macc supply chain
TRANSCRIPT
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Supply Chain Management
Macc. Business Core
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Forecast Demand
Produce to forecast
Ship
Ship
Buffer betweenproduction anddemand variation
Ship
Ship
Change requirement
Change due date Forecast error
Produce to forecast Produce to order with lead time
Supplier
Factory
Warehouse
SellingEntity
Customer
Distributor
Typical Supply Chain
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SUPPLIER FACTORY WAREHOUSE SELLINGENTITY
CUSTOMER
RATE-BASED PLANNING
Distributor
Lean Enterprise
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Objective of Rate-Based
Management Balance demand variation against
production, supply, and transportation
responsiveness
Create product flow across the supply chain
by producing and moving the product at a
steady rate at all stages in the supply chain.
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Benefits of Improved Forecasts for
the Supply Chain
Supply Planning Reduced Safety Stock Requirements
Stability of Plan (week to week, month to month)
Procurement Reduced material costs due to elimination of short-term
fluctuations
Reduces impact of long lead time items
Manufacturing Plant efficiencies
Reduces lost output due to last minute schedule changes
Logistics Cost of expedited transportation/deployment
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Rate-Based vs. ConventionalRate-Based Planning and
ExecutionConventional Planning and
Execution
1. Capacity accommodatesdemand variation
Inventory accommodates demandvariation
2. Forecast used for planning Forecast used for execution(build ahead)
3. Rates are established for end
items and component parts.Build to rate.
No rates are established for end
items or parts. Build tomanufacturing orders
4. Rates are broadcastthroughout supply chain
Orders used to communicaterequirements sequentiallythroughout the supply chain
5. Demand variation is critical todetermining capacity bounds
Demand variation unknown
6. Flexible capacity boundariesare planned as a function of leadtime
Flexible capacity boundaries arenot established
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Issues to be Addressed
How to level schedules in the face of variation in
product demand
How to balance demand variation with production,supply, and transportation resources.
How to communicate production requirements to
all key suppliers and transportation providers so
that all parties operate assets efficiently.
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How to Reduce Demand
Variation Reduce Promotional Activity
Reduce Set Up Times
Produce in Small Lots
Postponement Strategies
Variation Aggregation
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Demand Variation Analysis
The demand pattern for Neon, Inc. flashlights is basically level (non-seasonal)
with only a 5% annual growth rate.
1. Demand variation as seen by distributor/dealer.
Actual Demand Data (Last 26 Weeks) by Channel
Model Average Std. Deviation
Distributor #1
Green 20.52 1.94
Yellow 10.65 3.64
Red 15.10 1.62
Dealer Network #2Green 15.63 1.82
Yellow 5.99 3.42
Red 9.85 1.50
Distributor #3
Green 15.84 1.62
Yellow 5.64 3.85
Red 5.00 1.75
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Standard Deviation
Standard Deviation (): a measure of the magnitude of variation around an
average value.
Xi individual measurements of a population of measurements
(e.g., weekly demand data).
=
X = average value for a population of measurements.
standard
deviation=
(Xi - X)
n
n
i =1
2
X
5
46
3
4
22
X22
5= = 4.4
standard
deviation=
(5-4.4)2 + (4-4.4)2 + (6-4.4)2 + (3-4.4)2 + (4-4.4)2
5
0.36 + 0.16 + 2.56 + 1.96 + 0.16
5= 1.04= = 1.02
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Standard Deviation (Cont.)If we assume the following:
1. Weekly demand data is stable over time (in control).
2. Weekly demand data forms a normal distribution.
X
1
68.26%
2
95.44%
3
99.73%
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Combining Demand Across Customers, Products and
Locations
In developing an inventory strategy it is necessary tounderstand variation of demand and of combined demands.
For example:
How much end item safety stock is required asprotection against variation in demand? How muchcould the inventory be reduced if components wereinventoried instead?
How much flex capacity would be needed to achievemake-to -order capability?
How much could the inventory be reduced byincreasing commonality of components.
What would be the impact of moving the inventorystored at regional distribution centers to the factorywarehouse?
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Demand Variation Analysis2. Demand variation as seen at the factory warehouse.
Red 29.95 28.8%
Yellow 22.28 21.3% 6.31 28.42 56.85 85.27
Green 51.99 49.9% 3.11 5.98 11.96 17.95
Model Average % Mix Std. Dev. 1 Std Dev 2 Std Dev 3 Std Dev
Actual Demand Variation by Model
(Last 10 Weeks)
Variation as a Percent of
Demand
NOTE: Average Green Model = Dist. #1 + Dealer Network #2 + Dist. #3
= 20.52 + 15.63 + 15.84 = 51.99
STD Deviation Green Model = (Std Dev #1)2 + (Std Dev #2)2 + (Std Dev #3)2
= (1.94) 2 + (1.62) 2 + (1.82) 2 = 3.11* Complete the above table
for the red model.
