© 2009 IBM Corporation Utilizing GS1 Industry Standards – A way to improve your business Findings of the Global Compliance Survey 2009.

© 2009 IBM Corporation

Utilizing GS1 Industry Standards – A way to improve your business Findings of the Global Compliance Survey 2009

© 2009 IBM Corporation2

How is the usage of the GS1 standards and the impacts of their implementation on their supply chain? – High participation and a increased number of KPI scorecards indicates steady rising interest in the survey – Small companies to large cooperation– Analysis of over 5600 KPIs’ scorecards as well as over 2100 Enablers’ scorecards offer insights in the daily business of

the companies worldwide

At its score, the primary findings arose from the analysis:

Business profit in many ways from standards– Derive benefit in cost and efficiency by using GS1 standards– Companies improve the level as they experience the benefit– Examples would be: better fill rates, lower distribution costs, lower out-of-stock rates– Increasing implementation levels means increasing benefits– Enablers show strong connection with the corresponding implementation measures

Improvements for most of the standards– Most standards developed over the last years– “Panel sub-sample” shows a reasonable improvement trend in the last 4 years– Pushing implementation initiatives such as SSCC by GS1 for the last 5 years, show very positive results

Driving the GS1 standards implementation– Large Corporations – Companies dealing with fresh food– Former GCI member companies– The role model status of the large Corporations motivates smaller companies to be “fast followers” of implementing

standards

Executive Summary 1

Bullet point version of slide 3 for deck


Exploit supply chain savings due to the implementation of GS1 standards – Companies, who have implemented standards, behaved better than those who don’t– Furthermore you improve and strengthen the relationship with your trading partners

Create leadership: don’t stay up to date but actively lead the industry in development– Anticipate business trends – Actively lead the industry for the newer standards such as SSCC and Data Synchronization and early benefit from their advantages

for your competitiveness

Profit from data analytics – measure your benefits– Using standards means having access to a mass of information – Use business analytics for better planning and efficiency– Measure your benefit

Profit from use of global scorecard tool and survey results– Global scorecard tool and report provides information on individual companies, on country/regional analysis and on global analysis. It

demonstrates "as-is" performance (“the reality”) – The scorecard provides information basis across geographic regions when entering new markets– You can assess key process performance relative to peer companies – It helps to support the business case for improvement projects

It is absolutely necessary that you have consistent data across the value chain in order to manage your business most efficient and exhaust the whole potential of your tools and applications. Looking forward, consumers are demanding better product information and labeling. Furthermore, European legislation is also demanding that the industry provides further information related to packaging and the environment. Inconsistent data has a severe cost impact on the industry and will cost the industry a amount of money for administration costs and lost revenues. It is time that all CP companies more address the data quality issue and reap the considerable benefits*.

Executive Summary 2 / Recommendations

“If you can’t measure it, you can’t manage it!”Peter Drucker, Economist

* GS1 Data Crunch Report, October 2009


Content

Table of contents

Executive Summary

1. Introduction

About this report

Background of the Global Scorecard

2. Benefits of best practice

Importance of common data

Benefits of best practice

Case study SSCC/EDI

Case study Global Data Synchronization

Data Synchronization

3. Data Development

Overview of Implementation measures

Potential for standards

Comparison Implementation measures and Enablers

Trend analysis

4. Standards in practice

Drivers of the implementation

GCI results

Success factors

Benefits of ECR linked with Insights of our study (IBM)

How do companies use the scorecard results for internal planning

5. Participation

Participation details

Summary


Introduction


Content

About this report

The goal

To provide

- Status of the GS1 standards usage and implementation level

- Implication on Business measures, such as e.g. lower out-of stock rate or higher invoice accuracy

- Implementations in daily business

The methodology

- Data of 5,624 Key Performance Indicator scorecards and 2,180 Enablers scorecards from 2009 Scorecard survey

- Scorecards from 50 countries worldwide

- Many big player (10% of Fortune 500) and a total revenue of 1,800bn US$

- Focus on Consumer products industry, which represent 89% of the KPI scorecards

- Case studies


The number of the submitted KPI scorecards increased again in 2009

Submitted Scorecards

0

1.000

2.000

3.000

4.000

5.000

6.000

2002 2003 2004 2005 2006 2007 2008 2009

KPIs

StandardCapabilityAssessment


The total revenue of businesses participating in the global scorecard survey, while strong, dropped off in 2009 as 4 large CGF member companies, who have participated in the past, did so only marginally in 2009

Revenue in m $ of Survey participants

0

500.000

1.000.000

1.500.000

2.000.000

2.500.000

2002 2003 2004 2005 2006 2007 2008 2009

KPIs



The Global Scorecard - a Capability Assessment Tool has been designed 10 years ago to give you a detailed understanding of your ECR capability each year and to highlight specific improvement opportunities for your company. You are able to compare your company with the peers in your industry. Questions presented to the participant depend on the business type and industry sector.

Content

Profile

Used for the annual report

•Standard Capability Assessment (Measures the status of implementation)•Demand•Supply•Enablers (Item identification, Electronic messages and master data synchronization)•Integrators

•Business Measures (e.g. Service levels, inventory, out-of-stocks, lead time, costs, invoice accuracy)

•Implementation Measures (Measures the level of implementation for e.g. Item and location identification, EDI, Global Data Synchronization)


Benefits of Best Practice


Importance of common data


•Wal-Mart announced end of July 2010 rollout of sophisticated RFID tags in all clothing in all 3,750 stores in the US

•Largest of such adoptions worldwide

•Wal-Mart expects significant savings:

•more-efficient recalls

•loss prevention

•better overview of the inventory

•get rid of checkout lines

•In 2007 a similar pilot at American Apparel Inc.: saw sales rise up to 14.3%

Wal-Mart Example – latest news

http://online.wsj.com/article/NA_WSJ_PUB:SB10001424052748704421304575383213061198090.html

“RFID can really transform our business" Raul Vazquez, the executive in charge of Wal-Mart stores in the western U.S.


… it is only a small tag, but the amount of data that is collected and can be analyzed is enormous

Data sharing as imperative and basis for powerful analytics

CP industry

•highly competitive

•fast-moving

•rapidly changing

•margins under pressure

•increasing complexity

ftp://public.dhe.ibm.com/common/ssi/ecm/en/cie03046usen/CIE03046USEN.PDF

Using GS1 Standards is the key for all activities

Consolidated

Data

Quickly

accessible to

be analyzed

Business Analytics

Powerful

insights

More than 2,500 CEOs focus on Analytics*To overcome

complexity and gain competitive advantage


Using GS1 standards

We explore from more than 4,400 Key Performance Indicator Scorecards, submitted

by Consumer product companies, how the usage of the GS1 standards and

technology result in savings and improvements….

+ 5.9% points increased Fill rates

- 5.2% points savings of

Distribution costs

- 5.8% points reduced

Out-of-stocks rate

+ 1.5% points increased

Invoice accuracy

- 61hours shorterLead time


Many direct effects of the implementation of standards on the Business Measures could be captured in the Global Scorecard survey

Efficiency Customer Friendliness Improved Quality Sustainability

Competitive advantage

• Time saving• Cost reduction• Improved supply chain operations• Improved visibility • Increased understanding of retailers needs and become preferred collaboration partner• Increased sales

• Improved client relationship• Improved customer satisfaction • Better information availability

• Improved data quality• Fewer invoice-disputes

• Improved Image & Brand• Less Waste• Optimized usage of resources• Better overview of inventory

• Supplier Service Level žGTIN on consumer units

ŽGTIN on cases/cartons/innersŽGTIN catalogued with GS1 Product classification code

• Store Service Level žSSCCŽEDI for ordersŽEDI despatch advise ŽSales with syn master dataŽGTIN catalogued with GS1 Product classification code

• Annual Revenue Growth Rate ŽRoll out and full implementation of Trading partner performance standards (E401)

• Out of stocks žGTIN on cases/cartons/inners

ŽSSCCŽEDI for ordersŽEDI for despatch adviceŽGTIN catalogued with GS1 Product classification code

• On-time delivery Ž GTIN catalogued with

GS1 Product classification code

• Invoice accuracy žEDI for invoices (manufacturers)

• Distribution costs žGTIN on consumer units

ŽGTIN on cases/cartons/inners

• Order to delivery cycle time žGTIN on consumer units

ŽGTIN on cases/cartons/inners

Improvements through implementation

Should we keep this

standard in here?

