Chapter 2
Inventory
Management
and Risk Pooling
McGraw-Hill/Irwin
Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved.
2.1 Introduction
Why Is Inventory Important?
Distribution and inventory (logistics) costs
are quite substantial
Total U.S. Manufacturing Inventories ($m):
 1992-01-31: $m 808,773
 1996-08-31: $m 1,000,774
 2006-05-31: $m 1,324,108
Inventory-Sales Ratio (U.S. Manufacturers):
 1992-01-01: 1.56
 2006-05-01: 1.25
2-2
Why Is Inventory Important?

GM’s production and distribution network







Freight transportation costs: $4.1 billion (60% for
material shipments)
GM inventory valued at $7.4 billion (70%WIP; Rest
Finished Vehicles)
Decision tool to reduce:


20,000 supplier plants
133 parts plants
31 assembly plants
11,000 dealers
combined corporate cost of inventory and transportation.
26% annual cost reduction by adjusting:


Shipment sizes (inventory policy)
Routes (transportation strategy)
2-3
Why Is Inventory Required?

Uncertainty in customer demand
Shorter product life cycles
 More competing products


Uncertainty in supplies

Quality/Quantity/Costs/Delivery Times
Delivery lead times
 Incentives for larger shipments

2-4
Holding the right amount at the
right time is difficult!

Dell Computer’s was sharply off in its forecast of
demand, resulting in inventory write-downs


Liz Claiborne’s higher-than-anticipated excess
inventories


1993 unexpected earnings decline,
IBM’s ineffective inventory management


1993 stock plunge
1994 shortages in the ThinkPad line
Cisco’s declining sales

2001 $ 2.25B excess inventory charge
2-5
Inventory Management-Demand
Forecasts

Uncertain demand makes demand
forecast critical for inventory related
decisions:
What to order?
 When to order?
 How much is the optimal order quantity?


Approach includes a set of techniques

INVENTORY POLICY!!
2-6
Supply Chain Factors in Inventory
Policy





Estimation of customer demand
Replenishment lead time
The number of different products being considered
The length of the planning horizon
Costs

Order cost:



Inventory holding cost, or inventory carrying cost:





Product cost
Transportation cost
State taxes, property taxes, and insurance on inventories
Maintenance costs
Obsolescence cost
Opportunity costs
Service level requirements
2-7
2.2 Single Stage Inventory
Control


Single supply chain stage
Variety of techniques









Economic Lot Size Model
Demand Uncertainty
Single Period Models
Initial Inventory
Multiple Order Opportunities
Continuous Review Policy
Variable Lead Times
Periodic Review Policy
Service Level Optimization
2-8
EOQ: Costs
FIGURE 2-4: Economic lot size model: total cost per unit time
2-9
Demand Uncertainty

The forecast is always wrong


The longer the forecast horizon, the worse the
forecast


It is difficult to match supply and demand
It is even more difficult if one needs to predict
customer demand for a long period of time
Aggregate forecasts are more accurate.


More difficult to predict customer demand for
individual SKUs
Much easier to predict demand across all SKUs
within one product family
2-10
Single Period Models
Short lifecycle products
 One ordering opportunity only
 Order quantity to be decided before
demand occurs


Order Quantity > Demand => Dispose excess
inventory
Order Quantity < Demand => Lose sales/profits
2-11
Single Period Models

Using historical data



identify a variety of demand scenarios
determine probability each of these scenarios will
occur
Given a specific inventory policy


determine the profit associated with a particular
scenario
given a specific order quantity



weight each scenario’s profit by the likelihood that it will occur
determine the average, or expected, profit for a particular
ordering quantity.
Order the quantity that maximizes the average
profit.
2-12
Observations
The optimal order quantity is not
necessarily equal to forecast, or average,
demand.
 As the order quantity increases, average
profit typically increases until the
production quantity reaches a certain
value, after which the average profit starts
decreasing.
 Risk/Reward trade-off: As we increase the
production quantity, both risk and reward
increases.

2-13
What If the Manufacturer Has an
Initial Inventory?

Trade-off between:
Using on-hand inventory to meet demand and
avoid paying fixed production cost: need
sufficient inventory stock
 Paying the fixed cost of production and not
have as much inventory

2-14
Multiple Order Opportunities
REASONS
 To balance annual inventory holding costs and annual fixed order
costs.
 To satisfy demand occurring during lead time.
 To protect against uncertainty in demand.
TWO POLICIES
 Continuous review policy




inventory is reviewed continuously
an order is placed when the inventory reaches a particular level or reorder point.
inventory can be continuously reviewed (computerized inventory systems are
used)
Periodic review policy



inventory is reviewed at regular intervals
appropriate quantity is ordered after each review.
it is impossible or inconvenient to frequently review inventory and place orders if
necessary.
2-15
Service Level Optimization
Optimal inventory policy assumes a
specific service level target.
 What is the appropriate level of service?


