The Value of Information

1
The Value of Information

• Designing Managing the Supply Chain
• Chapter 4
• Byung-Hyun Ha
• bhha_at_pusan.ac.kr

2
Outline

• Barilla SpA
• Introduction
• The Bullwhip Effect
• Effective Forecast
• Information for the Coordination of Systems

3
Barilla SpA

• Introduction
• Barilla SpA is the worlds largest pasta
  manufacturer
• The company sells to a wide range of Italian
  retailers, primarily through third party
  distributors
• During the late 1980s, Barilla suffered
  increasing operational inefficiencies and cost
  penalties that resulted from large week-to-week
  variations in its distributors order patterns

4
Barilla SpA

• Distribution channels

5
Barilla SpA

• Weekly demand for Barilla dry products

6
Barilla SpA

• Demand fluctuations
• The extreme fluctuation is truly remarkable when
  one considers the underlying aggregate demand for
  pasta in Italy
• Causes of demand fluctuations
• Transportation discounts
• Volume discount
• Promotional activity
• No minimum or maximum order quantities
• Product proliferation
• Long order lead times
• Poor customer service rates
• Poor communication

7
Barilla SpA

• Impact of demand fluctuation
• Inefficient production or excess finished goods
  inventory
• Utilization of central distribution is low
• Workers
• Equipment
• Transportation costs are higher than necessary

8
Barilla SpA

• Just-in-Time Distribution (JITD) proposal
• Decision-making authority for determining
  shipments from Barilla to a distributor would
  transfer from the distributor to Barilla
• Rather than simply filling orders specified by
  the distributor, Barilla would monitor the flow
  of its product through the distributors
  warehouse, and then decide what to ship to the
  distributor and when to ship it
• Evaluation of the proposal
• JITD proposal as a mechanism for reducing these
  costs?
• Why should this work?
• How does it work?
• What makes Barilla think that it can do a better
  job of determining a good product/delivery
  sequence than its distributors?

9
Barilla SpA

• Resistance from the Distributors
• Managing stock is my job I dont need you to
  see my warehouse or my figures.
• I could improve my inventory and service level
  myself if you would deliver my orders more
  quickly I would place my order and you would
  deliver within 36 hours.
• We would be giving Barilla the power to push
  products into our warehouse just so that Barilla
  can reduce its costs.
• Resistance from Sales and Marketing
• Our sales levels would flatten if we put this
  program in place.
• How can we get the trade to push Barilla product
  to retailers if we dont offer some sort of
  incentive?
• If space is freed up in our distributors
  warehousesthe distributors would then push our
  competitors product more than ours.
• the distribution organization is not yet ready
  to handle such a sophisticated relationship.

10
Introduction

• Value of Information
• In modern supply chains, information replaces
  inventory
• Why is this true?
• Why is this false?
• Information is always better than no information
• Information
• Helps reduce variability
• Helps improve forecasts
• Enables coordination of systems and strategies
• Improves customer service
• Facilitates lead time reductions
• Enables firms to react more quickly to changing
  market conditions

11
Increasing Variability of Orders

• Lee, Padmanabhan, Wang (1997)

12
Bullwhip Effect

• Order variability is amplified up the supply
  chain upstream echelons face higher variability
• Main factors contributing to increase in
  variability
• Demand forecasting
• Lead time
• Promotional sales
• Forward buying
• Volume and transportation discounts
• Batching
• Inflated orders
• IBM Aptiva orders increased by 2-3 times when
  retailers thought that IBM would be out of stock
  over Christmas
• Motorola cell phones

13
Impact of Promotional Sales

• Order pattern of a single color television model
  sold by a large electronics manufacturer to one
  of its accounts, a national retailer

order stream
14
Impact of Promotional Sales
POS Data After Removing Promotions
Point-of-sales Data-Original
15
Demand Forecasting Lead Time

• Single retailer, single manufacturer
• Retailer observes customer demand, Dt
• Retailer orders qt from manufacturer
• Suppose a P period moving average forecasting is
  used

Dt
qt
Retailer
Manufacturer
L
Chen et al. 2000
16
Demand Forecasting Lead Time

• Var(q)/Var(D) for various lead times

14
L5
L5
Var(q) Var(D)
12
10
L3
L3
8
6
L1
4
L1
2
0
0
5
10
15
20
25
30
P
17
Demand Forecasting Lead Time

• Multi-stage supply chains
• Stage i places order qi to stage i1
• Li is lead time between stage i and i1
• Centralized each stage bases orders on
  retailers forecast demand
• Decentralized each stage bases orders on
  previous stages demand

q1
qoD
q2
Retailer Stage 1
Manufacturer Stage 2
Supplier Stage 3
L1
L2
18
Demand Forecasting Lead Time

• Var(qk)/Var(D) with regard to stages

Var(qk) Var(D)
P
19
The Bullwhip Effect

• Managerial insights
• Bullwhip effect exists, in part, due to the
  retailers need to estimate the mean and variance
  of demand
• The increase in variability is an increasing
  function of the lead time
• The more complicated the demand models and the
  forecasting techniques, the greater the increase
• Centralized demand information can significantly
  reduce the bullwhip effect, but will not
  eliminate it

20
Coping with the Bullwhip Effect

• Reduce uncertainty
• POS
• Sharing information
• Sharing forecasts and policies
• Reduce variability
• Eliminate promotions
• Year-round low pricing
• Reduce lead times
• EDI
• Cross docking
• Strategic partnerships
• Vendor managed inventory
• Data sharing

21
Information for Effective Forecasts

• Pricing, promotion, new products
• Different parties have this information
• Retailers may set pricing or promotion without
  telling distributor
• Distributor/Manufacturer might have new product
  or availability information
• Collaborative Forecasting addresses these issues
• e.g. Wal-Marts Collaborative Planning,
  Forecasting, and Replenishment (CPFR)

22
Information for Coordination of Systems

• Information is required to move from local to
  global optimization
• Questions
• Who will optimize?
• How will savings be split?
• Information is needed
• Production status and costs
• Transportation availability and costs
• Inventory information
• Capacity information
• Demand information

23
Locating Desired Products

• How can demand be met if products are not in
  inventory?
• Locating products at other stores
• What about at other dealers?
• What level of customer service will be perceived?

24
Lead-Time Reduction

• Why?
• Customer orders are filled quickly
• Bullwhip effect is reduced
• Forecasts are more accurate
• Inventory levels are reduced
• How?
• EDI
• POS data leading to anticipating incoming orders

25
Information to Address Conflicts

• Lot size inventory
• Advanced manufacturing systems
• POS data for advance warnings
• Inventory transportation
• Lead time reduction for batching
• Information systems for combining shipments
• Cross docking
• Advanced DSS
• Lead time transportation
• Lower transportation costs
• Improved forecasting
• Lower order lead times
• Product variety inventory
• Delayed differentiation
• Cost customer service
• Transshipment