Examples


Companies utilizing SSCC or EDI for orders show significant improvement for the store service level/fill rate

Efficiency

Store service level/Fill rate with the use of SSCC

93,9%

88,0%

Implementation ofSSCC

No Implementation ofSSCC

Examples on the next slides are selected by logical connection, variety of measures and % of change

Increase +5.9%

Store service level/Fill rate with the use of ED I for orders

93,0%

89,3%

Implementation of EDIfor orders

No Implementation ofEDI for orders

Increase +3,7%


Companies using GTIN on consumer units level on a higher implementation level gain advantage by an increased supplier service level

Efficiency

Supplier service level/Fill rate with the use of GTIN on consumer units level

94,3%

91,6%

Implementation >50% ofGTIN consumer units

level

Implementation 1-50%of GTIN consumer units

level

Increase +2.7%


Companies who are in roll out status or even have fully implemented (Enablers score 3+4) the GS1 standard framework for the calculation and exchange of trading partner performance generally do better in sales than other who don’t

Efficiency

Annual revenue growth rate with the use of Trading Partner Performance Measure

18,3%

5,2%

Implementation ofTrading Partner

Performance Measure

No Implementation ofTrading Partner

Performance Measure

Should we keep that correlation in here?

Need a quote!

+5,9%

Improved sales by +13,1%


The use of SSCC or EDI for orders positively affects the Out-of-stocks rate at the POS, which can be considerably reduced

Customer Friendliness

On-Shelf/POS Out-of-Stocks with the use of SSCC

3,8%

7,8%

Implementation of SSCC

No Implementation ofSSCC

On-Shelf/POS Out-of-Stocks with the use of EDI for orders

3,9%

9,7%

Implementation of EDI fororders

No Implementation ofEDI for orders

Reduction by - 4%

Reduction by - 5.8%


Companies using GTINs that are catalogued consistently with a GS1 Global Product Classification brick code profit from a higher On-time delivery

Customer Friendliness

On-Time Delivery with the use of Product classification

90,7%

89,6%

Using Productclassification

Not using Productclassification

Increase by +1,1%


Companies who have EDI for invoices implemented on a level above 50% could improve invoice accuracy and save a lot of money versus

Improved Quality

Invoice accuracy for manufacturers using EDI for invoices

97,2%

95,7%

Implementation of EDIfor invoices >50%

Implementation of EDIfor invoices 1 - 50%

Improved accuracy by +1.5%


Utilizing EDI for orders or GTIN on cases/cartons/inners level makes companies profit by lower distribution costs

Sustainability

Distribution costs with the use of EDI for orders

5,4%

10,6%

Implementation of EDIfor orders 1-50%

Implementation of EDIfor orders >50%

Distribution costs with the use of GTIN on cases/cartons/inners level

7,7%

12,4%

Implementation >50% of GTINcases/cartons/inners level

Implementation 1-50% of GTINcases/cartons/inners level

Reduction by – 5.2%

Reduction by – 4.7%


The order to delivery cycle time could be extensively reduced when companies have GTIN on case/cartons/inners level implemented

Sustainability

Order to delivery cycle time with the use of GTIN case/cartons/inners level

56h

117h

Implementation of GTINcases/cartons/inners

level

No implementation ofGTIN

cases/cartons/innerslevel

Reduction by - 61h


Case Study: McLane Company The value of data synchronization

Global Data Synchronization Network enables major distributor and its trading partners to exchange accurate data for cost savings and improved productivity.

Challenge

http://www.gs1us.org/DesktopModules/Bring2mind/DMX/Download.aspx?EntryId=1036&Command=Core_Download&PortalId=0&TabId=73

Solution

Benefits

Background

Meet retail partners´ requests and needs with efficient way to synchronize data.

McLane Company relies on the data pool certified by the Global Data Synchronization Network to synchronize data and improve data accuracy with trading partners. McLane uses the 1SYNC Product Introduction solution in its supplier certification process.

As a distributor, McLane Company plays he role of both a retailer and a supplier when synchronizing data. The company distributes products for approx. 3,500 suppliers and provides services to more than 60,000 customer locations worldwide. McLane´s customers include mass merchandisers, convenience stores, quick service restaurants, drug stores, and movie theaters.

After McLane seeing the value of synchronizing accurate item information, McLane rolled out its data synchronization campaign to its Tobacco, Confection and perishable& Frozen products. Since adopting the category approach, in only one year the numbers of partners with whom they synchronize data have doubled.

• McLane can focus and commit resources internally where they are needed at any one time.

• Data synchronization ensures that McLane and its suppliers are all speaking the same language, resulting in costs saving for McLane when purchasing products.

• Truck loads are more efficient based on data synchronization via GDSN.

• McLane suppliers also experience cost reductions since they can now send item information to McLane without shipping case samples.

„One of our suppliers saved close to $65,000 by not having to ship case samples“

Beckey James, Electronic Commerce Manager


Data Synchronization

Collaboration attempts brought the problem of asynchronous data to the forefront. Erroneous product codes result in mismatches between trading partners’ plans, resulting in costly errors. A manufacturer like Sony would realize that it failed to satisfy its customer fill-rate requirements for a new DVD player with Circuit City, due to a mismatch in product identification. As the supplier continues to send its customers the wrong products, unnecessary transportation costs and customer dissatisfaction mount. To avoid these problems firms looked for solutions that systematically synchronized their product data across disparate divisions and regions as well as with trading partners.

Forrester, Supply Chain Cooperation Check up, 2005

To measure the % of sales for which master data is being synchronized following the standards laid out by GS1 GDSN Inc. is nowadays only used by a small amount of companies. There is a huge potential left as the usage of impact on the e.g. the Unit fill rate. Retailers use higher average implementation level at 42% already than the manufacturers at the same time: 24%. Regarding the Enablers for the data synchronization we see a close link between the use of product classification standards and data quality. Both developed positively in the last years.

supplier:

retailer:

http://www.gs1uk.org/what-we-do/sector-solutions/retail/Pages/Master-Data-Management.aspx

GS1 Data Crunch Report from 2010:

To be continued


Data Development


Standards are more and more implemented, newer standards are following

Manufacturers Retailers & Wholesalers

2007 2008 2009 2007 2008 2009

IM01 % of consumer units allocated a GTIN 97.1 96.8 92.0 91.7 97.3 96.6

IM02 % of cases/cartons/inners allocated a GTIN 82.9 87.6 86.6 77.4 82.6 87.0

IM04 % of pallets/unit loads labeled with SSCC 45.9 49.4 67.2 51.1 49.4 71.6

IM05 % of shipping or receiving locations that have been allocated a GLN 43.9 41.2 51.1 64.3 74.5 87.5

IM06 % of orders transacted via EDI 52.4 51.7 47.0 68.8 70.4 75.8

IM07 % of invoices transacted via EDI 41.5 47.7 45.6 63.4 67.1 78.6

IM08 % of shipments for which a despatch advice was transmitted via EDI 22.5 27.6 35.5 28.0 22.4 58.7

IM09 % of shipments for which a receiving advice was transacted via EDI 7.1 12.0 16.0 29.8 13.9 58.4

IM10 % of sales with synchronized master data between trading partners via the GS1 Global Data Synchronization Network 13.5 19.0 24.4 9.4 17.0 42.4

IM11 % of sales with master data loaded into a GS1-certified data pool (%) 37.7 41.6 **

IM12 % of active SKUs where the master data has been synchronized using the GS1 Global Data Synchronization Network 2.9 7.0 26.5

IM13 % of GTINs that are catalogued consistently with a GS1 Global Product Classification brick code 45.7 47.2 71.0


Retailers & wholesalers tend to implement the standards on a higher average implementation level than manufacturers

