Hunting for problems

In a previous workplace of mine, there were a lot of strong, capable people who were good at problem solving and very oriented to that. However, they were not always good at identifying the right problems to deal with nor defined the problems well. So they went on and hack away at problems that were poorly defined and ended up not solving much. A lot of resources, energy and efforts were squandered on poorly defined problems.

To give an example, we could think about it from the perspective of an observation first. Say, there is a cat which is on a tree and meowing. Objectively speaking, it is not clear if there was a problem. It might be a problem to the flat owner on the second storey who is annoyed by the noises made by the cat. A cat lover might think the cat is stuck on the tree and unable to get down. The one who planted the tree and lives on the ground floor might think that the problem is that the cat might scratch and damage the tree. Now if you want to help, you need to define the problem in the context of someone’s perspective.

While there seem like a ‘straight-forward’ solution which is to remove the cat from the tree, if none of those people I mentioned saw it as a problem, then it would not have been considered a solution to begin with. If we contextualise the problem as the meowing, then the solution could just be to get the flat-owner to put on earplugs or insulate his flat from external noises better. Without the other stakeholders in the room, the solution set actually expands.

Problem solving is just the last stage of a repertoire of skills we need in the modern workplace. Being able to identify, define and contextualise problems can be just as, if not more important.

Going back to objectives

What happens when you are ‘stuck’; what exactly does it mean to feel stuck. Is it more about not making progress? If so, then progress towards what? You can’t get stuck if there’s no sense of destination you are trying to get to. And having no destination is not the same as being stuck. Because not knowing where you want to go means it’s perfectly fine wherever you are! Stop thinking like you need to go somewhere if you’re alright with here and now.

If you’re not alright with here and now, and unsure where you need to go, then it’s not about getting out. It’s about figuring where you want to go. And figuring out where you want to go has more to do with rethinking about your objectives. Your objectives for life, for lifestyle, for your work, your career, your relationships and all. Reflect on what is it about the here and now that is uncomfortable; consider what you know you want, and what you don’t know you want.

The same applies to problem-solving. When you feel that you’re not progressing towards the solution, and hence ‘stuck’, it’s time to revisit the objectives. What are you trying to do exactly? Have you contextualised or defined the problem in a way that narrows the solution set such that you are missing out things that can get you your objectives anyways. For example, if you are looking to hammer a nail into the wall, and you contextualise the problem as you “needing a hammer” then you essentially ruled out solving the problem by using any other equipment.

Revisiting objectives helps; and that’s also why it is sometimes difficult to deal with higher level issues by contextualising a problem within a silo-ed context. That would be a good topic of discussion for another day!

Passing exams

It’s interesting how people are amazed by ChatGPT passing exams. Exams are narrowly designed processes with somewhat clear rubric for determining scores, exactly the same type of process that had been used to train and improve machine learning and artificial intelligence. Never mind that it’s passing Wharton MBA or law exams, these are special situations which are designed specifically to be somewhat ‘gamed’. And these are the situations where machines are in their elements.

The fact that they only pass the exams and not excel, reflects that the variability of the exams and the desire to really pick out top human candidates. This is also a test for the exams-setting as it reflects that they are not at all about just getting the answers right. Rather, exams should be designed and set to be open-minded to ‘surprise me’ type of situations.

We could all become machine-like, ask ‘What is going to be on the test?‘ and then approach it by trying to get answers right to everything. Or we can learn to solve real world problems by acting like humans, accepting our weaknesses and vulnerability, and cracking on bit by bit. Problems are rarely solved by invulnerability – they are typically solved by first acknowledging what we don’t know and moving at the edges of what we do know.