Syllabus
•
•
•
•
•
•
•
•
•
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Class 1 (Jan 5): chap 1; chap 2, case study
Class 2: (Jan 12) No Class
Class 3: (Jan 19) Chap 6, Chap 8
Class 4: (Jan 26) chap 10, chap 11, Chap 17(Take home exam)
Class 5: (Feb 2) Chap 5, Chap 7
Class 6: (Feb 9) Chap 9, Chap 12, 14
Class 7: (Feb 16) Chap 15, Reverse Logistics – need “The Forklifts
Have Nothing To Do!” Available in the Lewis and Clark Bookstore
Class 8: (Feb 23) Cabela’s Tour
Class 9: (Mar 2) Chap 13; Chap 16, Chap 4 (take home exam)
Other requirements:
→visit Harley-Davidson Plant in Kansas City to see operations
management in practice and write a 3-5 page paper comparing the
class slides and readings to the Harley operations
→ Home Work
Supply Chain
Management
Supply Chain
Management
• First appearance – Financial Times
• Importance → Inventory ~ 14% of GDP
→ GDP ~ $12 trillion
→ Warehousing/Trans ~ 9% of GDP
→ Rule of Thumb - $12 increase in sales to = $1 savings in
Supply Chain
• 1982 Peter Drucker – last frontier
• Supply Chain problems can cause ≤ 11% drop in stock
price
• Customer perception of company
SCOR
Reference: www.supply-chain.org
Supply Chain
 All activities associated with the flow
and transformation of goods and
services from raw materials to the end
user, the customer
 A sequence of business activities
from suppliers through customers
that provide the products, services,
and information to achieve customer
satisfaction
Supply Chain
“The global network used to deliver
products and services from raw
materials to end customers through
an engineered flow of information,
physical distribution, and cash.”
APICS Dictionary, 10th ed.
Supply Chain Management
 Synchronization of activities
required to achieve maximum
competitive benefits
 Coordination, cooperation, and
communication
 Rapid flow of information
 Vertical integration
Supply Chain Uncertainty
 Forecasting, lead times, batch
ordering, price fluctuations, and
inflated orders contribute to
variability
 Inventory is a form of insurance
 Distorted information is one of
the main causes of uncertainty
Bullwhip effect
Information in the
Supply Chain
 Centralized coordination of
information flows
 Integration of transportation,
distribution, ordering, and production
 Direct access to domestic and global
transportation and distribution
channels
 Locating and tracking the movement
of every item in the supply chain RFID
Information in the
Supply Chain
 Consolidation of purchasing from all
suppliers
 Intercompany and intracompany
information access
 Electronic Data Interchange
 Data acquisition at the point of origin
and point of sale
 Instantaneous updating of inventory
levels
 Visibility
Electronic Business
In Theory:
 Replacement of physical processes
with electronic ones
 Cost and price reductions
 Reduction or elimination of
intermediaries
 Shortening transaction times for
ordering and delivery
 Wider presence and increased visibility
Electronic Business
 Greater choices and more information for
customers
 Improved service
 Collection and analysis of customer data
and preferences
 Virtual companies with lower prices
 Leveling the playing field for smaller
companies
 Gain global access to markets & customers
Electronic Data Interchange
 Computer-to-computer exchange of
business documents in a standard
format
 Quick access, better customer service,
less paperwork, better communication,
increased productivity, improved
tracing and expediting, improves billing
and cost efficiency
Bar Codes
 Computer readable codes attached to
items flowing through the supply chain
 Generates point-of-sale data which is
useful for determining sales trends,
ordering, production scheduling, and
deliver plans
1234
5678
IT Issues
 Increased benefits and sophistication
come with increased costs
 Efficient web sites do not necessarily
mean the rest of the supply chain will
be as efficient
 Security problems are very real –
camera phones, cell phones, thumb
drives
 Collaboration and trust are important
elements that may be new to business
relationships
Suppliers
 Purchased materials account for about
half of manufacturing costs
 Materials, parts, and service must be
delivered on time, of high quality, and
low cost
 Suppliers should be integrated into
their customers’ supply chains
 Partnerships should be established
 On-demand delivery (JIT) is a frequent
requirement - what is JIT and does it
work?