47% 46%

36%

16%

24%

71%

87%

72%

88%

76%79%

59% 58%

42%

92%

67%

87%

51%

97%

0%

20%

40%

60%

80%

100%

GTINConsumer Unit

GTIN Case SSCC P allet GLN EDI Orders EDI Invoices EDI DespatchAdvice

EDI ReceivingAdvice

Sales withsynch. Data

P roductclassification

Manufacturers

Retailers & Wholesalers


Still a huge potential for many standards, especially Data Synchronization

39%

27% 24%

8% 9%

20%

5%

12%

43%

51%

38%

45%44%

38% 35%18%

91%

24%

51%

27%

0%

20%

40%

60%

80%

100%

GTINConsumer Unit

GTIN Case SSCC P allet GLN EDI Orders EDI Invoices EDI DespatchNotes

EDI ReceivingAdvice

Sales withsynch. Data

P roductclassification

Values = 0

Values > 0

96% of all companies have indicated an implementation level;

4,779 KPI scorecards

91% indicated an implementation level above 0

5% have responded by indicating a 0-implementation level


92,0%

86,6%

67,2%

51,1%47%

24,4%

71,0%

0%

20%

40%

60%

80%

100%

GTIN consumerunit

GTIN cartons SSCC GLN EDI Global DataSynchronization

P roductClassification

Standard

Wei

gh

ted

ave

rag

e p

er I

mp

lem

enta

tio

n

Mea

sure

0

1

2

3

4

En

abler's S

core

Level of IM w eighted

Enabler's Score

Enablers scores and the corresponding Implementation Measure Levels for manufacturers worldwide are on a similar level, showing a consistency in the data – however there is a enormous discrepancy with regard to the Global Data Synchronization measure. Companies have already built a lot of capability but with a limited use


96,6%

87,0%

71,6%75,8%

87,5%

42,4%

0%

20%

40%

60%

80%

100%

GTIN consumerunit

GTIN cartons SSCC EDI GLN Global DataSynchronization

Wei

gh

ted

ave

rag

e p

er I

mp

lem

enta

tio

n

Mea

sure

0

1

2

3

4

En

abler's S

core


Enabler's Score

Enablers Scores and the Implementation Measure Levels for retailers & wholesalers fit better for the retailers & wholesalers – however there is again a discrepancy with regard to the Global Data Synchronization


Implementation trend analysis 2006 – 2009*

Sub-sample of 136 scorecards

Participation in 2006 and 2009

92% are GCI members

2006 survey: 886 scorecards

KPI Scorecards Breakdown by Business Type

Manufacturer; 123; 90%

Retailer; 13; 10%

Note: Data analysis is based on a sample of companies, which participated in 2006 and 2009

KPI Scorecards Breakdown by Region

South America; 21; 0.5%

North America; 17; 13%

Asia & Middle East; 26; 0.6%

Europe; 73; 53%

Australasia; 12; 0.3%

Africa ; 9; 0.2%

KPI Scorecards Breakdown by GCI Membership

GCI Member; 123; 90%

Non-Member; 13; 10%


After keeping track of the data over a time period of 4 years we can see an improvement for all standards except GTIN on consumer units level, which is already on a very high level

Note: Data analysis is based on a sample of companies, which participated in 2006 and 2009 and averages (in order not to bias results due to change in revenue; sample sizes: IM11 and IM12 have blank entries for 2006; IM01 n=132, IM02 n= 130, IM04 n=107, IM05 n=120, IM06 n=122, IM07 n=121, IM08 n=107, IM09 n=90, IM10 n=102, IM13 n= 94;

4,3

9,3

12,7

28,1

41,8

51,5

51,5

53,1

87,9

98,9

7,1

15,0

14,7

32,7

48,3

54,4

60,3

54,5

94,2

97,7

0% 20% 40% 60% 80% 100%

IM01 - % of consumer units allocated a GTIN

IM02 - % of cases/cartons/inners allocated aGTIN

IM04 - % of pallets/unit loads labeled with SSCC

IM13 - % of GTINs that are cataloguedconsistently with a GS1 Global Product

Classification brick code

IM05 - % of shipping or receiving locationsallocated a GLN

IM06 - % of orders transacted via EDI

IM07 - % of invoices transacted via EDI

IM08 - % of shipments for which a despatchadvise was transmitted via EDI

IM10 - % of sales with synchronized master databetween trading partners via the GDSN

IM09 - % of shipments for which a receivingadvise was transmitted via EDI

2006 survey

2009 survey

Improvement

Those companies believe in the use of standards and for this reason they continue to improve the implementation level. The sample developed with a annual revenue growth rate (CAGR) of almost 8% per year.


Implementation of standards in practice


Implementation Drivers


Generally companies tend to implement the standards they use in their company at a high level

n=4571, GCI n=243

Visionaries

1 5 6 10Number of standards implemented

1%50

%51

%10

0%

Ave

rage

impl

emen

tatio

n le

vel o

f st

anda

rds

impl

emen

ted

16%52%

28% 4%


n=4571, GCI n=242

We have almost the same picture for the CGF members, with

even more results for the CGF members in

the upper right quadrant

Visionaries


1%50

%51

%10

0%

Ave

rage

impl

emen

tatio

n le

vel o

f st

anda

rds

impl

emen

ted

All: 16%All: 52%

All: 28% All: 4%

GCI: 38% GCI: 57%

GCI: 1% GCI: 4%

GCI and CGF member lead the implementation – significant correspondence between Implementation and GCI membership, independently if they are manufacturers or retailers & wholesalers

Currently testing: how did the CP

industry perform vs the GCI sample

(higher performance?)


Visionaries


1%50

%51

%10

0%

Ave

rage

impl

emen

tatio

n le

vel o

f st

anda

rds

impl

emen

ted

16%52%

28% 4%

The manufacturer drive the implementation, however ….

Manufacturer: 54%

Retailer & Wholesaler: 44%

Manufacturer: 24%


Manufacturer: 18%


Manufacturer: 4%



Visionaries


1%50

%51

%10

0%

Ave

rage

impl

emen

tatio

n le

vel o

f st

anda

rds

impl

emen

ted

Inventory cover: 52,2 days

…the retailer and wholesaler should even implement more standards and on a higher level, as the retail store inventory cover shows much better results for the visionaries

Inventory cover: 25,6 days

-26,6 days


The size of the company (manufacturers and retailers & wholesalers) corresponds directly with the number of standards implemented

210

1083 1064

667

499

357 336283

16189

33

0

200

400

600

800

1000

1200

0 1 2 3 4 5 6 7 8 9 10

Number of standards implemented

Nu

mb

er o

f co

mp

anie

s

0

2000

4000

6000

8000

10000

12000

14000

Averag

e revenu

e

Number of companies

Average revenue

n=4779

A correlation between the revenue and the average

level of the measures implemented is supported

by the data only for the manufacturers, but not for the wholesalers & retailers

Note: „No IM implemented“ are either based on a „0“ or a blank entry


The size of the company positive correlates with all the level of individual measures for the manufacturers

GDSN Implementation Measure by size of company

5,2%

7,9%

33,5%

0%

10%

20%

30%

40%

IM10 % of orders transacted via EDI

Small companies <1m$

Medium companies 1-20m$

Large companies >20m$


EDI Implementation Measures by size of company

8% 7% 6%3%

21%

12% 14%

6%

62% 64%

48%41%

0%

20%

40%

60%

80%

100%

IM06 % of orders transacted via EDI IM07 % of invoices transacted viaEDI

IM08 % of shipments for which adespatch advise was transmitted

EDI

IM09 % of shipments for which areceiving advise was transmitted EDI

Small companíes <1m$

Medium companies 1-20m$

Large companies >20m$

The size of the company positive correlates with all the level of individual measures for the manufacturers


The fresh food & perishable produce industry is the driver of implementing measures (revenue-weighted averages), independently of the size of the company

Average implementation level and number of measures implemented

55%

60%

65%

70%

75%

80%

0 1 2 3 4 5 6Number of Measures implemented

Ave

rag

e im

ple

men

tati

on

leve

l of

all

IM im

ple

men

ted

n=4779

Books, Journals, Music, Video

Heath & Beauty

Electrical Goods

Textile

Multiple product categories (incl. fresh food)

Dry Grocery, non food

Multiple product categories (without fresh food)

Fresh FoodDry Grocery (Food)

Home Improvement

Hardware


Companies dealing with fresh & perishable food have a shorter lead time than those companies without fresh food

Lead time (hours)

