Slide 1

RFID-Enabled Visibility and Inventory Record Inaccuracy: Experiments in the Field

Bill Hardgrave (presenter)

John Aloysius

Sandeep Goyal

Information Systems Department

University of Arkansas

Will RFID technology improve inventory recordaccuracy? (Study 1)

Can RFID technology ameliorate the effects ofknown causal predictors of inventory recordinaccuracy? (Study 1 / Study 2)

What are the characteristics of product categoriesfor which RFID technology is effective in reducinginventory record inaccuracy? (Study 2)

All products in air freshener category tagged atcase level

Interrupted Time-series design

Data collection: 23 weeks

13 stores: 8 test stores, 5 control stores

Mixture of Supercenter and Neighborhood Markets

Daily physical counts

10 weeks to determine baseline

Same time, same path each day

Study 1 Results: Linear Mixed Effects (Discontinuous growth model for test stores)

Results of Linear Mixed Effects

Variables

Effect

(Intercept)

8.004***

Sales Volume

-0.953**

Variety

-0.003

Item cost

0.040*

Dollar Sales

0.000

PRE

0.138**

TRANS

1.875***

POST

- 0.345***

Notes p<.05, **p< .01, ***p<.001Velocity = Number of units sold per day; Item Cost Cost of an item in cents; Sales Volume = Item Cost X Velocity; Variety = Number of unique SKUS carried in a store; PRE: Periods numbered consecutively for 40 day window around the adjustment; POST: Periods numbered O to 20 days before the adjustment, numbered consecutively after; TRANS: Numbered 0 before the adjustment, numbered 1 after

Notes p<.05, **p< .01, ***p<.001

Velocity = Number of units sold per day; Item Cost: Cost of an item in cents; Sales Volume = Item Cost X Velocity; Variety =Number of unique SKUS carried in a store; PRE: Periods numbered consecutively for 40 day window around the adjustment;POST: Periods numbered O to 20 days before the adjustment, numbered consecutively after; TRANS: Numbered 0 beforethe adjustment, numbered 1 after

Study 1 Results: Discontinuous growth model (Interrupted time series for test stores)

Study 1 Results: Linear Mixed Model for Test versus Control stores (post period)

Variables

Fixed effects

(Intercept)

5.654***

Sales volume

2.356***

Variety

0.000

Item Cost

0.001

Dollar sales

-0.002

Test

-1 .630**

Period

-0.008

Notes: ***p<.001, **p<.01

Sales volume = Number of units sold per day; Item Cost = Cost of an item in cents; Dollar Sales = Item Cost X Velocity;Variety = Number of unique SKUs carried in a store; Test: Dummy variable coded I for test stores and 0 for control stores;Period: Day 1 starting when RFID auto-adjust was made available in test store.

•PI accuracy improved 23%

•Results were essentially what we expected

•Insight from DeHoratius and Raman (2008)variables

•Raises the question: what about other categories?

•Untreated Control Group design with pretest and post-test

•Matched Sample

•62 stores: 31 test stores, 31 control stores

•Mixture of Supercenter and Neighborhood Markets

•Spread across the United States

•Looked at both understated PI and overstated PI

•Control stores: RFID-enabled, business as usual

▫Test stores: business as usual, PLUS used RFID reads (frominbound door, sales floor door, box crusher) to determinecount of items in backroom

Auto-PI: adjustment made by system

For example: if PI = 0, but RFID indicates case (=12) in backroom, then PIadjusted

PI: Perpetual Inventory

•Five general merchandise categories

•Floorcare

•e.g., Powerforce vacuum, tough stain pretreat, Woolite gallon

•Air freshener

•e.g., Glade plugin, Febreeze paradise, Glade oil

•Formula

•e.g., Pediasure chocolate, Nutripal vanilla

•Ready to assemble furniture

•e.g., computer cart, pedestal desk, executive chair

•Quick cleaners

•e.g., wood floor cleaner, Readymop, Swiffer floor sweeper

PI: Perpetual Inventory

•Data collection

•Two waves (Pre and Post implementation), two months apart

•Same time, same path each wave

•Stock physical counts

•conducted over 5 days in each wave by an independent company

•Dependent variable: PI Absolute = |PI – Actual|

•Looked at both understated and overstated PI

Pre-implementation

Post-implementation

RFID Implementation

5 days

2 Months

5 days

•Data collection (contd.): Measures

•Item cost

•Cost of the item to the retailer

•Sales volume

•Quantity of item sold for two month preceding measurement

•Dollar sales

•Dollar amount of items sold for two month preceding measurement

•Density

•Total number of units in a category divided by linear feet of shelfspace for that category

