1. Supply Chain Management

2. 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

3. SCOR
Reference:

4. 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

5. 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.

6. Supply Chain Management
Synchronization of activities required to achieve maximum competitive benefits
Coordination, cooperation, and communication
Rapid flow of information
Vertical integration

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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?

16. Sourcing How does single source differ from sole source?
Relationship between customers and suppliers focuses on collaboration and cooperation
Outsourcing has become a long-term strategic decision
Organizations focus on core competencies
Single-sourcing is increasingly a part of supplier relations
How does
single source
differ from sole
source?

17. 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

18. 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

19. 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

20. 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

21. 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

22. Transportation
Common methods are railroads, trucking, water, air, intermodal, package carriers, and pipelines

23. 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

24. 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)

25. 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

26. 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

27. 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

28. 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

29. Pipelines Primarily for oil & refined oil products
Slurry lines carry coal or kaolin
High initial capital investment
Low operating costs
Can cross difficult terrain

30. Global Supply Chain Free trade & global opportunities
Nations form trading groups
No tariffs or duties
Freely transport goods across borders
Security!!

31. Global Supply Chain Problems
National and regional differences
Customs, business practices, and regulations
Foreign markets are not homogeneous
Quality can be a major issue

32. Security ~ 10+ million containers annually
Customs-Trade Partnership Against Terrorism (C-TPAT)
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

33. Forecasting

34. Fortune Council survey, Nov 2005
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

35. 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

36. 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

37. 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

38. 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.

39. 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

40. Forecast Techniques
Extrinsic Techniques – projections based on indicators that relate to products – examples
Intrinsic – historical data used to forecast (most common)

41. 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

42. 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

43. Forecasting Predicting future events
Usually demand behavior over a time frame
Qualitative methods
Based on subjective methods
Quantitative methods
Based on mathematical formulas

44. 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

45. 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

46. 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

47. 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

48. 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

49. Components of Forecasting Demand
Time Frame
Short-range, medium-range, long-range
Demand Behavior
Trends, cycles, seasonal patterns, random

50. Time Frame Short-range to medium-range Long-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

51. Demand Behavior Trend Cycle Seasonal pattern
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

52. Forms of Forecast Movement
Time
(a) Trend
(d) Trend with seasonal pattern
(c) Seasonal pattern
(b) Cycle
Demand
Random movement
Figure 8.1

53. Forecasting Methods Time series Qualitative methods Delphi method
Regression or causal modeling
Qualitative methods
Management judgment, expertise, opinion
Use management, marketing, purchasing, engineering
Delphi method
Solicit forecasts from experts

54. 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

55. 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

56. Moving Average Average several periods of data
Dampen, smooth out changes
Use when demand is stable with no trend or seasonal pattern
Sum of Demand
In n Periods n

57. Simple Moving Average ORDERS MONTH PER MONTH Jan 120 Feb 90 Mar 100
Apr 75
May 110
June 50
July 75
Aug 130
Sept 110
Oct 90
ORDERS
MONTH PER MONTH
Example 8.1

58. Simple Moving Average Daug+Dsep+Doct MAnov = 3 90 + 110 + 130 = 3
Jan 120
Feb 90
Mar 100
Apr 75
May 110
June 50
July 75
Aug 130
Sept 110
Oct 90
ORDERS
MONTH PER MONTH 3
Daug+Dsep+Doct
MAnov = = 3
= 110 orders for Nov
Example 8.1

59. Simple Moving Average ORDERS THREE-MONTH
Jan 120 –
Feb 90 –
Mar 100 –
Apr
May
June
July
Aug
Sept
Oct
Nov – 110.0
ORDERS THREE-MONTH
MONTH PER MONTH MOVING AVERAGE
Example 8.1

60. Simple Moving Average  Di MA5 = = 91 orders for Nov Jan 120 –
Feb 90 –
Mar 100 –
Apr
May
June
July
Aug
Sept
Oct
Nov – 110.0
ORDERS THREE-MONTH
MONTH PER MONTH MOVING AVERAGE
MA5 = 5
i = 1  Di = 5
= 91 orders for Nov
Example 8.1