53,5

56,4

Companies with freshfood

Companies w/ freshfood

-3,2h shorter lead time


GCI results


3-year Results for GCI Members Revenue-weighted Average for Implementation Measures

GCI Manufacturers GCI Retailers & Wholesalers

2007 2008 2009 2007 2008 2009








IM09 % of shipments for which a receiving advice was transacted via EDI 9.1 4.8 11.8 46.9 4.1 **

IM10 % of sales with synchronized master data between trading partners via the GS1 GDSN 22.6 24.6 30.4 15.3 25.7 **

IM11 % of sales with master data loaded into a GS1-certified data pool63.4 60.7

IM12 % of active SKUs where the master data has been synchronized using the GS1 GDSN 4.0 3.1


** insufficient data available to produce a benchmark, n<5

Note: Sample for 2009 contains 243 scorecards submitted by 219 GCI manufacturers and 24 GCI retailers & wholesalers


GCI Manufacturers are ahead of the non-CGF-members in implementing Measures

80%

30%

12%

35%

54%

49%

50%

69%

91%

99%

49%

13%

24%

32%

31%

41%

51%

62%

79%

83%

0% 20% 40% 60% 80% 100%

Product classification

Sales with synch. Data

EDI Receiving Advice

EDI Despatch Notes

EDI Invoices

EDI Orders

GLN

SSCC Pallet

GTIN Case

GTIN Consumer Unit

Non-CGF members

GCI members

Should I use another

grouping?


84%

92%

90%

94%

88%

99%

100%

23%

16%

17%

46%

41%

46%

43%

73%

85%

0% 20% 40% 60% 80% 100%

Sales with synch. Data

EDI Receiving Advice

EDI Despatch Notes

EDI Invoices

EDI Orders

GLN

SSCC Pallet

GTIN Case

GTIN Consumer Unit

Non-CGF members

GCI members

GCI retailers & wholesalers are ahead of the non-CGF-members in implementing measures


Success Factors for implementation

1.) Pilot projects as entry point

- Top management commitment - Part of the company’s business strategy- Specific capabilities

2.) The selection of project partner

- Open to using standards and sharing information - Realistic scope has to be defined - A level of trust between the trading partners

3.) Quick adoption into normal working processes

- Require often changes in the organization- Standard’s adoption should be tracked - Benefits reported internally (The Global Scorecard and KPIs)

*The case of ECR, ECR Europe Academic Partnerchip and IBM Global Business Services


Implementing Standards require structure

Evaluate

Plan

Cultural Intervention

Align Goals& Objectives

AlignMeasures

& Incentives


Participation


Taking only the consumer products companies in consideration, the manufacturers and the retailers & wholesalers represent the strongest groups with 96% of the scorecards and 98% of the total revenue

CP KPI Scorecards by Business Type 2009

Others; 105; 2%Wholesalers; 455; 9%

Retailers; 256; 5%

Packaging Suppliers; 42;

1%

Raw Material Suppliers; 29;

0.6%Manufacturers;

4068; 82%

KPIs Revenue in $m by Industry Sector 2009

Manufacturers; 810266; 50%

Retailers; 753430; 46%

Packaging Suppliers; 9110;

0.6%

Raw Material Suppliers; 3210;

0.2%

Others; 17048; 1%Wholesalers;

33813; 2%

For the whole analysis we only consider

CP Manufacturers, Retailers and Wholesalers

Manufacturers 4,068

Wholesalers 455

Retailers 256

Total 4,779


Consumer products companies represent the vast majority of the total sample

KPI Scorecards Breakdown by Industry Sector 2009

Automotive; 14 0.2%Other; 415

7%

Aerospace; 2 0.04%

Chemicals; 39 0.7%Health Care; 196

3.5%

CP; 495189%

KPIs Revenue in $m by Industry Sector 2009

CP; 1626420; 90%

Other62074; 3.4%

Health Care 57971; 3%

Aerospace602; 0.03%

Automotive 2861; 0.2%

Chemicals 75189; 4%


The consumer products manufacturers are overrepresented with regard to the submitted scorecards, compared to their overall revenue

CP Manufacturers KPI Scorecards by Region 2009

South America; 21; 0.5%


Asia & Middle East; 26; 0.6%

Europe; 3716; 91%

Australasia; 12; 0.3%

Africa ; 9; 0.2%

CP Manufacturers KPIs Revenue in $m by Region 2009

South America; 13935; 2%

Europe; 545368; 67%

Asia & Middle East; 28544; 4%

Australasia; 8382; 1%

Africa ; 942; 0.1%



Most of the consumer products retailers & wholesalers participating in the survey come from Europe, while nearly half of the revenue represented comes from North America

CP Retailers KPI Scorecards by Region 2009

Europe; 656; 93%

Australasia; 3; 0%




CP Retailers KPIs Revenue in $m by Region 2009

Europe; 405715; 52%



Australasia; 29877; 4%



•Implementing and using standards delivers clear benefit•Significant opportunities remain•Using standards as competitive advantage•Using data for analytics•Jointly satisfying our customers

Summary


Tables for Consumer Products Manufacturers, Retailers & Wholesalers

CK: Following slides are only

for the presentation


3 year Results for Enablers Scores Worldwide (Revenue-weighted Averages*)


2007 2008 2009 2007 2008 2009

E1 – Common Identification Standards

E0101 GTIN at Consumer Unit Level 3.8 3.3 2.8 3.9 3.5 3.8

E0102 GTIN at Trade (Case; Cartons) Unit Level 3.7 3.2 3.2 3.3 3.2 3.5

E0103 Serial Shipping Container Code (SSCC) 2.9 2.6 3.1 2.4 2.3 3.3

E0104 Global Location Number (GLN) 2.5 2.2 2.0 2.7 2.8 3.5

E0105 Electronic Product Code (EPC)1.6 1.7 1.0 1.8 1.7 2.3

E0106 Product Classification Standards 2.5 2.5 3.2 1.3 1.4 2.8

E2 – Use of Electronic Message Standards

E0201 Electronic Messages for Supply 3.2 2.9 2.4 3.4 3.4 3.5

E0202 Electronic Messages for Planning, Forecasting and Replenishment2.2 1.9 1.5 2.9 2.7 3.4

E0203 Electronic Messages for Master Data2.5 2.2 1.5 2.5 2.3 3.4

E3 – Global Data Synchronization

E0301 Global Data Synchronization 2.7 2.8 2.6 2.3 2.2 3.0

E0302 Data Quality 2.1 2.4 3.1 2.1 2.1 3.3

E4 – Trading Partner Performance

E0401 Use of GS1 Standard Trading Partner Performance Measure 0.4 0.1

Note: Scale from 0 (Nothing planned) to 4 (Fully implemented)* Revenue-weighting averages: measures are weighted with their individual revenue in order to balance small and large companies results.


3 year Results for Business Measures Worldwide (Revenue-weighted Averages)


2007 2008 2009 2007 2008 2009

BM01 Annual Growth Rate (%) 5.3 5.9 3.1 4.9 4.3 6,6

BM02 Supplier Service Level/Unit Fill Rate to Customer Distribution Center (%) 95.1 96.7 97.8 90.0 89.9 90.9

BM03 Store Service Level/Unit Fill Rate to Customer Distribution Centre (%) 96.0 96.3 93.6 93.3 92.8 90.6

BM04 On-Time Delivery (%) 91.9 92.1 91.7 87.9 86.0 89.1

(BM05) OM18 (in 2009 survey) Perfect Order Rate (%) 86.8 88.4 68.6 85.1 77.3 **

BM06 Raw Materials Inventory Cover (days) 18.1 19.8 15.4

BM07 Manufacturer/Supplier’s Finished Goods Inventory Cover (days) 32.6 35.7 31.4

BM08 Retail Distribution Centre Inventory Cover (days) 15.3 20.7 13.1

BM09 Retail Store inventory Cover (days) 23.7 30.1 37.6

BM10 On-Shelf/Point-of-Sales Out-of-Stocks (%) 5.1 4.7 3.9 3.8 4.8 3.5

BM11 Order to Delivery Cycle Time (hours) 85.6 68.0 62.8 62.2 46.3 50.5

BM12 Distribution Costs (% of sales value) 7.6 7.0 7.9 3.4 4.9 2.9

BM13 Invoice Accuracy (%) 94.4 93.8 96.4 90.1 84.7 82.0

BM14 Retail Shrinkage Rate (%) 1.6 1.5



3 year Results for Implementation Measures Worldwide (Revenue-weighted Averages)


