This week, James Clear posted an interesting idea on How to effectively measure improvements. His main point was that it might be better approach to use short-term feedback to calibrate your actions and your probability of achieving your goals. Most people act based on assumptions of how their future should be or where they want to be. A more sensitive approach is to make small constant improvements in our decision-making model. It is much simpler and effective to use only the most recent information at hand to improve a personal growth process.
Once you incorporate short-term feedback and act accordingly, your decision-making model assimilates these lessons into your personal policy. From this new standpoint, only the most recent information becomes relevant.
As a side effect, the small lessons provide a constant flow of satisfaction and achievement that will keep you on track longer than the excitement of a large reward to come.
There is a clear connection between these ideas and reinforced behavior theories. It seems to me that following this very fundamental (but not easy to achieve) growth pattern, provides a more focused, lasting, and even gratifying process. The big challenge, in my opinion, is to leave behind the long term experiences and trust that your model is assimilating enough of those experiences. Another challenge is to overcome the anxiousness of planning too ahead and let unrealistic goals dilute the thrill of more modest achievements.