•Variety

•Total number of unique SKUs in a category

PI: Perpetual Inventory

Study 2 Results: Ameliorating effects of RFID (Pre-test/Post-test)

PI~TREAT + COST + SALESVOL + DOLLARSA + DENSITY + CATVAR + TREAT_XXX

*** p < .01, ** p < .05, * p < .10

Study 2 Results:Effect size for Treatment, Linear Mixed Model

PI = β0 + β1*Treatment

1.*** p < .01, ** p < .05, * p < .10

2.Significance of difference assessed by interactionterm of treatment (pre-post) and group (test-control)

Study 2 Results:Characterization of Categories

*** p < .01, ** p < .05, * p < .10

▫RFID technology with case-pack taggingdemonstrated to improve inventoryinaccuracy by 16% to 81% depending oncategory characteristics

▫Evidence that RFID technology is effective inameliorating the effects on inventoryinaccuracy of item cost, sales volume, dollarsales, density, and variety

PI: Perpetual Inventory

RFID technology is more effective in reducingPI inaccuracy in product categories whichhave:

higher sales volume,

lower item cost,

higher dollar sales,

greater SKU variety,

greater inventory density

What is the economic impact of improvinginventory accuracy (with RFID)?

Imagine inventory accuracy with item-leveltagging …

Bill Hardgrave

bhardgrave@walton.uark.edu

479.575.6099

John Aloysius

jaloysius@walton.uark.edu

479.575.3003

Sandeep Goyal

sgoyal@walton.uark.edu

479.575.6961

For copies of white papers, visit

http://itri.uark.edu/research

Keyword: RFID

Perpetual inventory (PI) record inaccuracyaffects forecasting, ordering, replenishment

PI is inaccurate on 65% of items (Raman et al. 2001)

At any given time the retailer in this studymanages about $32 billion in inventory

Firms are skeptical about implementing newtechnologies based on pure faith, but needvalue assessments, tests, or experiments (Dutta,Lee, and Whang 2007)

Such empirical-based research requires “awell-designed sample, with appropriatecontrols and rigorous statistical analysis”

Research Model: Making the Business Case for RFID Technology

RFIDTechnology

InventoryVisibility

InventoryRecordInaccuracy

Costs/

Profitability

Research Gap

Delen et al. 2007

There is little empirical research in the fieldthat demonstrates and quantifies the abilityof RFID technology to improve inventoryinaccuracy

There is no empirical research thatcharacterizes product categories for whichRFID technology may be effective in reducinginventory record inaccuracy

Inventory visibility

Retailer’s ability to determine the location of a unit of inventory at agiven point in time by tracking movements in the supply chain

Inventory record inaccuracy

Absolute difference between physical inventory and the informationsystem inventory at any given time (Fleisch and Tellkamp 2005)

RFID-enabled auto-adjustment

A system that leverages RFID technology to correct for the absolutedifference between physical inventory and the inventorymanagement system inventory at any given time

Mechanisms whichresult in recordinaccuracy

Results inoverstated PI?

Results inunderstated PI?

Can case-levelRFID reduce theerror?

Incorrect manualadjustment

Yes

Improper returns

Yes

Mis-shipment fromDC

Yes

Cashier error

Yes

PI: Perpetual Inventory

Source: Delen et al. (2007)

There is evidence that RFID technology improvesinventory visibility

Researchers assume that improved inventory visibilitywill result in improved inventory record inaccuracyand consequently impact costs and profitability

The current research experimentally manipulatesinventory visibility in field conditions (by means ofan RFID enabled auto-adjustment system) in orderto assess the effect on inventory record inaccuracy