2007 2008 2009 2007 2008 2009








IM09 % of shipments for which a receiving advice was transacted via EDI 7.1 12.0 16.0 29.8 13.9 58.4

IM10 % of sales with synchronized master data between trading partners via the GS1 Global Data Synchronization Network 13.5 19.0 24.4 9.4 17.0 42.4

IM11 % of sales with master data loaded into a GS1-certified data pool (%) 37.7 41.6 **

IM12 % of active SKUs where the master data has been synchronized using the GS1 Global Data Synchronization Network 2.9 7.0 26.5




Consumer Products Manufacturers Worldwide Results for Enablers (Revenue-weighted Averages)

Consumer Products Manufacturers

2006 2007 2008 2009

Weighted average

Sample Size

Total revenue (millions of

US$)

Weighted average

Sample Size


US$)

Weighted average

Sample Size


US$)

Weighted average

Sample Size


US$)

E1- Common Identification Standards

E0101 GTIN at Consumer Unit Level 3.6 280 322,731 3.8 301 311,746 3.3 845 575,733 2.8 961 626,238

E0102 GTIN at Trade (Case; Carton) Unit Level

3.4 284 323,951 3.7 301 313,206 3.2 844 575,731 3.2 651 375,421

E0103 Serial Shipping Container Code (SSCC)

3.0 281 322,164 2.9 299 312,638 2.6 821 572,367 3.1 503 331,817

E0104 Global Location Number (GLN) 2.2 285 318,985 2.5 296 311,620 2.2 823 572,709 2.0 628 565,611

E0105 Electronic Product Code (EPC) 1.5 279 317,658 1.6 296 311,572 1.6 957 597,255 1.0 1541 686,156

E0106 Product Classification Standards 1.9 279 300,610 2.5 297 301,778 2.5 835 565,291 3.2 308 317,927

E2- Use of Electronic Message Standards

E0201 Electronic Messages for Supply 3.2 283 318,762 3.2 302 313,435 2.9 827 573,221 2.4 863 622,759

E0202 Electronic Messages for Planning; Forecasting and Replenishment

2.3 231 265,659 2.2 297 308,160 1.9 824 572,817 1.5 795 614,139

E0203 Electronic Messages for Master Data

2.5 229 262,729 2.5 300 313,293 2.2 823 572,789 1.5 651 612,482

E3- Global Data Synchronization

E0301 Global Data Synchronization 2.7 284 314,764 2.7 299 312,982 2.8 1339 627,198 2.6 1467 600,460

E0302 Data Quality 2.0 209 254,227 2.1 287 308,232 2.4 832 575,212 3.1 266 318,734

E4- Trading Partner Performance Measurement

E0401 Use of GS1 Standard Trading Partner Performance Measures

** <5 ** ** <5 ** ** <5 ** 0.4 232 292,256



Consumer Products Manufacturers Worldwide Results for Business Measures (Revenue-weighted Averages)


2006 2007 2008 2009

Weighted average

Sample Size

Total revenue (millions of US$)

Weighted average

Sample Size


US$)

Weighted average

Sample Size


US$)

Weighted average

Sample Size


US$)

BM01 Annual Growth Rate (%) 5.6 199 216,272 5.5 205 244,456 6.0 331 242,649 3.1 295 284,927

BM02 Supplier Service Level / Unit Fill Rate to Customer Distribution Centre (%)

97.6 254 231,228 95.1 201 260,308 96.7 365 320,207 97.8 317 272,767

BM03 Store Service Level / Unit Fill Rate (%)

97.1 101 119,999 96.0 88 128,780 96.5 174 113,050 93.6 208 202,331

BM04 On-Time Delivery (%) 91.6 236 245,124 91.9 242 271,871 92.1 372 314,072 91.7 305 272,638

(BM05) OM18 in the 2009 survey Perfect Order Rate (%)

79.9 159 164,902 86.8 98 128,559 88.3 300 68,333 68.6 14 2,983

BM06 Raw Materials Inventory Cover (days)

21.3 138 172,679 18.1 119 210,495 20.0 229 171,650 15.4 148 226,781

BM07 Manufacturer/Supplier's Finished Goods Inventory Cover (days)

32.3 219 238,562 32.5 190 259,787 35.7 318 261,713 31.4 220 274,751

BM10 On-Shelf/Point-of-Sale Out-of-Stocks (%)

4.8 124 185,132 5.1 105 196,692 4.8 183 156,330 3.9 128 211,299

BM11 Order to Delivery Cycle Time (hours)

77.4 257 239,970 86.0 255 273,439 68.1 305 242,680 62.8 308 286,493

BM12 Distribution Costs (% of sales value)

7.6 210 223,800 7.7 219 217,720 7.0 271 220,440 7.8 215 274,018

BM13 Invoice Accuracy (%) 94.4 223 201,975 94.4 161 148,506 93.9 246 143,708 96.4 285 226,799



Consumer Products Manufacturers Worldwide Results for Implementation Measures (Revenue-weighted Averages)


2006 2007 2008 2009

Weighted average

Sample Size


US$)

Weighted average

Sample Size


US$)

Weighted average

Sample Size


US$)

Weighted average

Sample Size


US$)

IM01 % of consumer units allocated a GTIN

99.2 621 453,451 97.1 1718 579,712 96.8 1914 683,851 92.0 3964 792,408

IM02 % of cases/cartons/inners allocated a GTIN

95.0 605 364,489 82.8 1799 580,033 87.5 1827 670,918 86.6 2541 692,032

IM04 % of pallets/unit loads labeled with SSCC

46.8 562 399,755 45.6 1865 604,795 49.0 2006 737,064 67.2 2811 714,890

IM05 % of shipping or receiving locations that have been allocated a GLN

34.7 594 430,135 43.6 1836 592,570 41.1 2165 747,590 51.1 3361 745,563

IM06 % of orders transacted via EDI 50.4 588 398,749 52.5 1834 595,180 52.0 2121 722,479 47.0 3130 662,859

IM07 % of invoices transacted via EDI 41.9 595 402,650 41.5 1844 583,059 47.9 2097 737,710 45.6 2901 636,894

IM08 % of shipments for which a despatch advice was transmitted via EDI

21.1 484 323,762 22.2 1814 540,710 27.4 2048 714,796 35.5 2744 593,398

IM09 % of shipments for which a receiving advice was transacted via EDI

7.9 472 309,069 6.7 1827 535,302 11.7 2029 709,219 16.0 1805 416,648

IM10 % of sales with synchronized master data between trading partners via the GDSN

13.1 552 403,802 13.6 1781 549,088 19.1 1657 642,927 24.4 1964 465,984

IM13 % of GTINs that are catalogued consistently with a GS1 Global Product Classification brick code

46.5 465 420,036 45.6 969 520,751 47.0 1746 694,225 71.0 1824 487,952


Consumer Products Retailers and Wholesalers Worldwide Results for Enablers (Revenue-weighted Averages)

Consumer Products Retailers & Wholesalers

2006 2007 2008 2009

Weighted average

Sample Size


US$)

Weighted average

Sample Size


US$)

Weighted average

Sample Size


US$)

Weighted average

Sample Size


US$)

E1 - Common Identification Standards

E0101 GTIN at Consumer Unit Level 3.7 76 554,393 3.9 118 774,603 3.5 385 802,612 3.8 406 478,389

E0102 GTIN at Trade (Case; Carton) Unit Level

2.9 75 553,993 3.3 117 774,093 3.2 385 802,612 3.5 240 455,618

E0103 Serial Shipping Container Code (SSCC)

2.6 71 526,968 2.4 116 773,825 2.3 382 800,719 3.3 125 451,555

E0104 Global Location Number (GLN) 2.8 73 547,368 2.7 117 774,093 2.8 385 802,612 3.5 163 473,153

E0105 Electronic Product Code (EPC) 2.0 75 548,393 1.8 117 774,602 1.7 477 830,037 2.3 411 550,978

