated - the "blue domain"
A complicated problem could also be called a problem where you need knowledge in order to solve it. I.e. it is a problem which has already been solved in the past (by you or someone else) and you can use that existing knowledge for it. A routine task so to say.
It has several interesting attributes. Obviously, you know what steps you have to do before you come to a successful outcome. They are causal i.e. you can put them in an if-then-relation. There is exactly one effect for one action / cause and vice versa. Because of the causality, complicated problems are controllable and predictable. That means, someone could know what to change in the context to come to the desired result. Solutions can be rated as "right" and "wrong" upfront. Therefore a step by step solution (that is a plan) can be applied for it.
As a result, if I know the if-then-relations I can solve the problem.
An example of a complicated thing is a ball rolling down a track. If I exchange the right curve by a left one, the ball will roll down in the left direction. I can be sure that the ball will roll down, if I tested it before. Therefore children can plan a track with track pieces and predict the movement of the ball. A more complicated example is an engine that can be deconstructed and reassembled only by experts. But once they studied the domain long enough and gained enough knowledge about the specific engine, the expert is able to do his work.
Blue domain
Creating value by knowledge- Complicated
- "Problems of the norm"
- If-then-relation, causal
- Controllable
- Predictable
- Knowledge is the key
Dependent on the available knowledge - Example: (mechanical) items like a watch or a marble track
Complex - the "red domain"
In contrast to this, a complex problem is something totally different. This is quite important to emphasize, because "complex" is not an extension of "complicated" or "more" of it. It is just something completely different:
A complex problem needs a solution which you have never found before. So existing knowledge cannot be applied. This could be something completely new on the one hand. But on the other hand a complex problem will not be easier to solve even when the same problem has been solved successfully in the past. So the repetition over and over will not make a complex problem complicated! You cannot turn complexity into something complicated!
Thus, there are very many solutions to a complex problem but you don't know (literally; by using knowledge) which one will lead to a resolution. Therefore you cannot successfully follow a step-by-step approach i.e. a plan. To be more precise: the outcome could still be successful even though you followed a plan. However, the reason for solving the complex task was not following the plan. We'll come to that later.
Another attribute of a complex problem is that it cannot be controlled nor predicted with guarantee. As a result, the nature of complex problems is uncertain and full of surprises.
A current situation evolved to a given state but it could have become totally different, too. [Technically speaking for systems thinking nerds this is because the range of possible transitions from one situation to another is larger than the number of state transitions that can be applied at the same time.]
Red domain
Creating value by ideas and intuition- Complex
- "Surprising problems / exceptions"
- Contingent (i.e. the situation just emerged this way)
- Uncontrollable
- Unpredictable
- Having intuition and an idea is the key
Dependent on talents and the specific human, who solves the problem - Example: any human interaction like a sales pitch
Examples are numerous, generally speaking every aspect where humans are involved, for instance a sales pitch. No one in a sales talk can tell what exactly and how it should be said (by whom) in order to sell the product to the customer. Not even the customer knows what needs to be said. Even if you have sold a product to your customer, there is no guarantee that the same sales representative will sell the exact same product to the exact same customer twice when he behaves the same way and says the same words.
As a result, solving a (pure) complex problem cannot be done with cognitive skills. Instead ideas from humans are needed that can be tested, if possible in a trial and error approach. Having an idea originates from the gut feelings, so it is a response of the body (not of the brain).
Imagine the sales guy "thinking" based on logic what needs to be said in order to sell his product. After some time has passed, he says the correctly calculated magic words and ... no, this won't work. Instead he has to react to his surroundings, find the right tone and words and react accordingly to hunderts of emotional inputs from the situation. A good sales person "knows" how to react in some situations, however this is actually a learned behavior (from a lot of failures) supported by his talent.
Why is this important?
The distinction between those two types is crucial, however not so obvious in the first place.
As you have learned by now, each kind of problem needs a different way of handling in order to solve it. Complicated problems need knowledge in order to solve. Complex problems need ideas from humans.
This finding is the key to a new point of view for problems in a company.
As you can imagine, the world of problems is not strictly black and white (or "blue" and "red") only. Real world problems consist of both types.
Successful companies try to split their problems into complicated and complex domains and solve each part the appropriate way.
Handle complicated questions with knowledge and complex ones with employees that have talents addressing the attributes of the problem.
By doing so it is easier to react to "surprises" which are created from competitors on the market. On the other hand, it is easier to create pressure (i.e. put new surprising services / products etc.) on the market. That is what we have been observing by companies like Amazon, Tesla for instance in the past. Companies that don't understand the distinction are less likely to handle the fast market changes any longer. They typically collapse on surprises.
And when there is no tool to solve complexity, the learned "resolution process" kicks in and tries to solve the problem by applying knowledge with all the classic management approaches that became famous during the mass production years. Strong hierarchies, bonus salaries, wide ranging planning with budgeting, employee utilization optimization just to name a few.
Those management principles make sense when employees work on problems that just need to be done with little thinking. Simple tasks like sorting out products on an assembly line. The faster the employee handles the task, the better.
Complex problems, however, need ideas from employees. They cannot be "produced" faster nor better when there is a bonus system for instance.
The method trap
The distinction is important for another reason. When we encounter a complex problem and haven't understood the theory behind it, the dilemma becomes worse when existing knowledge in the form of methods are applied.
This is a natural reflex, because our brains want to process rather simple and logic problems instead of complex ones. This saves energy.
However complexity cannot be turned into something complicated.
Once you know this, you are less tempted to say something like:
"Just throw more data engineers onto the problem...",
"Artificial Intelligence will fix this..."
"We need to work with SCRUM to deliver faster..." etc.