61. Simple Moving Average ORDERS THREE-MONTH FIVE-MONTH
Jan 120 – –
Feb 90 – –
Mar 100 – –
Apr –
May –
June
July
Aug
Sept
Oct
Nov –
ORDERS THREE-MONTH FIVE-MONTH
MONTH PER MONTH MOVING AVERAGE MOVING AVERAGE
Example 8.1

62. Smoothing Effects 150 – 125 – 100 – 75 – 50 – 25 – 0 – Orders
| | | | | | | | | | |
Jan Feb Mar Apr May June July Aug Sept Oct Nov
Orders
Month
Figure 8.2

63. Smoothing Effects 150 – 125 – 100 – 75 – 50 – 25 – 0 – Orders Actual
| | | | | | | | | | |
Jan Feb Mar Apr May June July Aug Sept Oct Nov
Orders
Month
Actual
Figure 8.2

64. Smoothing Effects 150 – 125 – 100 – 75 – 50 – 25 – 0 – Orders 3-month
| | | | | | | | | | |
Jan Feb Mar Apr May June July Aug Sept Oct Nov
3-month
Actual
Orders
Month
Figure 8.2

65. Smoothing Effects 150 – 125 – 100 – 5-month 75 – 50 – 25 – 0 – Orders
| | | | | | | | | | |
Jan Feb Mar Apr May June July Aug Sept Oct Nov
5-month
3-month
Actual
Orders
Month
Figure 8.2

66. Weighted Moving Average
Adjusts moving average method to more closely reflect data fluctuations

67. Weighted Moving Average
WMAn =
i = 1 
Wi Di
where
Wi = the weight for period i, between 0 and 100 percent
 Wi = 1.00
Adjusts moving average method to more closely reflect data fluctuations

68. Weighted Moving Average Example
MONTH WEIGHT DATA
August 17% 130
September 33% 110
October 50% 90
Example 8.2

69. Weighted Moving Average Example
MONTH WEIGHT DATA
August 17% 130
September 33% 110
October 50% 90
November forecast
WMA3 = 3
i = 1 
Wi Di
= (0.50)(90) + (0.33)(110) + (0.17)(130)
= orders
3 Month = month = 91

70. Seasonal Adjustments Repetitive increase/ decrease in demand
Use seasonal factor to adjust forecast

71. Seasonal Adjustments Repetitive increase/ decrease in demand
Use seasonal factor to adjust forecast
Seasonal factor = Si = Di D
= demand for period/sum of demand

72. Seasonal Adjustment DEMAND (1000’S PER QUARTER) YEAR 1 2 3 4 Total
Total
DEMAND (1000’S PER QUARTER)
YEAR Total

73. Seasonal Adjustment S1 = = = 0.28 D1 D 42.0 148.7 S2 = = = 0.20 D2
Total
DEMAND (1000’S PER QUARTER)
YEAR Total
S1 = = = 0.28 D1 D
42.0
148.7
S2 = = = 0.20 D2
29.5
S4 = = = 0.37 D4
55.3
S3 = = = 0.15 D3
21.9

74. Seasonal Adjustment DEMAND (1000’S PER QUARTER) YEAR 1 2 3 4 Total
Total
DEMAND (1000’S PER QUARTER)
YEAR Total Si

75. Seasonal Adjustment Forecast for 1st qtr 2002
Total
DEMAND (1000’S PER QUARTER)
YEAR Total Si
Forecast for 1st qtr 2002
Forecast for 2002 using simple 3 year moving ave

76. Forecast Accuracy Find a method which minimizes error
Error = Actual - Forecast
Mean Absolute Deviation (MAD)

77. MAD Example PERIOD DEMAND, Dt Ft ( =0.3) 1 37 37.00 2 40 37.00
557
PERIOD DEMAND, Dt Ft ( =0.3)

78. Forecast Control Reasons for out-of-control forecasts Change in trend
Appearance of cycle
Weather changes
Promotions
Competition
Politics

79. 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

80. Forecasting Long Term – location, capacity, new product design
Short Term – production, inventory control, labor levels, cost controls
Questions?