E0106 Product Classification Standards 1.7 75 554,293 1.3 116 774,334 1.4 385 802,612 2.8 46 423,393

E2 - Use of Electronic Message Standards

E0201 Electronic Messages for Supply 3.5 76 554,393 3.4 118 774,603 3.4 383 795,908 3.5 377 475,326


3.1 75 537,193 2.9 116 723,799 2.7 384 795,912 3.4 320 447,656

E0203 Electronic Messages for Master Data

2.7 76 554,393 2.5 117 774,335 2.3 384 795,912 3.4 303 448,444

E3 - Global Data Synchronization

E0301 Global Data Synchronization 2.2 75 554,293 2.3 118 774,603 2.2 774 829,940 3.0 355 523,669

E0302 Data Quality 1.5 34 482,467 2.1 116 774,334 2.1 383 795,911 3.3 43 423,365

E4 - Trading Partner Performance Measurement


** <5 ** ** <5 ** ** <5 ** 0.1 37 422,322



Consumer Products Retailers and Wholesalers Worldwide Results for Business Measures (Revenue-weighted Averages)


2006 2007 2008 2009Weighted average

Sample Size


Weighted average

Sample Size


Weighted average

Sample Size


Weighted average

Sample Size


BM01 Annual Growth Rate (%)

4.2 70 430,134 4.9 87 602,855 4.3 142 552,294 6.6 37 363,375


89.0 46 403,712 90.0 60 506,740 89.9 88 571,637 90.9 32 337,115


93.7 75 246,610 93.3 70 300,519 92.8 101 305,009 90.6 41 60,786

BM04 On-Time Delivery (%) 86.2 63 435,240 87.9 93 581,696 86.0 133 565,741 89.1 47 360,405

(BM05) OM18 in 2009 survey - Perfect Order Rate (%)

83.0 12 340,528 85.1 14 383,498 77.3 79 82.853 ** <5 **

BM08 Retail Distribution Centre Inventory Cover (days)

15.4 60 201,019 15.3 60 322,637 20.7 74 215,569 13.1 15 37,452

BM09 Retail Store Inventory Cover (days)

25.6 74 218,128 23.7 79 308,441 30.1 88 241,363 37.6 24 60,205


3.8 51 415,823 3.8 68 512,762 4.8 80 500,659 3.5 15 338,927


63.2 78 466,373 62.2 73 518,522 46.3 100 552,527 50.5 43 360,383

BM12 Distribution Costs (% of sales value) (%)

3.0 51 218,287 3.4 67 307,566 4.9 83 243,687 2.9 15 8,950

BM13 Invoice Accuracy (%) 88.3 64 444,779 90.1 72 547,133 84.7 88 517,934 81.9 32 311,295

BM14 Retail shrinkage rate (%)

** <5 ** ** <5 ** 1.6 62 121,292 1.5 12 8,873



Consumer Products Retailers and Wholesalers Worldwide Results for Implementation Measures (Revenue-weighted Averages)


2006 2007 2008 2009Weighted average

Sample Size


Weighted average

Sample Size


Weighted average

Sample Size


Weighted average

Sample Size



97.8 164 525,759 91.7 548 990,651 97.3 619 899,108 96.6 635 750,769


91.8 125 522,379 77.4 485 880,492 82.6 560 832,410 86.6 483 687,952


59.0 137 501,925 51.1 503 895,783 49.4 600 857,712 71.6 394 670,983


62.9 159 531,674 64.3 532 974,626 74.5 804 919,050 87.5 387 756,492

IM06 % of orders transacted via EDI

81.8 130 519,895 68.8 536 932,876 70.4 655 858,514 75.8 558 684,560

IM07 % of invoices transacted via EDI

76.9 132 520,279 63.4 540 999,769 67.1 662 882,635 78.62 541 733,748


10.8 121 278,561 28.0 518 916,380 22.4 604 532,810 58.7 508 668,761


7.4 121 296,563 29.8 513 899,250 13.9 598 547,128 58.4 393 588,322


11.4 154 531,768 9.4 500 850,983 17.0 381 683,823 42.4 150 459,139

IM12 % of active SKUs where the master data has been synchronized using GDSN

** ** 2.9 448 711,893 7.0 354 673,150 26.5 84 519,230



Regional Breakdown – Consumer Products Manufacturers - Enabler (Revenue-weighted Averages)

North America South America Europe Asia Australasia

20th Centile*

Weighted average

80th Centile

20th Centile

Weighted average

80th Centile

20th Centile

Weighted average

80th Centile

20th Centile

Weighted average

80th Centile

20th Centile

Weighted average

80th Centile


E0101 GTIN at Consumer Unit Level 3.5 4 4 4 4.0 4 1 1.9 4 3 3.9 4 2.5 3.9 4

E0102 GTIN at Trade (Case;Carton) Unit Level 2 3.6 4 4 3.9 4 0 2.2 4 2 3.8 4 3.5 4 4

E0103 Serial Shipping Container Code (SSCC) 0 3.5 2 0 0.8 1 0 3 4 0 0.6 2 0 3.4 4

E0104 Global Location Number (GLN) 0 2.9 3.5 0 3.1 4 0 1.3 3 0 1.4 2 1 2.9 4

E0105 Electronic Product Code (EPC) 0 1.9 0 0 0.9 1 0 0.5 0 0 0.2 0 0 0 0

E0106 Product Classification Standards 0 3.7 3.5 0 2.8 4 0 2.3 4 0 0.4 1 0 1.8 4


E0201 Electronic Messages for Supply 0 3.4 3.5 2 3.3 4 0 1.7 2 1 1.8 3 3 3.4 4

E0202 Electronic Messages for Planning; Forecasting and Replenishment 0 2.6 2 0 1.9 3.5 0 0.8 1 0 0.6 2 0 0 0

E0203 Electronic Messages for Master Data 0 2.9 3.5 0 0.9 3 0 0.8 1 0 0.2 0.5 0.5 1.5 2.5


E0301 Global Data Synchronization 0 3.8 4 0 1.8 3 0 1.9 0.5 0 1.1 1.5 0.5 2.7 4

E0302 Data Quality 0 3.4 3.5 0 2.1 3 0 2.3 3 0 2.3 2 0.5 2.2 3


E0401 Use of GS1 Standard Trading Partner Performance Measures 0 0.3 0.5 0 0.8 0 0 0.7 1 0 0.1 0 0 0 0.5

* A centile is the value of a variable below which a certain percent of observations fall.


Regional Breakdown – Consumer Products Manufacturers – Business Measures (Revenue-weighted Averages)

North America South America Europe Asia

20th Centile

Weighted average

80th Centile

20th Centile

Weighted average

80th Centile20th

CentileWeighted average

80th Centile

20th Centile

Weighted average

80th Centile

BM01 Annual Growth Rate (%) 2 2.8 18 3.9 17.8 21.2 -4 0.4 4.4 -1.5 -0.4 15


90 98 100 92.7 94.6 97.3 96 97.6 99.1 94.6 98.8 99.3


90 92.7 100 ** 94 ** 95 97.9 98.6 ** 97.3 **

BM04 On-Time Delivery (%) 90 90.4 100 85 87.9 96.7 96.4 94.4 99.5 92.9 98.8 99.9

BM06 Raw Materials Inventory Cover (days)

9 12.1 65 17.8 27.4 53 10 20.2 28 10 18.3 24

BM07 Manufacturer/Supplier's Finished Goods Inventory Cover (days)

10 28.9 60 26.8 40.2 72.1 23.8 32 72 31.9 39.6 86.5


0 3.2 8 ** 13.8 ** 2.8 5.2 8 ** 4.6 **


24 61.4 145 57 77.9 103.8 48 64.5 72 24 31 72

BM12 Distribution Costs (% of sales value)

3.8 8.9 13 3.7 6.9 8 3 5.5 6.5 3.2 5.3 5.8

BM13 Invoice Accuracy (%) 90 96.1 100 ** 96.2 ** 91.3 96.1 98 95.4 98.7 99.8

Note: Sample for Australasia is too small for a Business Measure analysis; not enough data for Perfect Order Rate



Regional Breakdown – Consumer Products Manufacturers – Implementation Measures (Revenue-weighted Averages)

