warelite real time demand chain management chain...

WareLite Real Time Demand WareLite Real Time Demand WareLite Real Time Demand WareLite Real Time Demand

Chain Management Chain Management Chain Management Chain Management –––– A Simple A Simple A Simple A Simple

Solution to Shelf Out of StocksSolution to Shelf Out of StocksSolution to Shelf Out of StocksSolution to Shelf Out of Stocks

Powered by WareLite BOSSEnabled by IBM Store Integration

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Enabled by IBM Store Integration Framework

3rd EPTS Event Processing Symposium, Orlando, 17-19 September 2007

Elena Pasquali, CEO, WareLite [email protected]

www.warelite.net

© WareLite 2007

Shelf Out of Stocks: the Problem’s Size

• Retail Out-Of-Stocks (OOS) rate is on average 8.3% 1 globally• This figure doubles (16.5%) for products under prom otion 3,

increasing up to 30% in Europe 11

• Out-of-Stocks cause retailers an average 4% sales l oss 1

• Stock-outs cause walk-outs: in 2005 47% of customer s chose to shop elsewhere when faced by an empty shelf 5

• Overstocking to prevent OOS cost retailers around $ 40 billion • Overstocking to prevent OOS cost retailers around $ 40 billion globally 8

• 25% of Out-of Stocks globally 1 – and 38% in Europe 9 – are due to the fact that the goods are available in the store’ s backroom but are not displayed on the shelf

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Shelf Out of Stocks remains an unsolved problem for retailers and manufacturers

• Despite investments in sophisticated analytical too ls, HR initiatives and RFID implementations, shelf out- of-stocks remains a largely unsolved problem

– “Stock levels at the big six – Tesco, Sainsbury’s, Asda, Morrisons, Somerfield and Waitrose – have deteriorated over the past six months compared with the first half of the year “ Sean Poulter, Daily Mail, December 18, 2006

– “Today’s CP processes for demand sensing and shaping take 7 to 9 days to correct an out of stock. […] Retail perpetual inventory accuracy is worse

© WareLite 2007 3

correct an out of stock. […] Retail perpetual inventory accuracy is worse than originally believed. The inaccuracies of even Wal-Mart store-level inventory data triggers manufacturing replenishment two days too late at a store level.” L Cecere et Al, ‘What We Have Learned From Three Years of Retail RFID Pilots’, AMR Research, April 2007

The root cause of OOS is in the lack of consistent, automated, real

time monitoring of On Shelf Availability – i.e. Demand - across all

products in store.

WareLite Real Time Demand Chain Management addresses this issue

The Current Approach to On Shelf Availability Measurement 6,11

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The direct measurement of actual OOS is still manua l: POS data is only analyzed retrospectively – i.e. indirectly - to provide

demand forecasts and ‘prediction of likelihood of o ut-of-stock’ 6,11

WareLite Real Time Demand Chain Management: Automat ed In-Store Replenishment

SHELF POS Operator

Alert: Re-stock Shelf

RFID

PurchaseEvent

5Operator

Alert: Re-stockBackroom

RFID

or...

Backroom

ReplenishmentEvent

...Operator

WL DCM: ‘Store Data’ and ‘ Enterprise Data’

StoreData

StoreData

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‘Store Data’ supports real time in-store operations, managed by WL

DCM; ‘Enterprise Data’ supports Real Time Dashboards, managed by

third party BI/BAM tools

EnterpriseData

StoreData

EnterpriseData

EnterpriseData

StoreData

StoreData

StoreData

WareLite Real Time Demand Chain Management: the Pur chase Process

WL BOSS

PurchaseEvent

Update On-Shelf Availability

Business Process

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Calculate Sales Trend

Analyze Sales Trend & Alert

Check Watermark & Alert

Update Sales Trend History

Open Pending Operation

Check OOS & Alert

Update OOS History


WL BOSS

PurchaseEvent

OSA Tx = OSAT0 - 1

StoreData


Business Process

8






Check OOS & Alert

Update OOS History


WL BOSS

PurchaseEvent

Amount of product

sold per time unit

(e.g. 2 minutes)Update On-Shelf Availability

Business Process

Enterprise Data

9

(e.g. 2 minutes)






