Sc Physics 2 12 9 09 Webinar Final Web

Supply Chain Physics 2
The Very Real Decision Space of
Supply Chain Physics
December 9, 2009

Mark Gavoor
Direct: 630.242.0502
Toll Free: 866.865.2714 ext. 4
E-Mail: mgavoor@cadentresources.com
®
Web-Site: www.demandcaster.com
Copyright © 2009 Cadent Resources, Inc. All rights reserved. Not for distribution

Welcome

Part I: The Concept of Supply Chain Physics

Part II: December 9, 2009
The Very Real Decision Space of Supply
Physics

Part III: January 20, 2010 – 12 p.m. CST
Strategies for Communication &
Improvement

Copyright © 2009 Cadent Resources Group, LLC All rights reserved. Not for distribution

Agenda
Re-Cap from Part 1

Four Examples

Supply Chain Optimization

Two Categories of Violations

Conclusion


Why Supply Chain Physics?

Supply Chain Physics is a concept

Based on science, engineering, and
business

It is language and set of principles to foster
Accountabilities across functions
Improvement across the enterprise


Information Flow
Forecasting

Mfg Order
Purchasing Places
Planning Processing
Order

Order Taking
Manufacturing
& Fulfillment
Inventory
Warehouse
Suppliers Allocation Trade

Manufacturing Distribution

Material/Product flow

The Three Laws of SC Physics

1. Law of Interdependency

2. Law of Constraints

3. Law of Information



Inventory, Service, Quality, Costs are interdependent
In business improvement, silo-ed functional
improvement can only take you so far. All further
improvements require cross-functional efforts.






How much of any item can be produced in a finite
amount of time?
How far, fast, & in what quantities can goods be
shipped from Point A to Point B?
Yes … very related to the Theory of Constraints






Information moves at the speed of light, er… the
internet
Independent of accuracy of the information
Speed of information >> Lead times
Speed of information >> Production rates

Supply Chain Whack-a-Mole
• Quality
• Cost
• Service
• Inventory

Optimize all to a point
Then trade-off
optimization
Need structural
http://www.mmt-inst.com/End_of_management_whack_a_mole.html
change to optimize all
further

Three Examples
Cadent Resources is a company dedicated
to helping companies
Reduce Inventory
Improve Service
Generate Cash

So, let’s look at three Supply Chain Physics
examples in terms of inventory


Example I: Simple Inventory Model – Single SKU

Order Quantity

Re-Order
Point

Safety Stock


Simple Inventory Model – Single SKU

OQ

Re-Order
Point
Safety
Stock Due to Manufacturing and
Transit time Variation…



OQ

Re-Order
Point
Safety
Stock Due to Manufacturing LT and
Transit time Variations…
and Demand Volatility



OQ

Re-Order
Point Supply Chain
Safety LT & Variations
Stock

Demand Chain
Variations



We in the Supply Chain
are responsible for these
OQ parts?

Re-Order
Point Supply Chain
Stock

Demand Chain
Variations



Is the Supply Chain
responsible for this part?
OQ

Re-Order
Point Supply Chain
Stock

Demand Chain
Variations


You need to know this
breakdown for your company
We have seen LTs dominate
making it 80-20 & Demand
Volatility making it 20-80
OQ

Re-Order
Point Supply Chain
Stock

Demand Chain
Variations


We can actually assign an inventory
objective to Sales?

If we wanted to…


Example II: E&O Inventory
E&O
Excess & Obsolete Inventory

Some call it SLOB
Slow & Obsolete

These inventories are the result of both
Forecasting errors
Historical violations of the Laws of Supply
Chain Physics

You are tasked with reducing the E&O
which is 20% of all inventory.
(We have seen it as high as 60%!!)