Sourcing
 Relationship between customers and
suppliers focuses on collaboration and
cooperation
 Outsourcing has become a long-term
strategic decision
 Organizations focus on core
competencies
How does
 Single-sourcing is
single source
increasingly a part
differ from sole
of supplier relations
source?
Distribution
 The actual movement of products
and materials between locations
 Handling of materials and products at
receiving docks, storing products,
packaging, and shipping
 Often called logistics
 Driving force today
is speed
 Particularly important
for Internet dot-coms
Distribution Centers
and Warehousing
 DCs are some of the largest business
facilities in the United States
 Trend is for more frequent orders in
smaller quantities
 Flow-through facilities and automated
material handling
 Final assembly and product
configuration (postponement) may
be done at the DC
Warehouse Management
Systems
 Highly automated systems
 A good system will control item
slotting, pick lists, packing, and
shipping
 Most newer systems include
transportation management (load
management/configuration), order
management, yard management, labor
management, warehouse optimization
Vendor-Managed Inventory
 Not a new concept – same process used by
bread deliveries to stores for decades
 Reduces need for warehousing
 Increased speed, reduced errors, and
improved service
 Onus is on the supplier to keep the shelves
full or assembly lines running
 variation of JIT
 Proctor&Gamble - Wal-Mart
 DLA – moving from a manager of supplies to
a manager of suppliers
 Direct Vendor Deliveries – loss of visibility
Collaborative Distribution
and Outsourcing
 Collaborative planning, forecasting, and
replenishment (CPFR) started by Nabisco
 Allows suppliers to know what is really needed
and when
 Electronic-based exchange of data and
information
 Significant decrease in inventory levels and
more efficient logistics - maybe not!
 Companies work together for benefit of all of
the supply chain
Transportation
 Common methods are railroads,
trucking, water, air, intermodal,
package carriers, and pipelines
Railroads
 150,000 miles in US
 Low cost, high-volume
 Improving flexibility
 intermodal service
 double stacking
Complaints: slow, inflexible, large loads
Advantages: large/bulky loads, intermodal
Award-Winning Service
Recognition
Wal-Mart Stores, Inc.
Carrier of the Year – 5 years in a row
Target
Only rail carrier to receive
the Vice President’s Award
Federal Express
United Parcel Service
99.5% failure free, damage free
and on-time rating from United
Parcel Service every year since
1995
American Honda Motor Company
Premier Partner – 4 consecutive years
Only rail carrier to receive outstanding
supplier award - 2 years in a row
Toyota’s North American Parts
and Logistics Division (NAPLD)
Rail Carrier of the Year –
3 consecutive years
Schneider
KIA
Carrier of the Year – 3 consecutive years
Carrier of the Year
Trucking
 Most used mode in US -75% of total
freight (not total weight)
 Flexible, small loads
 Consolidation,
Internet load match sites
 Single sourcing reduces number of
trucking firms serving a company
 Truck load (TL) vs. Less Than Truck
Load (LTL)
Air
 Rapidly growing segment of
transportation industry
 Lightweight, small items
 Quick, reliable, expensive
(relatively expensive depending on
costs of not getting item there)
 Major airlines and US Postal
Service, UPS, FedEx, DHL
Package Carriers
 FedEx, UPS, US Postal Service, DHL
 Significant growth driven by
e-businesses and the move to smaller
shipments and consumer desire to have it
NOW
 Use several modes
of transportation
 Expensive - relative!!
 Fast and reliable - relative!!
 Innovative use of technologies in some
cases
 Online tracking – some better than others
Intermodal
 Combination of several modes of
transportation
 Most common are truck/rail/truck
and truck/water/rail/truck
 Enabled by the use of containers –
the development of the 20 and 40
foot containers significantly
changed the face of shipping
 ~2% of all US cargo via intermodal
Water
 One of oldest means of transport
 Low-cost, high-volume, slow
(relative)
 Security - sheer volume - millions of
containers annually
 Bulky, heavy and/or large items
 Standardized shipping containers
improve service
 The most common form of
international shipping
Pipelines
 Primarily for oil & refined oil
products
 Slurry lines carry coal or kaolin
 High initial capital investment
 Low operating costs
 Can cross difficult terrain
Global Supply Chain
 Free trade & global opportunities
 Nations form trading groups
 No tariffs or duties
 Freely transport
goods across borders
 Security!!