Check OOS & Alert

Update OOS History


WL BOSS

PurchaseEvent

Conditioner Brand X: Current Sales Trend

20

25

30

Qua

ntity

Sol

d

Enterprise Data


Business Process

10

0

5

10

15

09:00 09:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30

Time

Qua

ntity

Sol

d

Conditioner Brand X: Current Sales

0

20

40

60

80

100

09:00 09:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30

Time

Cum

ulat

ive

Sal

es






Check OOS & Alert

Update OOS History


WL BOSS

PurchaseEvent If a product is selling so

quickly that it risks

going out of stock in a

time shorter than the

replenishment time, an

Operator is sent an alert

StoreData


Business Process

11

Operator is sent an alert






Check OOS & Alert

Update OOS History


WL BOSS

PurchaseEvent Watermarks can be

defined differently

for each single

product and they

can be fixed, semi-

fixed or variable

StoreData


Business Process

12

fixed or variable






Check OOS & Alert

Update OOS History


WL BOSS

PurchaseEvent

When a Low Watermark

alert is sent, a Pending

Replenishment Operation is

StoreData


Business Process

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Replenishment Operation is

opened. This will be closed

only when the shelf

replenishment will have

been completed. The time

elapsed between the

opening and closing of the

operation is calculated,

allowing measurement of

Operational Effectiveness






Check OOS & Alert

Update OOS History


WL BOSS

PurchaseEvent Store

Data


Business Process

14






Check OOS & Alert

Update OOS History


WL BOSS

PurchaseEvent

OOS Current Status - 14:30 Today

Enterprise Data


Business Process

15

02468

101214

Condit

ioner

ASha

mpoo B

Toothp

aste

C

Wipe

s C

Mas

k DLip

stick

Z

Product Name

N.

of A

lerts N. Trend Alerts

N. Low Watermark Alerts

N. OOS






Check OOS & Alert

Update OOS History

WL BOSS

WareLite Real Time Demand Chain Management: the She lf Replenishment Process

Business Process

ReplenishmentEvent

16

Close Pending Operation


Update On-Shelf AvailabilityProcess

Update Warehouse Availability

Check OOS & Alert

Update OOS History

WL BOSS


Store

ReplenishmentEvent

Business Process

17

OSA Ty= OSATx + N

StoreData





Check OOS & Alert

Update OOS History

WL BOSS


Enterprise Data

ReplenishmentEvent

Business Process

18

Operational Effectiveness - Average Shelf Replenishment Time Today

0

20

40

60

80

100

ConditionerA

Shampoo B Toothpaste C Wipes C Mask D Lipstick Z

Product

Min

utes

Data





Check OOS & Alert

Update OOS History

WL BOSS


StoreData

ReplenishmentEvent

Business Process

19

Warehouse AvailabilityTy=

Warehouse AvailabilityTx - N

Legacy

Inventory

Management

Application





Check OOS & Alert

Update OOS History

WL BOSS


Store

ReplenishmentEvent

Business Process

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Alerts can be sent to

Store Managers, Depot

Operators, Suppliers etc.

Standing orders, delivery

schedules etc. can be

automatically updated

StoreData





Check OOS & Alert

Update OOS History

WL BOSS


ReplenishmentEvent

Business Process

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Up to the minute

data available by

product, store,

region, globally etc.

Enterprise DataClose Pending Operation




Check OOS & Alert

Update OOS History

WL DCM and IBM SIF: Architecture Overview

EXTENDA

3° Party POS

IBM STOREBROKER

DCM-ENT

DCM-ENT

Portal

DCM-ENT

DCM-ENT

SAP Oracle ......

3° Party IMS/ERP

RETEK

......

