Time to competence rates in training scenarios are something that are very delicate and also must be watched closely. It is the measure of time spent converting an untrained individual or group to an one capable of applying the subject matter practically in the workplace with confidence.
Obviously, in most cases, time to competence rates will therefore have pretty big base numbers, so you have to think on larger digits with lower values. Once you factor this in, determine when the units are too big on upperbound by comparing similar case studies of successes and failures.
Now, you have a metric and bounds for suggested constraint. If it is too long, you know it. You are now powerful enough to make modifications to the scenario to improve the clock rate of this machine so that the training process works more efficiently and at a higher rate.
There are a lot of internal variables to tweak here to modify performance, so let’s look at the ones you’d mess with the most.
The primary thing that may be causing lag is the social dynamic you are using to support the process. It may be time to retool it and reshape it so that it works at the expected tolerance. This will greatly remove lag from the time to practicality duration.
Another common problem is that the material is being inhibited by some hangup in the team. It could be something as simple as learning inhibitions, lack of team mindedness and other social defects. These do not affect the dynamic but affect the individual. These must be dealt with by workshopping casual gatherings to encourage comfortable social relationships and wider awareness will reduce lag from social barriers here..
Another lag is time available for training. If you cannot give work day training sessions, the units are going to be huge. The only way to really work past this is to, you guessed it, use more real time per session to shorten the global duration. This is akin to tweaking the frequency at which the machine operates.
Finally, we come to the biggest barrier and variable to work with, energy input. This takes the form of incentives and motivation as well as all facilitating expenses involved. This is the reward system to drive employees to learn faster and master the new material. This eats time, effort and expenses to accomplish. However, a better budget will produce more energy, to give it higher fidelity on top of the increased frequency and strength.
We just compared tweaking a training engine to tweaking the cycles of a microprocessor. That was fun, wasn’t it? But, take that allegory to heart, because there is meaning to it. Systems, even abstract one made by people obeying procedure, are still a mechanic, a machine of sorts. All work done mechanically has a frequency control like these values, allegorically. So, with the right knowledge of how the values work, you can indeed program your training engine and for temporary time periods the people within it, to meet goals at a much more efficient rate.
This time to competence rate increase is worth all the expense and effort, so show this to your bean counters when they demand ROI forecasts