Global Supply Chain
Problems
 National and regional differences
 Customs, business practices, and
regulations
 Foreign markets are
not homogeneous
 Quality can be a
major issue
Security
• ~ 10+ million containers annually
• Customs-Trade Partnership Against Terrorism (CTPAT)
• Port Security – SAFE Ports Act; Scanning of all
Containers
• Cost - $2 billion closing of major port
• 66% of all goods into US comes through 20 major
ports
• 44% through LA/Long Beach
• Cost of attack on major port estimated at $20
Billion
Chapter 11
Forecasting
Forecasting Survey
• How far into the future do you
typically project when trying to
forecast the health of your industry?
 less than 4 months 3%
 4-6 months
12%
 7-12 months
28%
 > 12 months
57%
Fortune Council survey, Nov 2005
Indices to forecast health
of industry
•
•
•
•
•
•
•
•
•
Consumer price index
51%
Consumer Confidence index 44%
Durable goods orders
20%
Gross Domestic Product
35%
Manufacturing and trade inventories
and sales
27%
Price of oil/barrel
34%
Strength of US $
46%
Unemployment rate
53%
Interest rates/fed funds
59%
Fortune Council survey, Nov 2005
Forecasting Importance
• Improving customer demand forecasting
and sharing the information downstream
will allow more efficient scheduling and
inventory management
• Boeing, 1997: $2.6 billion write down due
to “raw material shortages, internal and
supplier parts shortages” Wall Street
Journal, Oct 23, 1987
Forecasting Importance
• “Second Quarter sales at US Surgical
Corporation decline 25%, resulting in a
$22 mil loss…attributed to larger than
anticipated inventories on shelves of
hospitals.” US Surgical Quarterly, Jul 1993
• “IBM sells out new Aetna PC; shortage
may cost millions in potential revenue.”
Wall Street Journal, Oct 7, 1994
Principles of Forecasting
• Forecasts are usually wrong
• every forecast should include an
estimate of error
• Forecasts are more accurate for
families or groups
• Forecasts are more accurate for
nearer periods.
Important Factors to
Improve Forecasting
• Record Data in the same terms as
needed in the forecast – production
data for production forecasts; time
periods
• Record circumstances related to the
data
• Record the demand separately for
different customer groups
Forecast Techniques
• Extrinsic Techniques – projections
based on indicators that relate to
products – examples
• Intrinsic – historical data used to
forecast (most common)
Forecasting
• Forecasting errors can increase the total
cost of ownership for a product
- inventory carrying costs
- obsolete inventory
- lack of sufficient inventory
- quality of products due to accepting
marginal products to prevent
stockout
Forecasting
• Essential for smooth operations of
business organizations
• Estimates of the occurrence, timing,
or magnitude of uncertain future
events
• Costs of forecasting: excess labor;
excess materials; expediting costs;
lost revenues
Forecasting
 Predicting future events
 Usually demand behavior
over a time frame
 Qualitative methods
 Based on subjective methods
 Quantitative methods
 Based on mathematical formulas
Impact of Just-in-Time
on Forecasting
• Just in time as a inventory method
• Just in time as a Continuous process
improvement program
• Just in time - one on the shelf
• Usage factors
• Single order vs. Case order
Strategic Role of
Forecasting
 Focus on supply chain management
 Short term role of product demand
 Long term role of new products,
processes, and technologies
 Focus on Total Quality Management
 Satisfy customer demand
 Uninterrupted product flow with no
defective items
