[11 min read]
I know it, for sure. No, you cannot. The things get complicated if humans start to struggle with what they know, what is possible, and what is real. Especially in IT, based on programming and formalized approaches for dealing with the real world, it’s not only important to be as much as possible close to it. However, due to complexity, this might not always be the case. Then, we help ourselves with some kind of believing.
The newbie
As far as we understood our outside world, we tried to understand also the dependencies. Here a candy, there a shout out, wrangling, hugging, loving and hating – all those things come usually for us out of the blue if we aren’t the originator of such. The survival pattern in all this unordered events is to select the important ones for us at the moment those happen. First hand, this means to focus on something that might be not the most urgent one, second it will mean to discard all the other events. A snapshot of our focused time reflection is what we understand as the real outside world.
Challenging might be in this regard that we remember and learn from those events with very limited context. This, however, is our foundation of what we describe as experience.
Experience is key
Starting with our first days in our job, especially in IT, we quickly adsorb at huge amount of information that needs to be collected, ordered, stored. Later on, this information may be recalled, tackled for proof in various situations – and then stored as a ‘lesson learned’. There is usually context to this learning, in time, in relation to other events, results, and challenges. While this all is based on observation with a limited view, usually lacking the “full picture” as we say when we miss some or more information, the learning is biased right from the start.
During front teaching, biased learning is what we want to accomplish. In self-experienced learning, the results are also biased but not as a goal. However, whichever approach you choose, the bias will be an integral part.
Learnings being incomplete, usually do not surface immediately. If new learnings clash with previous, it’s usually understood that the mismatch must be because of a mistake with the previous, but leaving room for investigation. Having room does usually not mean to have time to do the investigation and check about this mismatch. There are three ways to approach this, still: discard the old learning, skip the new learning, keep both. The latter is at a first look a good approach, since we keep both. What this usually then makes it challenging in the future is that we can perhaps remember our feelings with the one or the other but those got blurred if no other context is that evident that it’s an inherent part of the learned. The other both options are usually the quickest: decide and forget, discarding information and overwriting the probability to be false on something. This cascades with any new experience.
Focus on what ?
Because of the overall complexity in our life in general, we need to focus on things that seem to be understandable. A way of doing so is applying models. Models help to remember the – for us actually – essentials of situations. Although we name it not this way, except in science and engineering, this is the foundation of how we as humans reduce the outside world with all the highly dynamic influences and complex dependencies to something more handy.
This also happens for predictions or actions. While those sound differently, the latter is pretty much just a follow-up on something we predicted – or just imagined to may become real if we “do” something. The action resulting might be appropriate in any mean, inappropriate, or just complete nonsense. Sometimes, we know it before, but still apply the action. Other times, we might act but then figure out whether it was appropriate or not and can next time perhaps act in the same way or learn from it and do it next time better. But what exactly is this ‘better’ ?
Since the focus of a learning is reduced to what was ‘remembered’, it might be appropriate to do something based on empiric learning from the past. This might not always work and hence the saying is ‘think twice’. If time is available, this might open up the world again for collecting additional data around us and perhaps combine those into a ‘bigger picture’. Since time is always a resource being short, only philosophers can keep on collecting additional information for a pretty much infinite time.
In real world, the window for decisions is very small and information is limited. In regards to the ever changing environment and with complex dependencies in addition to what we immediately experience, our base for a profound decision is very vage. We need to guess, apply our models, and hope for the best.
Hope for the best
Here it comes in, what I call the principle of hope: Since in almost all cases, we have a very limited understanding and ability to predict the world’s move in the future, being it right now after or just in the time frame we look at, the outcome is something that we wish to happen. It might be based on something like data, signs from our peers, and experience, but we have to apply our model of the world in order to decide and act.
The outcome of these decisions is open. With the look to IT, the complex matters in a very broad technological environment may be overwhelming to the most of us. The most things that form an environment are usually out of our comfort zone. However, the challenge is that we must decide and act, regardless whether we have fully understood the complete set of dependencies. This is the time when we hope for the best that nothing would break, the outcome will happen, the things we planned to do will work.
Hope is depending on fortune and not the best base for a strong path towards success. With any planning applied, still there will be no guarantee that everything will work as we thought and wished.
Success is organised
Because we cannot tell the future, we should try to understand the dependencies and not simply believe in something said. Success should be planned and everything else is down to fortune.
Not only in IT but also in real life, which as well happens within the application of our actions to achieve something also in IT, understanding the technology well, understanding dependencies, understanding people and existing processes and their shortcomings are a foundation of success.
Processes are good for standard situations but fail if things happen that weren’t planned for. However, with good processes, the most situations can be caught and steered into a known handling approach. Good processes, however, should exist at any level and having the best processes to guardrail unforeseen situations matters most.
To avoid wild guessing, reducing complexity in changes and steps is good practice, especially in software development and project management. Applying those practices as a standard way in business in general would help to create well performing processes.
Since we don’t know everything, we should check with peers, experts and listen. Well, even if we need to trust people in this, still we together might check for obvious pitfalls and plan for the unexpected.
Keep calm
Even with the best planning, experts being involved, processes in place, and affected people included in the planning – it can still fail. It can fail for “external” reasons which is a wide term of everything else that we haven’t planned for or is just happening. Those things are there and blaming Murphy does not help – but helps understanding that we cannot know everything nor can we plan for everything, but it simply reflects our all shortcomings. Then keep calm, find the most important things to fix first, and …. hope for the best.