Analysis and Modeling of Inventory Shrinkage

November 12, 2001

2

Summary

The current economic downturn will increase inventory shrinkage from shoplifting by $1 billion in 2002, based on the economic model developed in this report.

The graphic shows the incremental cost triggered by rising unemployment and growing strain on household spending, compared with what might have been expected if the economy had continued to grow at its 2000 pace.

Inventory Shrinkage from Shoplifting(Billions of Dollars, Actual vs. Predicted)

$7

$8

$9

$10

$11

$12

$13

$14

$15

$16

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

$1 billion increase in shrinkage from shoplifting because of economic downturn.

Source: Retail Forward Inc., U.S. Department of Commerce, University of Florida Retail Security Survey, and FBI Uniform Crime Reports

3

Summary

The estimated cost is based on an economic model that found that shoplifting trends can be explained by changes in unemployment claims, the savings rate and retail prices.

The growing population of youth age 15 to 24 represents another factor that will tend to increase inventory shrinkage from shoplifting.

These economic factors should reverse the trend of recent years during which shoplifting eased as a source of inventory shrinkage.

In total, shrinkage from all sources shoplifting, employee theft, vendor fraud and paperwork error reached an estimated $39 billion in 2000. Shoplifting accounted for one-third of the total.

Table of Contents:

Page

Summary 2

Background on Total Shrinkage 4

Focus on Shoplifting Shrinkage 8

An Economic Model of Shoplifting10

The Modeling Approach 12

Population as Another Key Driver 15

4

A Positive Recent Trend

Source: University of Florida National Retail Security Survey

Total Shrinkage as a Percentage of Retail Sales

During the booming economy of recent years, inventory shrinkage – from all sources – has seemingly remained under control.

In 2000, total shrinkage slipped to 1.7% of retail sales, according to a survey by the University of Florida.

Over the last eight years, shrinkage has trended slightly downward from nearly 2.0% of retail sales in 1994.

1.0%

1.1%

1.2%

1.3%

1.4%

1.5%

1.6%

1.7%

1.8%

1.9%

2.0%

1993 1994 1995 1996 1997 1998 1999 2000

5

Differences by Retail Segment

Source: University of Florida National Retail Security Survey and Retail Forward Inc.

Shrinkage as Share of Sales by Type of Retailer(Average Since 1993)

2.3%

2.3%

2.1%

2.1%

2.1%

2.0%

1.8%

1.8%

1.8%

1.8%

1.8%

1.6%

1.6%

1.3%

1.0%

0.9%

0.0% 0.5% 1.0% 1.5% 2.0% 2.5%

Book stores/ greeting card & novelty shops

Recorded music & video stores

Toy & hobby stores

Convenience, liquor wine & beer stores

Drug stores & pharmacies

Discount stores

Apparel stores (men, women & children)

Department stores

Jewelry & optical stores

Home centers, lumber & garden supply

Total Retail

Sporting goods stores

Supermarkets & grocery stores

Shoe stores

Furniture & household furnishings stores

Consumer electronics & appliances

Not surprisingly, segments such as book and music stores that sell smaller-sized products have higher inventory shrinkage rates compared with segments such as consumer electronics and furniture stores that sell larger products.Although these rates by segment are volatile year-to-year, they show that the economic slowdown in 1996 resulted in a noticeable increase in shrinkage rates for discount stores, department stores and furniture/home furnishings stores.

6

Total Costs Still Rising

Despite the slight decline in the overall shrink rate in recent years, inventory shrinkage measured in dollars rose to an estimated $39 billion in 2000 from $30 billion in 1993 as the total retail market grew briskly over that time span.The losses are estimated at retail value by applying the annual shrinkage rates to total retail sales.

Total retail sales, excluding motor vehicle sales and food service, registered $2.3 trillion in 2000, according to the U.S. Department of Commerce. Source: University of Florida Survey, U.S. Department of Commerce and Retail Forward Inc.

Total Inventory Shrinkage(billions of dollars)

$0

$5

$10

$15

$20

$25

$30

$35

$40

$45

1993 1994 1995 1996 1997 1998 1999 2000 2001

7

A Shift in Sources of Shrink

Sources of Shrinkage in 1996

Shoplifting36%

Employee Theft38%

Paperwork Error19%

Vendor Fraud6%

Sources of Shrinkage in 2000

Shoplifting33%

Employee Theft44%

Paperwork Error18%

Vendor Fraud5%

Source: University of Florida National Retail Security Survey

During the economic boom of recent years, slower growth in shoplifting contributed to a striking shift in the sources of shrinkage.

As shoplifting became a significantly smaller share of shrinkage by 2000, employee theft grew to be a larger share of shrinkage compared with 1996.

8

Shoplifting Lagged in Good Times

As shoplifting grew slowly during the boom times, it noticeably lagged the growth of total inventory shrinkage.

Shrinkage from shoplifting is estimated at nearly $13 billion in 2000, which is only modestly higher than the $12.2 billion estimated for 1996.

Source: University of Florida Survey, U.S. Department of Commerce and Retail Forward Inc.

Inventory Shrinkage by Source(billions of dollars)

$0

$5

$10

$15

$20

$25

$30

$35

$40

$45

1993 1994 1995 1996 1997 1998 1999 2000 2001

Shrinkage from Shoplifting

Total Shrinkage

9

Shoplifting Cases Declined

Shoplifting Cases(in thousands)

-

200

400

600

800

1,000

1,200

1,400

1,600

1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000

* Cases prior to 1975 derived from crime reports data

The slow growth in shrinkage from shoplifting corresponds with a dramatic decline in the number of shoplifting cases reported by the FBI since 1996.

