Back in July, I wrote a posting about the great results that DSC Logistics received after implementing a Labor Management System (LMS) in its warehouses. In one section I wrote that DSC “used a predetermined time system, Master Standard Data, as its methodology.” I knew at the time that some readers would not understand that reference, but I didn’t have the time or space to explain.
So today will be the first of several postings on warehousing labor standards basics, which I assume will be of value to logisticians who have not taken a course in Industrial Engineering (IE).
Because I also lack a background in IE, I reached out to leading consultants in this area, including Al Gagnon and Tom Stretar of enVista who were particularly helpful.
In warehousing, a labor standard is the amount of time required by a fully trained associate, working at a reasonable effort level under normal operating conditions, to complete a task.
How are standards created?
- You could guess or estimate the time or even arbitrarily set a standard, which is not uncommon. Often this rolls down hill from the budgeting process. The CEO demands a 5 percent improvement in productivity so he can impress Wall Street. The COO demands it of the VPs of manufacturing and distribution. The Distribution VP demands it in the warehouses. The warehouse manager then decrees that picking must be done 5 percent faster based on some measure (e.g., cases per hour). After several years of this, if workers are held to these arbitrary standards, you often have too many injuries and too much employee turnover. Or you have a very unhappy workforce that decides to unionize.
- You can also use historical data to set standards, such as the transaction history in a warehouse management system. You can use this data to examine on average how long it takes to do certain types of tasks. You can create single variable or multivariable time standard formulas using historical data. The problem with averages, however, is that the average speed with which work is being done can represent far less than a “reasonable” effort.
- There are also time studies. Time studies involve consultants with stop watches timing how long it takes to do particular types of tasks. This is one way to develop very accurate standards.
- Finally, there are predetermined time systems. Pre-determined standards are based on tables that document how long it takes to make very elemental motions. In warehousing, Master Standard Data (MSD) is the most common predetermined time system methodology. In MSD, the two most common elemental motions are “Obtain” (grasp and take control of an object) and “Place” (move an object to a new position). These elemental motions are aggregated into patterns. For example, mounting a pallet jack is a pattern built up from a series of elemental motions measured in Time Measurement Units (TMUs). A TMU is equal to 1/100,000 of an hour. This is, perhaps, the most granular way to build time standards.
These standards are often tracked in an LMS. Multivariable, time studies, and predetermined time systems can create daily scoring systems for associates. Often 100 (or 100 percent) is considered a full and fair day’s work. If an associate has worked at under 100, they have not worked up to the standard. If they score over 100, they have exceeded the standard for that day.
Single and multivariable standards, time studies, and pre-determined time systems will be described in more detail, as well as their pros and cons, in future postings.