Transcript BUSN 6110 CLASS 4 - supply chain research

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, 1987: $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
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
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
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
=
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
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
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
Exponential Smoothing
 Averaging method
 Weights most recent data more
strongly
 Reacts more to recent changes
 Widely used, accurate method
Exponential Smoothing
 Averaging method
 Weights most
recent data more
strongly
 Reacts more to
recent changes
 Widely used,
accurate method
Ft +1 = Dt + (1 - )Ft
where
Ft +1 = forecast for next
period
Dt = actual demand for
present period
Ft = previously
determined forecast
for present period
= weighting factor,
smoothing constant
Forecast for Next Period
• Forecast = (weighting factor)x(actual
demand for period)+(1-weighting
factor)x(previously determined
forecast for present period)
0 >  <= 1
Lesser
reaction
to recent demand
Greater
reaction
to recent demand
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
2008
2009
2010
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
2008
2009
2010
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
2008
2009
2010
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
2008
2009
2010
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 2011
50.1
50*.28
14
53.6
148.7
49.56667 Forecast for 2011 using simple 3 year moving ave
Forecast Accuracy
 Find a method which minimizes error
 Error = Actual - Forecast
Forecast Control
 Reasons for out-of-control forecasts
 Change in trend
 Appearance of cycle
 Weather changes
 Promotions
 Competition
 Politics
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
End-to-End Supply
Chain
Plan
Plan
Deliver
Source
Return
Return
Suppliers’
Supplier
Make
Deliver
Return
Supplier
Source
Make
Return
Deliver
Plan
Source
Return
Your Company
Internal or External
Return
Make
Deliver
Source
Return
Return
Customer
Internal or External
Customers’
Customer
SCOR reference model
•
Whether from Cow to Cone or from Rock to Ring SCOR is not
limited by organizational boundaries
Copyright © Supply Chain Council, 2008. All rights reserved
45
4
End-to-End Supply
Chain
Components
Sourc
e
Make
Delive
r
Supplier’s Supplier
Sub assemblies
Sourc
e
Make
Supplier
Delive
r
Manufacturer
Sourc
e
Make
Delive
r
Retailer
Source
MP3 Company
Deliver
Customer
Consumer
Sourc
e
Customer’s Customer
Process, arrow indicates material flow direction
Copyright © Supply Chain Council, 2008. All rights reserved
46
4
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
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
 Data acquisition at the point of origin
and point of sale
 Instantaneous updating of inventory
levels
 Visibility
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
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 WMS 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
 Home Depot
Collaborative Distribution
and Outsourcing
 Collaborative planning, forecasting, and
replenishment (CPFR)
 Allows suppliers to know what is really needed
and when
 Electronic-based exchange of data and
information
 Europe’s ECR/QR
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
Trucking
 Most used mode in US -75% of total
freight (volume 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
 UPS, US Postal Service, FedEx Ground
 Significant growth driven by
e-businesses and the move to smaller
shipments and consumer desire to have it
NOW
 Use several modes of transportation
 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
Switching
Milk Cans
from a
Farmer’s
Buggy to a
Truck on a
Rural Road in
North
Carolina,
1929
Early form of intermodal transport and cross docking
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!!