Chris data crunch

IBM Global Business Services and IBM Software Group

The Data Crunch Report

The impact of bad data on the Retail and
Consumer Products Industry

ECR Asia-Pacific Conference
Kuala Lumpur, October 2010
Chris Cave Jones. IBM

© Copyright IBM Corporation 2009


Background to UK data crunch study
CIES Top of Mind

• No surprise, it’s the
economy &
consumer demand
that is #1

• Food Safety is still
very high priority

• Drive for Efficiency
and data quality
continues to
underpin all TOM
issues

600 decision makers in food and consumer goods across 54 countries

Page 2 © Copyright IBM Corporation 2009

IBM Confidential


Background

The evolving value chain of 2016



Background
The UK retail industry is behind the curve in addressing poor supply chain data

But “stars are aligning” - now is the time for the UK industry to address this issue

In tough economic Increasing demand for Increasing regulation
conditions the industry data from consumers – around food and product
needs to maximise nutrition, safety, lifestyle, safety and impact on the
efficiency environment, ethical environment

DATA CRUNCH PROJECT OBJECTIVES:
1. Understand the impact of inconsistent data on the UK supply chain (now and future)
2. Identify opportunities to increase efficiency and reduce costs
3. Collaborate with the stakeholders to agree and develop an industry action plan and solution


IBM Confidential


IBM’s Involvement

Following a tendering process, IBM were selected as GS1 UK’s partners for both software
and consulting services.

“This is the first time that such an exercise has been carried out on this scale. We are delighted to
work with IBM to analyse the data records we are being provided with. The combination of their
leading data analysis software and their unrivalled industry experience made the choice of IBM an
easy one,” commented Malcolm Bowden, Business Development Director, GS1UK.



IBM’s Involvement

Why IBM?

Requirements: IBM’s Capabilities:

1. Analytics tools: 1. Business Analytics & Optimisation:
Analytics functionality Advanced analytics software
Scalable Over 1 million records!
Adaptable Intuitive
Flexible Structured

2. Industry Knowledge 2. GBS Consulting Services:
Retail experience Worked with all major players
Supply Chain expertise Leaders in SCM
Real world insights Industry experienced


IBM Confidential


IBM’s Involvement
What we did

Obtained data files from retail partners
Step 1 Step 1

Reviewed each file for completeness using
Step 2 IBM Information Analyser software
Step 2

Matching of consumer unit and traded unit data between
Step 3 retailer files Step 3

Step 4 Requested supplier data Step 4

Reviewed supplier files for completeness using IBM
Step 5 Step 5
Information Analyser software

Matching of consumer unit and traded unit data
Step 6 between suppliers and retailers Step 6



Report Findings

UK grocery sector identifies opportunity to
better serve 21st century consumers

GS1 UK report highlights golden opportunity
to enhance consumer experience through
improved product information

Industry data standards to help manage the
demand for 4 fold increase in retail product
information

Opportunity to realise savings of £1 billion
over the next five years


IBM Confidential


Report Findings

Results 80% - average level of
retailer and supplier product
data inconsistency



Report Findings

Over time, retailers have found ways of minimising, avoiding and managing these issues…

Ch
an eck
PRODUCT FLOW
d data
Ti-Hi m Twrong or missing, Case weights inaccurate,
i-H
a receiving
causing in i o problems resulting in cage and trailer
sy tai consolidation
at RDCs andn n r Case dimensions wrong, fill problems
ste o ece
points causing cage and pallet fill
n
m loc ipt problems & inefficiencies
al
Product descriptions
differences, causing pricing
and replenishment
Incorrect product life data
RETAILER RDC confusion in stores
generates RDC rejections CONSOLIDATION STORE
FACTORY WAREHOUSE and waste
Product coding and different
hierarchies across retailers, G et sa
making data analysis m le
challenging m eas pIncorrect errors in space
s fr o item dimensions
m
Bar code errors causing “no
u causing
m ain re pro du supp liers scans” and impacting
sy D e tain in planning a
c ts systems , customer service
lo ga in
m stefilevinconsistencies
Price m elo s ys te ca l s pace ,
atc s p
resulting in high invoice RETAILER m
SUPPLIER hin to w
matching m or k
g workload HEAD OFFICE
HEAD OFFICE
Invoice matching errors po as e ake flow
resulting in late payment of
ss ffi inv
ibl cie oi
invoices e n t ce
as

DATA/INFORMATION FLOW
97.3%
ECR On-Shelf
Availability Survey
Aug 09
…it may not be efficient, but it isn’t really broken, so why fix it?