 Necessary for strategic planning
Strategic Role of
Forecasting
 Focus on supply chain management
 Short term role of product demand
 Long term role of new products,
processes, and technologies
 Focus on Total Quality Management
 Satisfy customer demand
 Uninterrupted product flow with no
defective items
 Necessary for strategic planning
Total Quality Management
• Management approach to long term
success through customer
satisfaction
• Total Quality Control - process of
creating and producing quality
goods and services that meet the
expectations of the customer
• quality - conformance to
requirements or fitness for use
Trumpet of Doom
• As forecast horizon increases, so does the
forecasting error (i.e., accuracy
decreases) – shorten horizon by
shortening of cycles or flow times
• Law of Large Numbers – as volume
increases, relative variability decreases –
forecasting error is smaller: goal –
forecast at aggregate levels; collaborate;
standardize parts
• Volume and activity increase at end of
reporting periods – Krispy Kreme
Components of
Forecasting Demand
 Time Frame
 Short-range, mediumrange, long-range
 Demand Behavior
 Trends, cycles, seasonal
patterns, random
Time Frame
 Short-range to medium-range
 Daily, weekly monthly forecasts of
sales data
 Up to 2 years into the future
 Long-range
 Strategic planning of goals, products,
markets
 Planning beyond 2 years into the future
Demand Behavior
 Trend
 gradual, long-term up or down
movement
 Cycle
 up & down movement repeating over
long time frame
 Seasonal pattern
 periodic oscillation in demand which
repeats
 Random movements follow no pattern
Demand
Demand
Forms of Forecast Movement
Random
movement
Demand
Time
(c) Seasonal pattern
Figure 8.1
Time
(b) Cycle
Demand
Time
(a) Trend
Time
(d) Trend with seasonal pattern
Forecasting Methods
 Time series
 Regression or causal modeling
 Qualitative methods
 Management judgment, expertise, opinion
 Use management, marketing, purchasing,
engineering
 Delphi method
 Solicit forecasts from experts
Time Series Methods
 Statistical methods using historical
data
 Moving average
 Exponential smoothing
 Linear trend line
 Assume patterns will repeat
 Naive forecasts
 Forecast = data from last period
Moving Average
 Average several periods of data
 Dampen, smooth out changes
 Use when demand is stable with no
trend or seasonal pattern
 stock market analysis - trend
analysis
Moving Average
 Average several
periods of data
Sum of Demand
 Dampen, smooth out
In n Periods
changes
n
 Use when demand is
stable with no trend
or seasonal pattern
Simple Moving Average
MONTH
Jan
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Example 8.1
ORDERS
PER MONTH
120
90
100
75
110
50
75
130
110
90
Simple Moving Average
MONTH
Jan
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Example 8.1
ORDERS
PER MONTH
120
90
100
75
110
50
75
130
110
90
Daug+Dsep+Doct
MAnov =
3
90 + 110 + 130
=
3
= 110 orders for Nov
Simple Moving Average
MONTH
Jan
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Nov
Example 8.1
ORDERS
PER MONTH
120
90
100
75
110
50
75
130
110
90
–
THREE-MONTH
MOVING AVERAGE
–
–
–
103.3
88.3
95.0
78.3
78.3
85.0
105.0
110.0
Simple Moving Average
MONTH
Jan
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Nov
Example 8.1
ORDERS
PER MONTH
120
90
100
75
110
50
75
130
110
90
–
THREE-MONTH
MOVING AVERAGE
–
–
–
103.3
88.3
95.0
78.3
78.3
85.0
105.0
110.0
5
Di

i=1
MA5 =
=
5
90 + 110 + 130 + 75 + 50
5
= 91 orders for Nov
Simple Moving Average
MONTH
Jan
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Nov
Example 8.1
ORDERS
PER MONTH
120