BROKER

DCM-RT

DCM-RT

DCM-RT

MQSeries

DCM-RT

IBM Mobile Front-End

WareLite Real Time Demand Chain Management: Benefit s

• It brings an instant 1% increase in revenues by eliminating those 25% of Out-of-Stocks that arise when goods are avai lable in store but are not on the shelves

• It makes more efficient use of shelf stackers’ and shop floor operators’ time, thus reducing operational costs and increasing employee satisfaction

• It improves the customers' buying experience , leading to increased loyalty and future revenues

• Provides real time visibility over sales volumes, sales tren ds, out -of -stocks, inventories and operational effectiveness , allowing both

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• Provides real time visibility over sales volumes, sales tren ds, out -of -stocks, inventories and operational effectiveness , allowing both timely responsiveness to unexpected events and bett er planning, thus addressing those 47% of OOS that arise from in accurate demand forecasting - increasing revenues by another 1.88%

• By sharing real time demand data between retailers and suppliers, the final 28% of Out-of-Stocks that arise from mism atches between suppliers capabilities and customer demand can be a ddressed and eliminated , adding a final 1.12% to turnover

Acknowledgments

• For their contribution to the development of WL DCM and unwavering support, we thank– Dr. Adriano Visconti, IT Director, Coop CentroItalia– The Motorola (Symbol) EMEA team

• With special thanks to James Pemberton, Strategic Alliance DirectorDirector

– The IBM Retail Innovation/EBO Team (Northern and Southern Europe)

• With special thanks to Chris Osborne

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References1. Grocery Manufacturers of America et Al, ‘Retail O ut-of-Stocks: A Worldwide Examination of Extent,

Causes and Consumer Responses’, October 20022. D. Corsten, T. Gruen, ‘Stock-Outs Cause Walkouts’ , Harvard Business Review, May 20043. J.C. Taylor, ‘Retail on-shelf performance of adve rtised items: An assessment of supply chain

effectiveness at the point of purchase’, Journal of Business Logistics, 20014. L.W. Emmelhainz et Al, ‘Logistics Implications of Retail Stockouts’, Journal of Business Logistics,

n. 2, 19915. John Davison, ‘How retailers can keep the custome r satisfied’, Computing 19 Jan 2006,

http://www.computing.co.uk/computing/features/21488 56/retailers-keep-customer6. ECR (Efficient Consumer Response) UK, ‘Availabili ty - A UK Perspective’, IGD (Institute of Grocery

Distribution), 20047. E Pasquali et Al, ‘WareLite Real Time Demand Chai n Management – A Simple Solution to Retail

Out-of-Stocks’, WareLite http://www.wlboss.com/articles/WL_Real_Time_Demand_ Chain_Management.pdf

8. Rene Schrama, “Beyond the Hype… Delivering On -Shelf Availability”, Symbol Technologies 2006,

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8. Rene Schrama, “Beyond the Hype… Delivering On -Shelf Availability”, Symbol Technologies 2006, http://www.gs1uk.org/uploaded/doc_library/Rene%20Sc hrama1377.pdf

9. Bill C Hardgrave et Al, ‘RFID’s Impact on Out of Stocks: A Sales Velocity Analysis’, RFID Research Center, Information Technology Research Institute, Sam M. Walton College of Business, University of Arkansas, June 2006, http://itrc.uark.edu/research/display.asp?article=I TRI-WP068-0606

10. L Cecere et Al, ‘What We Have Learned From Three Years of Retail RFID Pilots’, AMR Research, April 2007, http://www.amrresearch.com/Content/View.asp?pmillid =20358

11. ECR Europe, ‘How to improve Consumer Response an d Sales Performance through On-Shelf-Availability’ ECR Europe Forum, Milan, 8 May 2007, http://www.ecreuropeforum.net/PublicPages/Archive/M ilan/Downloads/CC5%20-%20OSA.pdf

12. Dirk Heyman, Procter & Gamble, ‘EPC Enabled Prom otional Display excellence’ ECR Europe Forum, Milan, 10 May 2007, http://www.ecreuropeforum.net/PublicPages/Archive/M ilan/Downloads/BO4.2%20-%20RFID.pdf

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