Page 175 - Six Sigma Demystified

156 Six SigMa DemystifieD

(2) if the call arrival rate increased by 50 percent, the total order cycle
time increased by 68 percent.
(3) if both the order and call arrival rates increased by 50 percent, the
total order cycle time increased by over 600 percent, with 56 percent of
orders exceeding eight hours of total cycle time.
(4) These results indicate a process with little capacity to handle pro-
cess disruptions, such as increased volume.
c. The proposed change to remove the order processing person from the
call queue is estimated to reduce the total cycle time to less than 30 min-
utes, including 7 minutes of average wait time. all orders are completed
within 90 minutes; only 4 percent exceed 60 minutes. This aspect of the
proposed change likely would reduce customer order status inquiries and
improve the overall order processing efficiency but would not greatly re-
duce the actual order processing time (or cost).
d. Reducing the order processing time by 50 percent results in a 68 per-
cent reduction in total cycle time because average wait time is reduced to
5 minutes. all orders were processed in less than 100 minutes, with only 3
percent beyond 60 minutes.
(1) if the order processing person also was taken offline, the cycle time
was reduced by a total of 83 percent, with only 1 percent of orders’ cycle
times exceeding 30 minutes. This process performance was unchanged if
the order arrival rate increased by 50 percent
(2) if the order processor remained in the call queue and the incoming
call rate increased by 50 percent, the total cycle time was reduced by 58
percent from baseline.
5. The simulation results indicated substantial benefit in taking the order
processor offline as the order is processed. a secondary simulation to es-

timate the effect of taking the order processor offline on the call queue
also was performed.

Redefining operating conditions

To truly drive a sustained reduction in process variation, process improvements
must concentrate on controlling the underlying factors that predict future out-
comes. This helps to prevent problems before they occur. In the analyze stage,
process drivers were identified that contribute to process variation. In the im-