The CalcuQuote learning curve provides a more accurate labor cost model by applying learning curves to variable labor activities. Here's how it works.
Labor Learning Curve Overview
CalcuQuote's labor calculations are organized by labor activities (aka, routing steps). For each variable labor activity, you can define a learning curve on a scale of 1-100 to show how significantly the per-unit cost for that activity is reduced for each additional unit of production. This is useful for activities where there can be significant efficiencies gained from repetitive builds. For example: doing a manual quality check (QC) for the first assembly is usually more time to consume and thorough than on the 10th assembly. This gain in efficiency could be reflected by the learning curve variable.
A 100% learning curve signifies that there is no efficiency gained. This is typical for robotic, automated activities where the machine operates with the same level of efficiency regardless of how many times that operation has been performed before. The lower the learning curve percentage, the more significant the drop in variable costs for that activity between consecutive units of production.
In CalcuQuote, the labor learning curve is defined as a default for each variable labor activity. You can also adjust the learning curve for an activity independently for each assembly that you are quoting. This means that even if your default learning curve is set at 95%, you can still adjust the learning curve for a particular assembly to be 98% for that activity without changing the default value for future or past labor calculations.