Just an FYI: Here is a paper I put together for using Data Envelopment Analysis for benchmarking. My paper is OK; but does have references and an example. The initial work came out in 1978, and is extremely popular due to its flexibility and approach. Feel free to Google Data Envelopment Analysis for more information.
Basically, it’s a comparison of all relevant inputs to all relevant outputs, and how efficient each unit/department is with what they have.
Basically, it’s a comparison of all relevant inputs to all relevant outputs, and how efficient each unit/department is with what they have.
- This was initially designed for determining efficiency within non-profit entities; hence the reliance on relative efficiency. It has subsequently been used in all kinds of different industries.
- You don’t have to change everything to the same units. You can have labor hours, # of temps, $material, etc. This is a relative efficiency tool.
- These can be solved using Excel Solver; you don’t have to have some specialized software. If you’re not into programming and math stuff, I would skip the formulas in the paper. The math stuff is not mine; and is common within DEA. Do look at the inputs and outputs.
- This is an exercise to identify all the inputs and outputs in a process; it’s not designed to find the substandard workers. It is theoretically assumed that all workers are equally efficient.