Yet…
You are not allowed to write any of it off
And the goal is to sell it at full margin i.e. no
fire sales

This is a very real scenario

No one can has ever been able to explain
How this is tasked to the Supply Chain
Cannot sell it
Cannot dispose of it
Yet we have to reduce it????
We can
Stack it neatly
Dust it off now and again
Report on the value of it monthly


Example III: Good E&O Example
Not all examples are violations of Supply
Chain Physics
Strategy in all Subsidiaries of a global CPG
company
New GM comes in
Is shocked by the level of E&O
Disparages the old GM for letting this happen
Clears the decks: Fire Sale & Write-offs
Then rebuilds E&O to the same level until his
next promotion

Argentina Subsidiary
GM realized that this was not a Supply
Chain problem alone
Sales
Finance
Assigned:
An Inventory Czar
A Sales person focused only on E&O


Underselling or
Overproducing promotions
was the largest cause of E&O

10+% in Obsolete alone

Two pronged attack
Better promotion planning &
performance measures
Selling off the E&O


Better promotion planning & performance
measures
Tracked Demand Plan vs Actual by Account
Manufacturing to begin promotion month with
forecast volume in inventory ready to go
At mid-month checked Account Forecast vs.
Sales
This practice led to co-development of
Promotions Management Module with ERP
provider

Marketing folks are paid to
Look forward
Come up with new news
Old promotions, failed products, is so…
yesterday

No rearview mirrors in
Marketing Cars


Selling off the E&O
Created a space in DC for Saleable E&O
Showroom
Old promotions considered in new promotions
planning
Sales person hosted sales managers monthly
Review offerings
Use E&O in trade promotions
Offer cases of E&O as the free goods in BOGOs
Finance needed to sign-off on promotions for
margin purposes

Example IV: Law of Constraints/Information

Aggregate Product Category
Demand always goes down year end
This year going up with big spikes



2008 Drop
Even larger because of economic downturn
Had to downsize inventory
2009 Increase
Due to coming out of recession?
Returning to pre-recession level of demand?
Within LT, cannot react fast enough
Seeing and hearing



Actual Sales and Demand Plans can be communicated at the speed of
the internet
Given our global Supply Chains, that is good
But we still have to move the camera from Point A to the store near
you and me



While Information was almost instantaneous
Lean is not JIT
Cannot react to demand spikes or changes
within LT



Different product category
Same issue


In one SKU, 2 big spikes within lead time
Overseas vendor
Vendor Stated lead time 75 days
Planned lead time 120 days
Actual lead time 133 days



120 Day LT 133 Day LT 75 Day LT No Spikes
Unit Cost $2.50 $2.50 $2.50 $2.50
Service Level 98% 98% 98% 98%
Projected Demand 100,754 104,291 83,512 90,606
Safety Stock 49,900 51,267 39,008 25,741
Target Inv. Level 150,654 155,558 122,520 116,347
Change 0 4904 -28134 -34307
% Change 0 3% -19% -23%
$ Impact $0.00 $12,260.00 -$70,335.00 -$85,767.50


Summary of Examples
We believe that Inventory and Service are
the final arbiter of Supply Chain
Performance
It is the indicator of a company’s
Operating Practices & Processes
Good & bad

Silo improvements only go so far
Cross-Functional effort is required when
the Interdependent Level is reached

Isn’t there a lot of Math in Physics???


When we VIOLATE THE LAWS
We compromise

Inventory
Service
Quality
Cost


We compromise

Inventory Cash, Profit
Service Customer Loyalty, Revenue
Quality Customer Loyalty, Profit
Cost Profit

We Compromise Performance!



Not Accounting for Realities of Compromise & Cause
Supply Chain Physics Trade-offs in Performance

• Manufacturing Lead Times
• Transit Times • Inventory
• Production rates • Service
• Production capacities • Quality
• Warehouse utilization • Cost
• Transportation equipment
availability
• Demand Volatility


It is a complex Multi-Criteria Problem
Optimize all i Cost i, Inventory i, Service i, Quality i

Subject to:
Manufacturing Lead Times > MLTij
Transit Times > TTijk
Production rates < PRij
Production capacities < PCij
Warehouse utilization < Wik
Transportation equipment availability < Eijk
Demand Volatility = σi

i = SKU number
j = Plant or Supplier (how many plants/suppliers?)
k = DC number


It is a Multi-Criteria Problem
Optimize Cost i, Inventory i, Service i, Quality i

