Companies can use several different types of standards to set goals for how long it should take employees to complete different tasks in a warehouse. Today I want to describe how single and multi-variable standards are developed, and their pros and cons.
Labor standards are typically characterized as being “single variable” or “multi-variable.” As the name implies, single variable standards are based on just one variable. An example is “cases per hour” picked. One advantage of single variable metrics is that they are easy to calculate. They are also useful in establishing long-term metrics and trends, which look good on warehouse management dashboards.
The disadvantages of single variable standards are that they are subject to seasonal variability; they require long time periods for “averaging” to take effect (one month or more); they are not recommended in large or complex warehouses or in warehouses with incentive-based pay programs; and they are generally not recommended in unionized facilities because they would not stand up to a fairness test in a lawsuit.
In practice, single variable standards are rarely used comprehensively in labor management programs because their disadvantages largely outweigh their advantages. But they can be used for small and simple processes. For example, at one warehouse enVista worked at, there were two people receiving full pallets and breaking them down into cases for put-away. enVista did not believe there would be payback from a detailed study. So, they created a simple single-variable calculation, cases per hour, for this process.
Multi-variable standards involve creating a standard based on more than one variable. For example, in putting together a standard for picking items to several cartons on a cart, the formula might be based on the SKU class (a family of bulky SKUs can be given a greater time allowance), the number of items to be picked, the number of lines on the order (which tells you how many locations the worker needs to travel to), and the number of cartons on the cart a worker needs to fill.
In smaller warehouses, where travel paths are shorter, multi-variable standards can be sufficiently accurate. They have been proven in arbitrations as “fair” and they are suitable for incentive programs. They do, however, require periodic updating (e.g., every 12 months or so).
Discrete labor standards are the most accurate. Discrete standards are a more detailed version of multi-variable standards. In discrete standards, the actual travel distance is calculated, and there are other calculation parameters, such as type of material handling equipment and type of rack used, that make these formulas far more accurate, but are also much more costly to develop than single and multi-variable standards.
I will discuss discrete labor standards in more detail in a future posting.