Page 59 - Design for Six Sigma for Service (Six SIGMA Operational Methods)

40 Chapter Two

2.3.4 Phase 4: Design

The goal of this phase is to develop a detailed service product design to
meet customer needs. The result of this phase is an optimized design with
all functional requirements released at the Six Sigma performance level. As
the concept design is finalized, there are still a lot of design parameters that
can be adjusted and changed. With the help of computer simulation, design
review, failure modes and effects analysis (FMEA), and some simple sta-
tistical analysis, the detailed design will be determined.

It is common that the detailed design on service products cannot be
completed without completion of the corresponding service process design
or redesign. Service process design (or redesign) can follow the DFSS
phases for service process that will be discussed in Sec. 2.4.

A good design should have the following properties:
• Superior performance
• High performance capability
• Robustness

Superior performance means the new design can achieve high performance
metrics. For example, in the restaurant service case, if we redesign the
ordering procedure, a good design would be one that has shorter ordering
times and fewer mistakes. If we redesign the kitchen workflow process, a
good design would be one that has shorter cooking times, better-tasting
food, and less waste in the kitchen.

High performance capability means the newly designed service can perform
consistently and has very few mistakes. For example, McDonald’s is famous
for its high consistency in worldwide operations; no matter where you go in
the world, you can expect that the same food item in one McDonald’s will
be cooked in the same way and will have a similar taste to that in another
McDonald’s and the kitchen productivity will be the same in both.

Robustness means that a newly designed service will perform consistently
for various operating conditions and various types of customers.

The following are some general design principles that can help in
developing service designs that have high capability and robustness
(Ramaswamy 1996):
• Selection of technologies with large capacities so that resources are not
stressed