Subject to:
Manufacturing Lead Times > MLTij
Transit Times > TTijk
Production rates < PRij
Production capacities < PCij
Warehouse utilization < Wik
Transportation equipment availability < Eijk
Demand Volatility = σi

i = SKU number
j = Plant or Supplier (how many plants/suppliers)
k = DC number


Multi-Criteria Optimization?
This is the Whack-a-Moley stuff

We can optimize in one dimension
When you have two or more dimensions, it
is more complicated
Are the criteria independent or dependent?


Multi-Criteria Optimization?
How is this done mathematically?
1. Prioritize and Optimize – one by one
2. Find the efficient set
3. Map the Criteria into one dimension
4. Change some of the criteria into
constraints


Money is a Good Unifying Dimension
Money is additive
My money, your
money becomes our
money
We add up revenues
and cost
We minimize costs in
the Supply Chain
We subtract costs
from revenues & try
to maximize profits

Make some of the Criteria Constraints
This is done in inventory management

We want to maximize Service & minimize
Inventory

They are different units of measure
Service is % Case or Unit Fill
Inventory is in units or dollars


Make some of the Criteria Constraints
Ideally: Want 100% Service but cannot
afford that level of inventory

So we prioritize using by ABC classification
of SKUs or items

We set minimum service target levels


Service: From Objective Criteria to
Constraint
SKU/Item Top Down of Minimum
Classification Sales or Margin Service Level
A 80% 99%

B 15% 97%

C 5% 95%


Segmentation
3 dimensional product segmentation
Set demand plan policy based on:
Importance
Order Frequency
Forecastability
H
Frequency

M

L
L M
H
A B C
Importance


Multi-Criteria Optimization
Hard to do as pure mathematics
Close to impossible to get all the equations
Things are constantly changing


The Supply Chain Physical World
Is a world of constant change
New Supply Sources
Material and Commodity Pricing
Competition
Economic factors
Technology
Make for a world of constant flux

Multi-Criteria
Hard to do as pure mathematics
Close to impossible to get all the equations
Things are constantly changing

So we use a combination of Math, Physics,
and Heuristics as we do with our
DemandCaster software tool


Two categories of VIOLATIONS

1. That which maybe can be done

2. Impossible to get there from here


Two categories of VIOLATIONS



• These are violations of the:
• Law of Constraints
• Law of Information


Two kinds of VIOLATIONS
Not necessarily impossible
But will require efforts of epic proportions
And will most likely have a Whack-a-Moley
effect on performance





Are you freaking kidding me?
How did you ever get into your position?
And remarkably you have kept the job




Are you freaking kidding me?
How did you ever get into your position?
And remarkably you have kept the job
On the inside




We calmly, clearly, and politely explain
Why no how, no way
We can get there from here



Why can we communicate #2 when we
have to?
But never communicate #1 with any
force?


In the Supply Chain
We are good corporate citizens
We are businessmen
We are paid to get things done & have a can
do attitude
That is why when thing are just “iffy” we
say we can do it.

We will explore these categories a bit more
in Supply Chain Physics 3.

Conclusion
Reviewed the concepts
Presented a mathematical optimization model
Concept
Strategies for Multi-Criteria Optimization
Looked at Five Examples

Set the stage for Supply Chain Physics 3


Thank You!
Please join us for the final part of Supply
Chain Physics

Part III: January 20, 2010 – 12 p.m. CST
Strategies for Communication &
Improvement


Software + Expertise
The Cadent Resources Group, LLC Difference

Your path to a smarter and healthier company
with lower costs and satisfied customers is only a
phone call away!


Contact Us

Schedule a complimentary
30 minute phone assessment

Toll Free: 866-865-2714

asurenian@cadentresources.com

mgavoor@cadentresources.com

www.demandcaster.com

Twitter: @DemandCaster


Sc Physics 2 12 9 09 Webinar Final Web

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