North America South America Europe Asia Australasia

20th Centile

Weighted average

80th Centile

20th Centile

Weighted average

80th Centile

20th Centile

Weighted average

80th Centile

20th Centile

Weighted average

80th Centile

20th Centile

Weighted average

80th Centile


90 99.6 100 100 100 100 15 88.4 100 100 100 100 100 99.2 100


10 90.3 100 100 98.7 100 5 83.5 100 99 98 100 100 99.2 100


0 61 15 0 16.8 0 0 73.8 90 0 9.2 5 0 77 100


0 48.4 100 0 76.8 100 0 53.4 100 0 13.1 20 0 56.2 100

IM06 % of orders transacted via EDI 0 53.3 89 26 60 60 0 43.6 44.5 0 25.6 80 1 74.3 80

IM07 % of invoices transacted via EDI

0 62.8 89 0 45.7 38 0 37.4 25 0 15.6 38.9 5 44.5 60


0 48 50 0 9.2 20 0 32.8 31 0 6.7 5 0 18.6 24


0 19.6 30 0 6.1 0 0 14.7 0 0 0.8 0 0 14.6 20


0 36.2 50 0 3.2 10 0 16.2 0 0 0 0 0 34 50

IM13 % of GTINs that are catalogued consistently with a GS1 Global Product Classification brick code

0 91.7 100 0 36.3 100 0 60.8 90 0 2.0 0 0 63.1 100


Regional Breakdown – Consumer Products Retailers & Wholesalers - Enablers (Revenue-weighted Averages)

North America Europe

20th Centile

Weighted average 80th Centile

20th Centile

Weighted average 80th Centile


E0101 GTIN at Consumer Unit Level 3 4 4 1 3.4 3

E0102 GTIN at Trade (Case;Carton) Unit Level 1 3.7 4 0 2.5 2

E0103 Serial Shipping Container Code (SSCC) 0 3.5 1.5 0 2.3 3

E0104 Global Location Number (GLN) 0 3.6 3 0 3.1 3

E0105 Electronic Product Code (EPC) 0 3.1 0 0 0.9 0

E0106 Product Classification Standards 0 3.1 3 1 2 1


E0201 Electronic Messages for Supply 0 3.9 3.5 0 1.7 1


0 3.9 2 0 1.6 0

E0203 Electronic Messages for Master Data 0 3.9 3 0 2.1 0


E0301 Global Data Synchronization 0 3.9 3.5 0 1.3 0

E0302 Data Quality 0 3.8 2 0 1.5 2.5



0 0 0.5 0 1.2 0

Note: Insufficient data for South America, Asia and Australasia


Regional Breakdown – Consumer Products Retailers & Wholesalers – Business Measures (Revenue-weighted Averages)



20th

CentileWeighted average

80th Centile

20th Centile

Weighted average80th

Centile

BM01 Annual Sales Growth Rate (%) 1.5 7.1 50 -9.9 -2.3 2.6


85 90.5 99.5 ** ** **

BM03 Store Service Level / Unit Fill Rate (%) 80 94.7 100 80 85.3 88

BM04 On-Time Delivery (%) 90 88.5 100 82 86.9 90

BM08 Retail Distribution Centre Inventory Cover (days)

** 16.4 ** ** ** **

BM09 Retail Store Inventory Cover (days) ** 21.1 ** 45 61.9 65


1 3.6 20 ** ** **

BM11 Order to Delivery Cycle Time (hours) 30 48.0 72 36 49.9 68

BM12 Distribution Costs (% of sales value) (%) ** 3.0 ** ** ** **

BM13 Invoice Accuracy (%) 90 81.9 100 ** ** **

BM14 Retail shrinkage rate (%) ** 3.4 ** ** ** **



Regional Breakdown – Consumer Products Retailers & Wholesalers – Implementation Measures (Revenue-weighted Averages)



20th Centile Weighted average 80th Centile 20th Centile Weighted average 80th Centile

IM01 % of consumer units allocated a GTIN 75 98.8 100 25 94.2 100


10 98.6 100 0 72.2 100

IM04 % of pallets/unit loads labeled with SSCC 0 88.7 0 0 50.5 50


0 88.7 50 0 86.3 100

IM06 % of orders transacted via EDI 0 94.0 95 0 54.8 40

IM07 % of invoices transacted via EDI 0 96.7 90 0 61.9 25

IM08 % of shipments for which a despatch advice was transmitted via EDI 0 88.9 30 0 29.1 25


0 88.6 20 0 16.8 0

IM10 % of sales with synchronized master data between trading partners via the GS1 GDSN 0 53.5 70 0 10.3 0

IM12 % of active SKUs where the master data has been synchronized using the GS1 GDSN 0 33 35 0 14.1 0


Backup slides (not used slides)


Regional participation for the consumer products manufacturers, retailers & wholesalers is similar to the global one

0 2478

Scorecards

Range: 0 <5 5-89 90-168 169-2478 2478

Europe 4372

North America

333

South America

22

Asia 28

Australia 15

Africa 9

Europe+2304 Asia

-120

North America

-705

Would rather not include it –

shows the imbalance,

need to explain…


The total revenue of consumer products businesses participating in the global scorecard survey is decreasing, although on a high level

Revenue in m $ of Survey participants

0

500.000

1.000.000

1.500.000

2.000.000

2.500.000

2002 2003 2004 2005 2006 2007 2008 2009

KPIs



The number of submitted scorecards of consumer products companies increased again in 2009

Submitted Scorecards of CP Manufacturers, Retailers & Wholesalers

0

1.000

2.000

3.000

4.000

5.000

6.000

2002 2003 2004 2005 2006 2007 2008 2009

KPIs



Table: measure overviewImplementation measures

Business measures

Optional measures


Table: Enablers overview


Glossary

http://www.gs1.com/gdsn/ds/suppliers

ECR: Efficient Consumer ResponseGS1: Global StandardsGTIN:


Effects of ECR implementation


Benefits for SuppliersAccenture and Cap Gemini have published reports describing the business benefits of GDSN based on extensive research with major associations, suppliers and retailers, including Royal Ahold, The Coca-Cola Company, General Mills, The Hershey Company, The J.M. Smucker Company, Johnson & Johnson, Nestlé, PepsiCo, Procter & Gamble, Sara Lee, The Gillette Company, Unilever, and Wegmans. The results clearly show that synchronizing accurate and properly classified data brings many business benefits to suppliers. Time-to-shelf was reduced by an average of 2 to 6 weeks. Order & item administration improved by 67%. Item data issues in sales process were reduced by an average of 25% to 55%. Some other benefits manufacturers can get from implementing GDSN

Better Category & Promotion Management

Improved visibility for stock-level planning Maximized retail exposure and product posting Simplified/enhanced category reporting Quicker and easier new item introductions Shorter lead time on product promotions Easier to add or change catalogue items (or their prices)

Easier Administrative Data Handling

No need for cross-reference tables Fewer invoice disputes Fewer write-offs Fewer accounts receivable Fewer order defects Fewer downstream shipping and billing discrepancies

Smoother Logistics

Efficient order sizing from accurate weights & measures Easier order tracking and tracing Fewer return shipments Higher percentage of perfect orders Fewer emergency orders More accurate picking Optimized short-term planning

More Efficient Employees

Less administrative work means sales, buying & merchandising teams can focus on generating demand for product, growing business

Better Bottom Line

Increased sales


Business measures profit from implementing IMs (significant correlations)IM02 % of cases/cartons/inners allocated a GTIN

Supplier service level/Fill rate with the use of GTIN on cases/cartons/inners level

94,3%

93,1%

Implementation >50% ofGTIN consumer units

level

Implementation 1-50%of GTIN consumer units

level+1,2%


Business measures profit from implementing IMs (significant correlations)IM01 % of consumer units allocated a GTIN

Supply Chain costs with the use of GTIN on consumer units level

7,7%

8,2%

Implementation of GTINconsumer units level

No implementation ofGTIN consumer units

level

- 0,5%

Order to delivery-cycle time with the use of GTIN on consumer units level

56

203

Implementation of GTINconsumer units level

No Implementation ofGTIN consumer units

level

- 147h, -72%


On-Shelf/POS Out-of-stocks with a despatch advice via EDI

3,9%

4,0%

Using a despatch advicevia EDI

Not using a despatchadvice via EDI

Business measures profit from implementing IMs (significant correlations)IM08 % of shipments for which a despatch advice was transmitted via EDI

