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Analysis of predictive sorting and process standardization at Amazon.com

In any process, complexity has the potential to
decrease processing rates of the operation. Mass production has
driven up operator efficiency by removing complexity to create a
standardized and simplified process. However, removing complexity
from a process reduces the operator's ability to customize their
products and remain flexible to variations in demand. Businesses
need to decide the appropriate level of process standardization
that allows their operators to work as efficiently as possible
while remaining flexible enough to satisfy customer demand. The
goal of this research is to analyze the standardization of the
least efficient process in an outbound order fulfillment system at
Amazon.com. Various tests were performed during a six-month
internship at Amazon's Lexington, KY facility to determine if this
process could benefit from standardization. The testing showed that
Amazon's processes must maintain a high level of flexibility to
satisfy the variations in customer demand and the diverse mix of
products that they ship. This research ends with a proposed process
improvement that will improve the efficiency of the baseline
scenario while providing flexibility to handle variation in order
flow. During the internship, the per-order cycle time at the
packing operation has been reduced by 9.7% and another improvement
was tested which reduced cycle times by 10.9% when implemented.
When the final improvement is implemented the total cycle time
reduction will be 20.6%.