May be determined by the downstream
customer
 Retailer
may require the supplier, to maintain a
specific service level
 Supplier will use that target to manage its own
inventory

Facility may have the flexibility to choose the
appropriate level of service
2-16
Trade-Offs

Everything else being equal:
the higher the service level, the higher the
inventory level.
 for the same inventory level, the longer the
lead time to the facility, the lower the level of
service provided by the facility.
 the lower the inventory level, the higher the
impact of a unit of inventory on service level
and hence on expected profit

2-17
Retail Strategy
Given a target service level across all
products determine service level for each
SKU so as to maximize expected profit.
 Everything else being equal, service level
will be higher for products with:

high profit margin
 high volume
 low variability
 short lead time

2-18
Profit Optimization
and Service Level
Target inventory level = 95% across all
products.
 Service level > 99% for many products
with high profit margin, high volume and
low variability.
 Service level < 95% for products with low
profit margin, low volume and high
variability.

2-19
2.3 Risk Pooling
Demand variability is reduced if one
aggregates demand across locations.
 More likely that high demand from one
customer will be offset by low demand
from another.
 Reduction in variability allows a decrease
in safety stock and therefore reduces
average inventory.

2-20
Demand Variation

Standard deviation measures how much
demand tends to vary around the average


Gives an absolute measure of the variability
Coefficient of variation is the ratio of
standard deviation to average demand

Gives a relative measure of the variability,
relative to the average demand
2-21
2.4 Centralized vs.
Decentralized Systems





Safety stock: lower with centralization
Service level: higher service level for the same
inventory investment with centralization
Overhead costs: higher in decentralized system
Customer lead time: response times lower in the
decentralized system
Transportation costs: not clear. Consider
outbound and inbound costs.
2-22
2.5 Managing Inventory in the
Supply Chain



Inventory decisions are given by a single
decision maker whose objective is to
minimize the system-wide cost
The decision maker has access to inventory
information at each of the retailers and at the
warehouse
Echelons and echelon inventory
 Echelon inventory at any stage or level of
the system equals the inventory on hand
at the echelon, plus all downstream
inventory (downstream means closer to
the customer)
2-23
Echelon Inventory
FIGURE 2-13: A serial supply chain
2-24
More than One Facility at Each
Stage


Echelon inventory at the warehouse is the
inventory at the warehouse, plus all of the
inventory in transit to and in stock at each of the
retailers.
Similarly, the echelon inventory position at the
warehouse is the echelon inventory at the
warehouse, plus those items ordered by the
warehouse that have not yet arrived minus all
items that are backordered.
2-25
Warehouse Echelon Inventory
FIGURE 2-14: The warehouse echelon inventory
2-26
2.6 Practical Issues
Periodic inventory review.
 Tight management of usage rates, lead times, and
safety stock.
 Reduce safety stock levels.
 Introduce or enhance cycle counting practice.
 ABC approach.
 Shift more inventory or inventory ownership to
suppliers.
 Quantitative approaches.
FOCUS: not reducing costs but reducing inventory levels.
Significant effort in industry to increase inventory turnover

Annual _ Sales
Inventory _ Turnover _ Ratio 
Average _ Inventory _ Level
2-27
Inventory Turnover Ratios for
Different Manufacturers
Industry
Upper quartile
Median
Lower quartile
Electronic components
and accessories
8.1
4.9
3.3
Electronic computers
22.7
7.0
2.7
Household audio and
video equipment
6.3
3.9
2.5
Paper Mills
11.7
8.0
5.5
Industrial chemicals
14.1
6.4
4.2
Bakery products
39.7
23.0
12.6
Books: Publishing and
printing
7.2
2.8
1.5
2-28
2.7 Forecasting
RULES OF FORECASTING
 The forecast is always wrong.
 The longer the forecast horizon, the
worse the forecast.
 Aggregate forecasts are more accurate.
2-29
Utility of Forecasting
Part of the available tools for a manager
 Despite difficulties with forecasts, it can be
used for a variety of decisions
 Number of techniques allow prudent use
of forecasts as needed

2-30
Techniques

Judgment Methods





Market research/survey
Time Series






Moving Averages
Exponential Smoothing
Trends


Sales-force composite
Experts panel
Delphi method
Regression
Holt’s method
Seasonal patterns – Seasonal decomposition
Trend + Seasonality – Winter’s Method
Causal Methods
2-31
The Most Appropriate
Technique(s)
Purpose of the forecast
 How will the forecast be used?
 Dynamics of system for which forecast will
be made
 How accurate is the past history in
predicting the future?

2-32
SUMMARY






Matching supply with demand a major challenge
Forecast demand is always wrong
Longer the forecast horizon, less accurate the
forecast
Aggregate demand more accurate than
disaggregated demand
Need the most appropriate technique
Need the most appropriate inventory policy
2-33