Solving complex problems (part 2)
The problem statement (summary)
As new projects appear there is always an underlying question: “can we make it (on time & budget)?”. At this moment anything can happen, this is the big bang of any project, the uncertainty is pretty high, and its complexity starts to get bigger. In many cases I have seen projects fail because they didn’t achieve one of 3 major variables: resources, time and scope. But this is an oversimplification to a problem that is even more complex, the project triangle is just the symptom and not the input.
In other words, the problem is: how can we live with the project’s complexity? How can we reduce the risk of what we don’t know?
We should change our mindset to think about products as a living complex system and projects as the system that makes energy flow.
How can other disciplines help to solve our problem?
Logics and Lean: Invalidate sooner
“The basic form of the response is to assert that the person who holds the justified true belief (for instance, Smith in Gettier’s first case) made the mistake of inferring a true belief (e.g. “The person who will get the job has ten coins in his pocket”) from a false belief (e.g. “Jones will get the job”)” — Epistemology, Wikipedia.
We used to think that projects are a pod, and sometimes we tend to think about the happiest path in order to simplify everything, because that is what we do, we change our environment to something that our brain can understand. The happiest path may be a good start, but then we should try to invalidate your assumptions (as it’s presented in Lean Startup by Eric Ries), this will let us think about different realities and how different variables will feed our project to let us see it as a complex and adaptable ecosystem.
Invalidating sooner our assumptions may point us to the right direction, reducing risks and avoiding unnecessary work.
Source: PDCA: https://en.wikipedia.org/wiki/PDCA
In project/product development we usually talk about PDCA as a scientific method to a lean production. This cycle created by Dr. W. Edwards Deming recalls the scientific method: Observation, Question, Hypothesis, Experiment, Conclusion, Result.
How is this relevant to this study? It’s a clear framework to invalidate our hypothesis, as this falsification can get us to a more probable “truth”, and with this point us to the right direction, making this a tool that connects the previous discipline.
The big question is: can we treat a project/program/product as an isolated system? Can we say that we can create an ecosystem? In general terms the less time that we put our lens on it, it becomes easy to handle uncertainty, but as it gets bigger it becomes more volatile, and more difficult to encapsulate. So, in none of these cases we may think that our scope is an ecosystem, because any changes on the outside will affect it and changes inside it will affect the outcomes.
This course gave me a new point of view on what ecosystem means: in other words, (as in nature) everything is connected. Your product development may be slowed or even canceled due to a flu that started in Asia (https://en.wikipedia.org/wiki/COVID-19), or due to a disruptive product that is getting adopted faster than yours.
Ethics, Humanities and Machines
Should we always know everything even if we didn’t ask? If a machine tells us that the project will fail, should we quit? Human will and intuition is still better than any machine, or maybe there are some aspects that cannot (or shouldn’t) be automated, even if they could.
There is still a lot that humankind can do, there is still room for unleashing our greater potential.
Liberating structures proposes a “menu” of activities based on complex analysis that look to empower groups of people to free themselves from traditional structures that slow or stop progress due to unexpected unknowns. These “microstructures” are intended to “enhance relational coordination and trust”.
Find a source (or sources) that addresses complex problems in the modern world or near future. We encourage you to look at sources that combine multiple disciplinary approaches, or that use established scientific, statistical, or humanistic approaches in novel ways. Sources that critique traditional approaches are also acceptable
But technology is increasing exponentially and that can’t be stoped. More and more jobs become automated, and with that humans become a deprecated work force. This will introduce new issues to global equity and access to jobs. Governments and organizations should be prepared to help these people to find new paths.
Let’s take a different thinking approach, most of these automation processes are meant to be efficient, they will produce the needed amount of products/services based on the minimum required resources and with that abundance will start showing up. Can you picture this future where humans are more humans instead of a workforce?