in the feasibility phase. The purpose of the feasibility stage is to quantify the potential to implement
a solution; the purpose of the due diligence phase,
by contrast, is to explore the qualitative aspects
of implementing a solution. For example, if we
determined that express airfreight costs had risen
substantially year-over-year, we would now engage
relevant stakeholders in a root-cause analysis and
seek remedies. This is also where you would evaluate
the future impacts of the project as modeled and test
your original assumptions. In short, you want to
quantify and qualify the performance gap, and then
either build additional credibility for the hypothesis
or disprove it using the information you uncover. If
the due diligence phase turns up information that
disproves the hypothesis’s feasibility, then the project should be terminated. For that reason, another
“go/no go” decision point occurs after this phase.
DETAILED DESIGN
The work completed in this phase is directly related
to the project’s scope and the complexity of the
activity being analyzed. Its aim is to identify the
optimal model after evaluating several alternatives.
If airfreight costs can indeed be reduced by 15 per-
cent, what are some ways to accomplish this, and
what would be the impact of each alternative on
service levels?
Now that the project process has determined
that the future state is feasible and you have done
the extensive analysis required in the due diligence
phase, you can more fully understand potential
tradeoffs. This is where the term “optimal” comes
into play. “Optimal” means nothing without con-
text. Is the cheapest model the optimal one? Is it
the one with the lowest inventory, or the one with
the shortest lead times? Understanding the project’s
goal and the strategy behind it brings the notion of
tradeoffs into clear focus. If the analysis was thor-
ough, weighing the pros and cons of each candidate
scenario becomes a straightforward exercise. Making
the final decision about which one to adopt may not
be easy, but it will at least be an informed, risk-ad-
justed decision that relies on facts. Naturally, an
initial implementation plan with resource require-
ments and timing is also created at this point.
GO/NO GO DECISION POINT
IN-SOURCE OR OUTSOURCE MANAGEMENT OF THE NEW MODEL?
PROJECT
HYPOTHESIS
; Assess current state
; Articulate desired state
; Quantify anticipated
benefits
; Assess resource
availability
; Evaluate known
constraints
FEASIBILITY
; Initial baseline analysis
; Build model, as needed
; Test hypothesis against
constraints
; Validate hypothesis
DUE DILIGENCE
; Gather historical supply
chain data
; Model network baseline
; Map existing processes
; List interdependencies
; Evaluate future impacts
; Test original assumptions
IMPLEMENT
; Develop phasing/timing
; Build information
technology interfaces
; Implement changes to
logistics network
; Establish metrics and
data sources
; Train people involved
INSTITUTIONALIZE
; Write operating
procedures
; Integrate new model
into cross-functional
workflow
; Establish permanent
tasks
; Put audits and controls
in place
CLOSE
; Document key learnings
; Define reusable content
; Dissolve project team
DETAILED DESIGN
; Create optimized
network model
; Design process changes
; Measure benefits and
tradeoffs
; Estimate resources and
timing
; Develop implementation
plan
Supply Chain
Diagnostic Output
LONG LEAD TIME?
HIGH COST?
EXCESSIVE INVENTORY?
SOURCE: EXPEDITORS
[FIGURE 2] SUPPLY CHAIN PROJECT LIFECYCLE METHODOLOGY