90
100
75
110
50
75
130
110
90
–
THREE-MONTH
MOVING AVERAGE
–
–
–
103.3
88.3
95.0
78.3
78.3
85.0
105.0
110.0
FIVE-MONTH
MOVING AVERAGE
–
–
–
–
–
99.0
85.0
82.0
88.0
95.0
91.0
Smoothing Effects
150 –
125 –
Orders
100 –
75 –
50 –
25 –
0–
|
Jan
|
Feb
|
Mar
|
|
Apr May
|
|
June July
Month
Figure 8.2
|
|
Aug Sept
|
Oct
|
Nov
Smoothing Effects
150 –
125 –
Orders
100 –
75 –
50 –
Actual
25 –
0–
|
Jan
|
Feb
|
Mar
|
|
Apr May
|
|
June July
Month
Figure 8.2
|
|
Aug Sept
|
Oct
|
Nov
Smoothing Effects
150 –
125 –
Orders
100 –
75 –
50 –
3-month
Actual
25 –
0–
|
Jan
|
Feb
|
Mar
|
|
Apr May
|
|
June July
Month
Figure 8.2
|
|
Aug Sept
|
Oct
|
Nov
Smoothing Effects
150 –
5-month
125 –
Orders
100 –
75 –
50 –
3-month
Actual
25 –
0–
|
Jan
|
Feb
|
Mar
|
|
Apr May
|
|
June July
Month
Figure 8.2
|
|
Aug Sept
|
Oct
|
Nov
Weighted Moving Average
 Adjusts moving average
method to more closely
reflect data fluctuations
Weighted Moving Average
WMAn =  Wi Di
 Adjusts
i=1
moving
where
average
Wi = the weight for period i,
method to
between 0 and 100
more closely
percent
reflect data
fluctuations
 W = 1.00
i
Weighted Moving
Average Example
MONTH
August
September
October
Example 8.2
WEIGHT
DATA
17%
33%
50%
130
110
90
Weighted Moving
Average Example
MONTH
August
September
October
WEIGHT
DATA
17%
33%
50%
130
110
90
3
November forecast WMA3 =
Wi Di

i=1
= (0.50)(90) + (0.33)(110) + (0.17)(130)
= 103.4 orders
3 Month = 110
5 month = 91
Linear Trend Line
y = a + bx
where
a
b
x
y
=
=
=
=
intercept (at period 0)
slope of the line
the time period
forecast for demand for period x
Seasonal Adjustments
 Repetitive increase/
decrease in demand
 Use seasonal factor
to adjust forecast
Seasonal Adjustments
 Repetitive increase/
decrease in demand
 Use seasonal factor
to adjust forecast
Di
Seasonal factor = Si =
D
= demand for period/sum of demand
Seasonal Adjustment
YEAR
1999
2000
2001
Total
DEMAND (1000’S PER QUARTER)
1
2
3
4
Total
12.6
14.1
15.3
42.0
8.6
10.3
10.6
29.5
6.3
7.5
8.1
21.9
17.5
18.2
19.6
55.3
45.0
50.1
53.6
148.7
Seasonal Adjustment
YEAR
1999
2000
2001
Total
DEMAND (1000’S PER QUARTER)
1
2
3
4
Total
12.6
14.1
15.3
42.0
8.6
10.3
10.6
29.5
6.3
7.5
8.1
21.9
17.5
18.2
19.6
55.3
45.0
50.1
53.6
148.7
D1
42.0
S1 =
=
= 0.28
D 148.7
D3
21.9
S3 =
=
= 0.15
D 148.7
D2
29.5
S2 =
=
= 0.20
D 148.7
D4
55.3
S4 =
=
= 0.37
D 148.7
Seasonal Adjustment
YEAR
DEMAND (1000’S PER QUARTER)
1
2
3
4
Total
1999
2000
2001
Total
12.6
14.1
15.3
42.0
8.6
10.3
10.6
29.5
6.3
7.5
8.1
21.9
17.5
18.2
19.6
55.3
Si
0.28
0.20
0.15
0.37
45.0
50.1
53.6
148.7
Seasonal Adjustment
YEAR
DEMAND (1000’S PER QUARTER)
1
2
3
4
Total
1999
2000
2001
Total
12.6
14.1
15.3
42.0
8.6
10.3
10.6
29.5
6.3
7.5
8.1
21.9
17.5
18.2
19.6
55.3
Si
0.28
0.20
0.15
0.37
45.0
50.1
53.6
148.7
45
Forecast for 1st qtr 2002
50.1
50*.28
14
53.6
148.7
49.56667 Forecast for 2002 using simple 3 year moving ave
Forecast Accuracy
 Find a method which minimizes error
 Error = Actual - Forecast
 Mean Absolute
Deviation (MAD)
MAD Example
PERIOD
1
2
3
4
5
6
7
8
9
10
11
12
DEMAND, Dt
Ft ( =0.3)
37
40
41
37
45
50
43
47
56
52
55
54
37.00
37.00
37.90
38.83
38.28
40.29
43.20
43.14
44.30
47.81
49.06
50.84
557
Forecast Control
 Reasons for out-of-control forecasts
 Change in trend
 Appearance of cycle
 Weather changes
 Promotions
 Competition
 Politics
Tracking Signal
• Tracking Signal establishes control limits usually +/- 3 MAD
• The greater the tracking signal the more
the demand exceeds the forecast
• Sum(Demand-Forecast)/Mean Absolute
Deviation
• Sometimes called Running Sum of
Forecasting Error
Next Week
• Chap 9
• Chapter 14