It is a mistake to look too far ahead. Only one link in the chain of destiny can be handled at a time.
– Winston Churchill
Earlier when discussing how to engage and lead people with respect, I described the coaching kata. The key is to focus on a target condition, and the next step to get there, running what are effectively experiments in a PDCA cycle. A similar method can be used with improvement projects, the improvement kata.
As with coaching kata, the first step is to set a target condition. The target condition is different than a goal in that it is the ultimate condition, what has to occur for the process to be successful. For example, if the customer demand is one unit each day, then that is the target condition. Not a goal that may be a great improvement, but still does not achieve what the customer demands. As always you must also know what the current state is, the actual condition.
Once we have the actual and target conditions, you need to observe the process and identify what obstacles are preventing you from achieving the target condition. These may be training, equipment, technology, human talent, facility, and so forth. Do not spend too much time prioritizing obstacles or attempting to gauge the relative impact of the obstacles.
The kata method is based on moving forward one step at a time using small experiments, creating rapid small improvements or learning from rapid small failures. From your list of obstacles, identify one that can potentially be improved, and run an experiment. What was the result? What have you learned? And what is the next step? The next step can be another small experiment building on the success or failure of the current experiment, documenting the improvement from a successful experiment into standard work, or it can be more analysis of the current experiment. They key is to simply keep moving forward to the target condition with rapid experiments.
Note how different the kata method is from traditional improvement projects. The end point is the ultimate target condition, not a goal. All steps between the actual condition and the end point are not defined. Instead of a detailed action plan, just the next step is acted on. This can turn traditional project planning on its head, but the rapid experiments creates ongoing forward movement and, perhaps most importantly, lots of new knowledge.