IBM Confidential


Report Findings

So what for Industry?

Retailers not using supplier data
Re-measuring within merchandising and depots
Duplication of effort
Suppliers sending sample products to different retailers
Suppliers’ effort to complete numerous different New Line Forms
Trading teams completing New Line Forms when data is fixed later in the
process

• Significant opportunities to better serve 21st century customer by
managing the 4 fold increase in retail product information

• Opportunity to realise huge savings over the next five years



Report Findings
Growing Data Requirements

GLOBAL LOCAL
SUPPLY CATALOGUE
SOURCING CALL CENTRE
MULTI-
CHANNEL
PRODUCT FLOW WEB

CONSUMER
DATA

RETAILER RDC
FACTORY CONSOLIDATION STORE
WAREHOUSE

RETAILER MOBILE
SUPPLIER NUTRITIONAL
HEAD OFFICE
HEAD OFFICE INFO

DATA/INFORMATION FLOW

CARBON DATA
PACKAGING
COMPLIANCE INFORMATION
TRACEABILITY


IBM Confidential


Report Findings

The future data needs

250
400%
40% of increase in
data
shoppers
required to
have specific be held by
dietary needs retailers
& need more
product info
66
Coke Retailing
Research Council



GS1 India – IBM Data crunch study

Retailers Manufacturers
Spensers Hindustan Unilever
Reliance Johnson & Johnson
Aditya Birla India Tobacco
Shoppers Stop Dabur


IBM Confidential


Initial data quality observations

Retailer 1 Retailer 2 Retailer 3 Retailer 4
Initial Observations
Available EAN codes for Analysis 1014 3265 1735 1313
Under the same retailer item code there are many EAN codes 60% 18% 43% 0%
attached
One EAN number attached to multiple item codes 0.4% 0.0% 0.0% 0.7%
Missing/Incorrect EAN Codes 3% 0% 0% 1%
MRP Missing 9% 4% 0% 0%
Vendor, Supplier product code missing 65% 100% 100% 100%
Shelf life blank or zero 51% 18% 24% 31%
Case configuration/ eaches in a case missing 5% 1% 0% 0%
Each L,W,H dimensions missing/incorrect 38% 1% 100% 100%
Each weight missing 9% 5% 99% 100%
case L,W,H dimensions missing 29% 100% 100% 100%
case Weight Missing 29% 100% 100% 100%

70% - 100% 40% - 70% Under 40%



Consumer Unit match across retailers

E x a c t M a tch

A ttribu te A tt ri b u te s A ttr ib u t es A tt r ib u te s
m a tc h e d m a tc h e d m a tc h ed
ac ro s s a ll 4 re ta ile r s a cro s s a n y 3 ret a ile r s ac ro s s a n y 2 re t a ile r s

E a c h es Pe r C a se
1% 22 % 66%
S h e lf L if e
7% 29 % 65%
MRP
4 2% 82 % 91%

• Th e sh e l f l i fe d a ta is c r it ic a l f o r e n su r in g pr o d u c t fre s h n e ss , D is c re pa n c y
Un de r 40 % M a tc h h e r e c a n h a v e fi n a n c i a l im p a c t a s w e l l sa fe t y c o n c e r n s

• C a s e c o n fi g ur a ti o n d a t a if in c o r re c t c a n a l so re s u l t in f in a n c i a l i m p a c t
4 0% - 70 % M a tc h i f u s e d i n c a l c u l a t in g th e u n it s re c e iv e d /i nv o i c e d

70 % - 100 % M a tc h • M R P is t he o n l y p a r a m e t e r w h i c h is a t a r e as o n a b le l e v e l (D isc rep an c y
a ttrib ut ab le t o hu m a n e rror and a ll s ys te m s no t u p da te d )


IBM Confidential


Consumer unit attribute match across 2 retailers

A t trib u te E x ac t M a tc h To ler a n c e 10 % +/-
A ttr ib utes A ttri bu te s
m atch ed m a tc h ed
ac ro ss an y 2 re tailers a cr oss an y 2 r eta ile rs

E ac h L en gt h
1% 2 3%
E ac h W idth
2% 1 3%
E ac h H ei gh t
7% 4 9%
Ea ch D im e ns ion Su m
3% 6 1%
E ac h V o lum e
1% 2 2%
Eac h N e t W eig ht
51 % 5 5%

