MAcc Supply Chain

7/31/2019 MAcc Supply Chain

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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

MAcc Supply Chain

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