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Demand Variation
We will use this information to:
Construct planning bills of materials.
Support demand funneling strategies.
Support safety stock strategies.
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Example Implications
The range of variation in demand for each of 100 individual items might be 50%, while the range of variation for the aggregate demand might be 5%.The former would determine inventory requirements in a make to stockenvironment. The later would determine inventory requirements in a configure
to order environment. Variation of demand common components, as a percentage of the average
demand, much smaller than the variation for individual end items.
The demand for an item at one warehouse location has a standard deviation of3. At a second warehouse the same item has a standard deviation of 4. If thedemand for the two warehouse were combined the standard deviation would
be . Thus in the first case the safety stock required for three standarddeviation protection would be 3*3+3*4= 21. In the second case therequired safety stock is reduced to 3*5=15.
The demand for end items varies 100%. Thus in a make to inventoryenvironment a high level of safety stock is required. The aggregate demandmay vary only 10%, indicative of the amount of flex capacity needed in amake to order environment.
54322
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Learning about Demand
Variation In order to establish rates, it is necessary to
know the underlying demand for various
commodities and products.
The orders you receive may not reflect
actual underlying demand. Why?
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DEMAND PLANNING &
PRODUCT TYPES
BTS
PlanningLevel
PlanningLevel
Components
End Items
Components
CTO
Components
Modules
End Items
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PRODUCT TYPES
PRODUCT TYPE DEFINITION EXAMPLE
Build-to-Stock
(BTS)
Built prior to demand
with a standard bill of
material.
Diet Coke
Build-to-Order
(BTO)
Built to demand
requirements withstandard Bill of Material.
Executive Jet
Configure-to-Order
(CTO)
Built to demand with
standard modules or
components. Higher
product variation than
BTO.
Desk-top Computer
Engineer to Order
(ETO)
Built from drawings.
Unique end products.
Custom valve to a
space station
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Rate Based SchedulingWeekly Schedule Flexibility
Full Schedule
MPS
Wk1 Wk2 Wk3
vs.
Plan
Wk1 Wk2 Wk3
CTO
Specials
BTO
CTO BTO
ETOETO ETO
Hold
for BTOsCTO
Specials Ds
At-Once
Wk4
New
Orders
New
New
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Customer Demand Profile
Lead Time
At-Once Order
< lead-time
Dema
nd
Order outside
of lead-time
BTS-FG Kanban
BTO/CTO
BTO
ETO
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Product Response Profiles-
Different Perspectives
Product Response
Profile
| | | | |0 1 2 3 4 . . . . wks
| | | | |0 1 2 3 4 . . . . wks
InfiniteFlexibility
Market
| | | | | |0 1 2 3 4 5 . . . . wks
No Changes -Level Load
Plant
| | | | | | |0 1 2 3 4 5 6 . . . . wks
Some MoreFlexibleThan OthersSupplier ?
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Supply Response Profiles
A firms flexibility is limited by supplier capabilities.
The objective is to increase flexibility.
RAMP UP... .
RAMP DOWN....
Time
QUANTITY
TODAY FUTURE
Each supplier will have its own
response profile. The responseprofile is NOT only leadtime. It is
the ability to flex up or down for
subsequent periods into the future.
The objective is to drive the
suppliers to achieve response
profiles that allow us to meet ourcustomers' demands/needs.
Suppliers can achieve the desired
response profile either by stocking
material or having flexible internal
capacities.
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ConventionalSpecific Tail
NumberI-C
Sheet MetalShop
Composites
Parts
Ocean
48-WeekCycle
Parts committed totail numbers
months before use
SaltTreat
ASEA
HPM
StretchForm
MRP
MRP
MRP
MRP
MRP
MRP
Schedule
MR
MaterialsRelease
MetalBond
S
MR
PI-H
I-G
I-F
I-F I-F I-F I-F
I-E I-E I-E I-E
I-E
I-D
I-C
I-CI-D
MR
MRP
Missing!
48-WkSchedule
S
S
I-B Wings
I-E I-D
LEAN Fi l A blTakt
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LEAN
Schedule
Final Assembly
Salt
Treat
ASEA
HPM
Stretch
Form
Press Area
Supermarket
Thru - Kanban
Kanban
Board
Flat Pattern Parts
SheetStock
Wings
TaktNose Middle Tail
MetalBondWing
Cell