What is expected of me and how did I do against that expectation?
Whether you are evaluating your entire supply chain or a specific node within it, is important never to forget you are dealing with humans. All around us today is talk of metrics, dashboards and SCORcards, all of which provide important information on supply chain performance. But information is only valuable if you understand it and apply it in balance with the human element. By this, I mean that it is human nature to want to know “what is expected of me, and how did I do against that expectation.” For this reason, metrics and performance data can be vital to evaluating supply chain success. Let’s take a specific distribution center as an example as to how we can set a performance expectation and measure against it.
Within a distribution center (DC), control is essential to any goal-setting system. One method of establishing control within a DC is to determine the instantaneous rates at which you expect work to occur and when someone is executing it. For each job function, the leadership must calculate the instantaneous rate at work performance based on the specific market conditions that exist in a given DC. You can calculate the expected rate for each job function by utilizing a combination of order profile, travel distance and material handling capability. When doing this, it is important to remember that in a variable workload environment (which most beverage DCs are) the expected rate for each activity is also variable. Therefore, management must calculate the instantaneous rate on a daily basis.
Again, order profiles, travel distances and material handling capability drive the rate of work performance for each function. Order profile refers to the complexity associated with customer orders. In a DC operation, the following drive the rate of work performance:
the number of full pallets vs. mixed pallets.
the number of layers vs. loose cases on a mixed pallet
the number of SKUs on a mixed pallet
the number of cases per SKU for loose cases.
Distance refers to the aggregate travel distance (on a material handling vehicle or on foot) required to fulfill an assigned task. As a rule of thumb, travel distance results in 70 percent of the time associated with picking a full pallet and only 30 percent of the time associated with picking an individual case. Material handling factors refer to the type of material handling equipment used for loading in the various loading functions. For example, single vs. double-wide forklift attachments, double-length pallet jacks and layer pick devices all impact the rate of work performance.
Just so you make the connection to the supply chain — on a larger scale, profile (make-up of a trailer), travel distance and truck capability drive down transportation costs.
With an approach in place to set targets and answer the “What does the company expect of me?” question, the second element of human nature: “How did I do against the expectation?” comes into play. Unfortunately, many organizations only put the latter into place and measure performance without any type of reference point.
An accurate performance measurement system (capable of tracking individual performance) is an essential step in any supply chain improvement effort. At the warehouse, level many companies utilize a computerized warehouse management system (WMS) to develop performance measures. If you do not have a WMS, you can still effectively measure performance using the Microsoft suite of tools. Even companies that have a WMS will sometimes create performance measure “off-line” depending on the measure being pursued.
Whatever tool you decide to use, measuring productivity at which performers can actually execute work provides management with insight into the overall capability and capacity of the supply chain. To truly determine the capability of a given DC, you must know the actual instantaneous rate and utilization of each individual and actual instantaneous rate and utilization by function. Individual refers to each performer within the operation. Function refers to the various discrete job functions within an operation. Therefore, resolution into each performer in each job function will determine overall capability of a DC.
In addition to instantaneous rate, I also mentioned utilization. Where instantaneous rate defines the speed at which work is performed while a worker is actively engaged in a job function, utilization represents the amount of time a worker spent working as a percentage of the total time available to work. In a conventional DC, a reasonable target for utilization is 85 percent. This means a worker should be actively engaged in a job for 6.75 hours out of an eight-hour shift. The 1 hour and 15 minutes of lost time allows for breaks, pre-shift meetings and post-shift clean-up activities.
When you multiply the instantaneous rate by utilization, you achieve productivity.
The inability of workers to achieve the productivity targets set by management inevitably drives cost into the supply chain. For example, if staffing levels are set on the basis of an order picker achieving productivity of 240 cases per hour, and an order picker only achieves a level of 180, the cost of labor increases by 25 percent. This 25 percent increase excludes the additional overtime hours needed to fulfill the required daily volume.
If you have the productivity expectation and the productivity results, you now have the information you need to make accurate managerial decisions at the same time you satisfy human nature. With this information, you can also identify the root cause of poor performance.
Although we focused on the DC level for this discussion, you can apply the same process at all levels of the supply chain. The trick is to set accurate expectations, calculate accurate measurements, use the information to identify action plans when performance falls behind expectation… and never forget human nature. BI
Ned Bauhof’s “beverage team” has executed more than 100 projects in 85 locations in 10 countries. Ned is a principal with York, Pa.-based St. Onge Co., a material handling and logistics consulting firm specializing in the planning, engineering and implementation of advanced material handling, information and control systems supporting logistics, manufacturing and distribution since 1983 (www.stonge.com). Ned can be reached at 717/840-8181 or by email at NedBauhof@stonge.com.
Finding the cause
If a distribution center’s productivity is lower than expected, there may be a number of reasons, including:
Workers are not following the standard work practices.
No one properly prepared the DC before the shift.
The performer may be physically unable to perform work.
The worker may be purposely working at slow rate. It happens.
Or there may be utilization-related reasons, including:
Insufficient work to keep workers busy throughout the shift.
Worker may have been doing other tasks unrelated to their function during the shift
Time may be lost waiting for a work assignment.
Inability to account for a worker’s time. It happens.
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