Maximum Point of Optimization (Saturation Point)

In life we try to embrace a forward way thinking of looking at possible ways of improving ourselves and our tasks.

This is a very good mindset but we need to consider the following:

All improvements/optimizations for a specific approach have a saturation point where efforts to better will have close to no impact or possibly a negative incline in the overall result. When a new idea or approach is set in motion it is the best opportunity to push efforts into optimization, but once it reaches maturity and becomes a working model, one should revert to smaller changes without big expectations of improvement. This will typically play a role on a micro level like oiling the system but have no real benefit to the overall result. If a big methodology change is made it might once again bring up the opportunity for more meaningful optimizations. A couple of different types of results you can expect:

• No improvement (Either wrong idea or it might be that the model is mature and has reached the saturation point for optimizations)
• Improvement to one or more focus points but negative effect on other parts (Pros and cons should be weighed from a holistic viewpoint) If you for instance implement a much more sophisticated step by step reporting system you might have better statistics on current activities but because of the extra overhead you might lose productivity that might hurt you even more.
• Small improvements (This should be seen for what it is, no big overall impact but might ease the execution - oiling out the system) These might have other positive impacts that are difficult to measure as job satisfaction, better relations etc.

Don’t ever try to change a system before you understand the dynamics of the current working system as you are very likely to both fail and damage relationships. (You need to know the rules before you can break them)

A good rule of thumb is to try new ideas but always keep the bigger picture in mind. The younger the concept the bigger the challenge to the process should be and although you should not expect amazing results for each iteration of change you should attempt it as such. Finally when your ideas don't work don’t try to force it, take the hit and consider the reasons and evaluate whether you have reached the maximum point of optimization.