U n d e r 4 0 % M a tc h • B e sid e s n e t w e ig h t t he d im e n sio n d at a i s in re d. T h e d im e nsio ns di d n o t m a tc h
be tw e e n R e ta ile rs
4 0 % - 7 0 % M a tc h
•E ve n a fte r a pp lyi n g a to l e ra nc e o f + /- 10 % n o ne o f the p ar am e te r s w e r e in
70 % - 10 0 % M atch g re e n



Consumer Unite Attribute match with 4 retailers by supplier

Attribute Sup plier 1 Sup plier 2 Supplier 3 Supplier 4

Eaches Per Case 3% 3% 0% 0%

Shelf Life 0% 0% 8% 0%

M RP 42% 23% 62% 33%

• Th er e is significan t discrepan cy between Retailer and Supplier data.
Und er 40% M atch • Ideally there shou ld not have been an y discrepan cy if the data from Suppliers
was u sed by Retailers with out any manu al intervention .
40% - 70% M atch
• Th is clearly shows th at Ret ailers are main taining th eir own version of data w hich
70% - 100% M atch is further impacted by manu al errors


IBM Confidential


Consumer unit attribute match across 2 retailers by supplier

S upp lier 1 Su pplier 2 Sup plier 3 Supplier 4
EXAC T MATCH
Each Net Weigh t 32% 67% 24% 0%
E ach Length 0% 0% 0% 0%
Each W idth 0% 0% 0% 4%
Each Height 0% 0% 0% 0%

Each Vo lu me 0% 0% 0% 0%

Supplier 1 Su pplier 2 Sup plier 3 Supplier 4
W IT H 10% T olerance

Each Net Weight 45% 70% 43% 19%
Each Length 29% 0% 22% 38%
Each Width 10% 0% 24% 42%
Each Height 48% 0% 18% 48%
Each Volu me 12% 0% 8% 23%



GS1 AUSTRALIA – IBM Organisations Involved - Grocery


IBM Confidential


GS1 AUSTRALIA – IBM Organisations Involved - Hardware



Process followed

What is being done

✓ Step 1 Obtained data files from retail partners
Step 1

✓
Reviewed each file for completeness using
Step 2 IBM Software Tools
Step 2

✓
Matching of consumer unit and traded unit data between
Step 3 retailer files Step 3

✓ Step 4 Requested supplier data
Step 4

✓
Reviewed supplier files for completeness using IBM
Step 5 software tools
Step 5

Matching of consumer unit and traded unit data
Step 6 between suppliers and retailers Step 6


IBM Confidential


Current Status

Australian Grocery retailer data analysed for
consistency & alignment with Supplier data

Australian Hardware retailer data analysed for
consistency & alignment with Supplier data

2.5 months of data review, clarification, and re-
submission in a number of circumstances.

Propose to lock data down for final report run by
October 8.

Commence data analysis after October 11.



What does this mean for companies?

RETAILERS: MANUFACTURERS:
Tackling data issues cannot wait What are the Retailer Agendas?

What does it mean? Do I become a Leader or Laggard?
Solution options
Internal IT impacts What does it mean?
Process impacts Solution options
Internal IT impacts
Where do I start? Process impacts

Drive competitive advantage? Where do I start?


IBM Confidential


What does this mean for companies?
GS1 STANDARDS
GS1’s Solution
Understand data

200+ Item standard attributes

Global Product Classification

Data Quality Framework

UK New Lines Form
Adopted so far by ASDA and JS
My PIM GDSN
Create, Cleanse and Exchange Data
Manage Data Facilitated
Allowing all GS1 UK supplier
for Industry
members to manage their master
data centrally as part of a by GS1 Enter once - publish to many
using a global standard network of
membership service interoperable data pools

Ensure all data is cleansed to GS1 One version of ‘the truth’ globally
standards held and accessible by all



How can IBM help?

Consulting: Software:
Thought Leadership Discuss the Information Agenda

Solution Design Infosphere:
Data Stage
Process Change Information Analyser

Systems Implementation MDM Server for PIM

Application Integration Traceability


IBM Confidential


Contacts

GBS
Chris Cave Jones
Growth Markets Software Lead for Consumer Products and Retail
Chris.cave.jones@sg.ibm.com
Tel: +65 9369 2114



Thank You

© Copyright IBM Corporation 2009

IBM Confidential

Chris data crunch

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