Store service level/Fill rate with a despatch advice via EDI

93,5%

91,8%

Using a despatch advicevia EDI

Not using a despatchadvice via EDI

+1,7%

- 0,1 %


Business measures profit from implementing IMs (significant correlations)IM10 % of sales with synchronized master data

Store service level/Fill rate with the use of synchronized master data for sales

93,2%

92,4%

Usage of synch. masterdata for sales

No usage of synch.master data for sales

+0,8%


Business measures profit from implementing IMs (significant correlations)IM13 % of GTINs that are catalogued consistently with a GS1 Global Product Classification brick code

Store service level/Fill rate with the use of Product classification

93,1%

92,7%



On-Shelf/POS Out-of-Stocks with the use of Product classification

3,8%

4,0%



Supplier Service Level/Fill rate with the use of Product classification

97,9%

92,2%



+0,4%

- 0,2 %

- 1,5%


Working together to fulfill consumer wishes better, faster and at less costIn creating the Efficient Consumer Response working model, the early adopters focused on two key principles:•Focus on consumers: A commitment to the belief that sustained business success stems only from providing consumers with products and services that consistently meet or surpass their demands and expectations. •Working together: The greatest consumer value can be offered only when organizations work together, both internally and with their trading partners, to overcome barriers that erode efficiency and effectiveness. Barriers can be seen both between trading partners and between business functions within one business. ECR attempts to break these barriers down.


Content

Introducing words/ A noteThere are many publications on ways to improve your business, however there is almost nothing available in the field of working together with

your business partners in an efficient way. We believe this study does just that.

The global scorecard survey is a voluntary project delivering a common tool, language and strictly anonymous and aggregated data. Although we have conducted this survey for 10 years, this year we have seen the highest participation with regard to the KPI’s ever. The study is co-led by the Consumer Goods Forum and IBM Global Business Services.

For the 2009 survey we have gathered and evaluated 5,624 responses from companies worldwide using Key performance measures, as well as 2,180 responses with standard capability assessments from all continents. This gave us valuable insights on an anonymous basis about their business.

This report will show not only what improvements have been made, but also how the implementation leads to business benefits in different areas. The results from the survey will demonstrate that there is not only further potential which can be lifted in your business when partnering but also gives evidence on how you boost your competitive capability through improved business measures (such as Fill rates, out of stock rate a.s.o.).

Our key finding is that companies notice this potential by using more and more of the interactive measures and improvements as described in detail in this report in order to profit from its benefit.

Letter from the co-chairs

The co-chairs


Summary

High participation around the globe from 50 countries, which makes the study becoming more relevant every year

Many new companies participate each year: this year 5,624 Scorecards for Key Performance Indicators (KPI) were submitted, compared to 3,630 in the previous year

CGF members submitted 549 KPI Scorecards

Wide range by size of companies: from very small companies to the big player (Out of the Fortune Global 500 more than 10% representative companies participated in the Global Scorecard survey this year – even 14% if we consider only the TOP 100)

Companies with a total revenue of over 1,800 billion US$ are represented in the survey

CP companies represent 89% of all Scorecards and 90% of the total turnover

For the analysis we take only into consideration Consumer Products manufacturers, retailer and wholesaler: 4,779 scorecards and 1,596 billion US$ revenue

The data is treated absolutely confidential as stated in the quality statement.

Highlights of the Sample of the global scorecard survey 2009

http://money.cnn.com/magazines/fortune/global500/2009/full_list/


Findings Implementation measures

GLN allocation to shipping or receiving locations, Global Location Number, a thirteen digit number used to identify parties and physical locations show a huge discrepancy between manufacturers, 51%, and retailers & wholesalers with 88%. The measure is more used by larger companies.

Shipments, for which a despatch advice was transmitted via EDI, are driven by the size of company for manufacturer. Retailer & wholesaler use it irrelevant of their size. The average weighted implementation level is in Northern America with almost 90% three times the value of the European level. Companies using a EDI for transmitting a despatch advice mostly use it also for the receiving advice, therefore the picture is similar. There is only a gap between the level of implementation for manufacturer – they use EDI for the despatch advice on a 36% implementation level while only on a 16% level for the receiving advice. In Northern America the implementation level for retailer & wholesaler is at around 89%, while it is only 17% for European ones.

Generally the lower values for Europe may be caused to due many new smaller companies which have participated in Europe in this year’s study.


345 key decision makers across 46 countries ranked their top priorities for the coming year. The result: in most of the top priorities standardization matters are a significant aspect

Source: http://www.ciesnet.com/pfiles/press_release/Press_Release_2010/2010_03_04_Top%20of%20Mind.pdf


Effects of ECR implementation


Case study Campina: GTIN http://www.gs1.com/traceability/support

Looking to Adopt the Global DataSynchronization Standard“Promises, Issues, and Perspectives”A Multi-stakeholder Case Studyof the French Retail Industry http://www.gs1.com/docs/gdsn/GDS_Study.pdf


How is the usage of the GS1 standards and the impacts of their implementation on their supply chain? In order to find out we have extensively analyzed over 5600 KPIs’ scorecards as well as over 2100 Enablers’ scorecards, which were submitted for this year’s survey. In the following we offer insights in the daily business of the companies worldwide. At its score, the primary findings arose from the analysis:

This report shows many examples where we see significant improvements for most of the standards. This conclusion can be supported by the fact that the “Panel sub-sample” (companies who have participated in all surveys) shows a reasonable increase trend over the last 4 years. Some of the standards, e.g. the standard SSCC (Serial Shipping Container Code), were strongly promoted by GS1 and therefore very positive results could be observed in this year’s survey. EDI is now well adopted, compared to 5 years ago.

Another reason for improving the GS1 standards is that companies experience substantial benefit through implementation. We have analyzed and identified that companies can significantly profit through implementing standards or improving the implementation level in many ways. Notable improvements are for example better fill rates, lower distribution costs, lower out-of stocks rate or a better invoice accuracy and therefore leads to more efficient supply chain. As we see a strong connection between the corresponding enablers and their implementation measures we assume data reliability.

As a part of our 2009 analysis, we were looking for who leads the GS1 implementation. Regarding the usage and the implementation level, the large Corporations, former GCI members, as well as the companies dealing with fresh food, drive the implementation. The role model status of the large Corporations motivates smaller companies to be “fast followers” of standards.

Sticking to one implementation level could be an indicator that companies don’t expect further benefits by increasing the implementation level. However, this study shows that this is not correct! We can demonstrate that increasing implementation levels means increasing benefits for the company.

Finally, the results from the survey will demonstrate that there is not only further potential regarding standards which can be lifted in your business but also gives evidence on how you boost your competitive capability through improved business measures. Your company should:

Executive Summary 1


97,8% 95,5%

59,0%

43,4%48%

24,8%

72,0%

0%

20%

40%

60%

80%

100%

GTIN consumerunit

GTIN cartons SSCC GLN EDI Global DataSynchronization

P roductClassification

Standard

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Enabler's Score

Enablers scores and the corresponding Implementation Measure Levels for manufacturers worldwide are on a similar level, showing a consistency in the data – however there is a enormous discrepancy with regard to the Global Data Synchronization measure. Companies have already built a lot of capability but with a limited use Version: only those who

have entered both, Enablers and

corresponding KPI; I tend to stick to slides 54 and 56

as results are similar


98,8%94,6%

87,2%90,3%

85,2%

47,4%

0%

20%

40%

60%

80%

100%

GTIN consumerunit

GTIN cartons SSCC EDI GLN Global DataSynchronization

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Enabler's Score

Enablers Scores and the Implementation Measure Levels for retailers & wholesalers fit better for the retailers & wholesalers – however there is again a discrepancy with regard to the Global Data Synchronization.

Version: only those who have entered both, Enablers and corresponding KPI

© 2009 IBM Corporation Utilizing GS1 Industry Standards – A way to improve your business Findings of the Global Compliance Survey 2009.

Documents

gs1 industry standards

gs1 standards usage

newer standards

standards executive

scorecard survey scorecards

data analytics

business case

business measures