This decline in shoplifting was likely the result of a booming economy. Plummeting unemployment rates and strong income growth dramatically reduced the factors that cause people to shoplift.As a result, the number of shoplifting cases is likely to increase significantly in 2001 and 2002 as the U.S. economy deteriorates.

Source: FBI Uniform Crime Reports and Retail Forward Inc.

10

Shoplifting Will Rise Again

Shoplifting Cases(Actual vs. Predicted)

-

200

400

600

800

1,000

1,200

1,400

1,600

1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

Actual

Predicted

Source: FBI Uniform Crime Reports and Retail Forward Inc.

The expectation that an economic downturn will increase retail inventory shrinkage is confirmed by an economic model of shoplifting.

The model shows that most of the change in shoplifting over time can be explained by three variables: unemployment claims, the savings rate and retail prices.

Shoplifting tends to increase with rising unemployment claims, a growing savings rate and higher retail prices.

The model predicts a jump in shoplifting in 2001 and 2002, assuming the recent rise in jobless claims and saving persists into 2002.

11

$1 Billion Cost

The predicted increases in shoplifting cases translate into $1 billion of incremental shrinkage losses in 2002 for retailers from shoplifting alone.

These losses are calculated by comparing shoplifting shrinkage given higher unemployment claims and savings to the shrinkage that would have been expected if unemployment claims and savings remained at their 2000 pace.

Inventory Shrinkage from Shoplifting(Billions of Dollars, Actual vs. Predicted)

$7

$8

$9

$10

$11

$12

$13

$14

$15

$16

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

$1 billion increase in shrinkage from shoplifting because of economic downturn.

Source: Retail Forward Inc., U.S. Department of Commerce, University of Florida Retail Security Survey, and FBI Uniform Crime Reports

12

The Modeling Approach

These were the variables considered as potential explanatory variables in the modeling:

Retail Sales Less Autos & GasolineIncomeConsumer CreditSaving RateHousing StartsEmploymentManufacturing EmploymentUnemployment RateUnemployment ClaimsUnemployed PersonsPrice Index for Retail Sales Less Autos & GasolineCore Consumer Price Index (excluding food & energy)

Gasoline Prices10-Year Treasury bond rateFederal Funds RatePopulation in five-year age brackets(i.e., Age 10-14, Age 15-19, etc.)

The economic model emerged from a statistical modeling process that considered a range of potential explanatory variables.

Considered were 15 macroeconomic variables, plus another 14 population age brackets.

A number of these variables, including certain population variables, showed a significant relationship to shoplifting.

The three variables in the model were the combination that together best explained movements in shoplifting.

13

The Economic Model

Shoplifting Cases(Percent Change, Actual vs. Predicted)

-10%

-5%

0%

5%

10%

15%

20%

1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001

ActualPredicted

Source: FBI Uniform Crime Reports and Retail Forward Inc.

The economic model actually models the change in shoplifting cases over time instead of the level number of cases.

The equation for the model is expressed this way:Shoplifting = .17 Unemployment Claims + .06 Savings Rate + .92 Prices

Each coefficient is essentially an elasticity measure that tells how much shoplifting will increase for each percent increase in the explanatory variable.

For example, a 10% increase in unemployment claims would be expected to increase shoplifting by 1.7%.

14

The Key Drivers

Source: U.S Bureau of Labor Statistics and Retail Forward Inc.

Prices in Retail Channels Excluding Autos(Percent Change)

-2%

0%

2%

4%

6%

8%

10%

12%

1970 1975 1980 1985 1990 1995 2000

Each spike in unemployment claims during a recession is associated with an increase in shoplifting.

As claims now reach 1991 recession levels, shoplifting should be pushed higher.

Unemployment Claims(average monthly claims in thousands)

-

100

200

300

400

500

600

700

1970 1975 1980 1985 1990 1995 2000

Source: U.S Bureau of Economic Analysis and Retail Forward Inc.

Saving Rate

0

2

4

6

8

10

12

1970 1975 1980 1985 1990 1995 2000

Source: U.S Bureau of Economic Analysis and Retail Forward Inc.

The recent falloff in shoplifting coincided with a big decline in the saving rate as incomes and wealth soared.

As households tighten their belts again, shoplifting should be pushed higher.

Shoplifting tends to rise amid high inflation as goods are priced out of consumers’ reach.

As the recent tame price environment continues, shoplifting should not be pushed higher by price pressures.

15

Population as a Driver

Age Distribution of Theft Arrests in 2000

1%

12%

30%

15%

9% 9% 9%

7%

4%

2%1% 0% 1%

0%

5%

10%

15%

20%

25%

30%

35%

Under 10 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65 plus

Source: FBI Uniform Crime Reports and Retail Forward Inc.

Although a population variable was not among the key explanatory variables, the modeling generally showed a positive relationship between shoplifting and the age brackets under age 35 – and conversely a negative relationship between shoplifting and the age brackets above age 45.The link between shoplifting and age is also evident in the age distribution of persons arrested for theft.

Persons between the ages of 15 and 24 represented the highest share of persons arrested for theft in 2000.

16

The Threat from Ages 15-24

Source: U.S. Bureau of Census and Retail Forward Inc.

Population Age 15 to 24

-

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

The potential threat represented by the population of persons age 15 to 24 is growing.

In recent years the numbers in this group have begun to grow as the Echo Boom, the children of the Baby Boom, reach their teen years.

As a result, this growing youth population represents another factor that should increase inventory shrinkage from shoplifting in the coming years.