Levi's wanted to open a new flagship store in Singapore and increase sales at existing stores. This required quality data on real estate, demographics, products, inventory, sales, and customers. However, data challenges included outdated information, inaccuracies, and inconsistencies. To overcome this, Levi's standardized processes, used recent external data sources, conducted quality checks, and ensured data was up-to-date and an accurate representation of reality to make informed business decisions.

1. Data Quality Case Study
Retail Fashion Industry: Levi’s
JANANI JANARDHANAN: G1200842B
ANAND KRISHNA: G1200833A
OM GURU NARESH SREENIASAN: G1200860D
VENKATARAMANUJAM KANNAN: G1101791L
Oct 6 2012

2. Agenda
Characteristics of retail fashion industry
Challenges with data quality
Background of Levi’s
Assumptions and decisions made
Data, challenges and overcoming challenges
Conclusion
References

3. Characteristics of Retail Fashion industry
Fast moving Changing customer
products needs
Plethora of
High competition designs,
substitutes
Highly evolving Low barriers to
market entry and exit

4. Challenges with Data: How to identify quality data?
Market
Fashion
data
trends
Sales
data Customer
data
Competitor
Supplier
data data
Quality
data

5. Background
 Levi’s was founded in 1853 and is headquartered in California,
United States
 It is a global brand in the retail fashion industry and it has
high brand equity
 Customer loyalty and brand identity are core elements of
Levi’s business
Retail Strategy
• Chain and departmental stores
• Franchise stores ( approximately 1800 )
• Multi-brand specialty stores
• Mass channel retailers and licensees
• Online channel
• Discount stores

6. Levis retail statistics
Total number of stores 2300
Number of countries with 110
stores
Geographies Americas, Europe, Asia Pacific
Number of stores in various Americas:211
geographies Europe:178
Asia Pacific:109
Product line Jeans,casual pants,tops,
shorts,skirts,jackets,footwear accessories
Brands (asset of Levis) Levis, Dockers, Denizen, Signature
Levis & Dockers retail strategy USA: Chain retailers, departmental stores
EU & Asia Pacific: Departmental stores,
franchised stores ,specialty retailers
Signature retail strategy USA: Mass channel retailers
EU & Asia Pacific: Franchised stores
Denizen retail strategy USA & Mexico: Mass channel retailers
Asia Pacific: Franchised stores
There are around 18 original Levi’s stores in Singapore.
Source:Levi’s annual report 2011

7. Assumption:
Levi’s has two objectives this financial year:
1. To open a new “concept” store that builds on the brand imagery
1. To increase sales across existing stores
Decision 1:
Decision made by Levi’s- Open a new store in Singapore at
Orchard Road to build its brand and this store will be the
biggest retail fashion store on Orchard Road.
Decision 2:
Levi’s decides to increase sales volume for all
the existing stores in Singapore, next year.

8. Decision 1
Levi’s opens a new store in orchard road to build brand image
• Real estate, rentals and permission to open the store
1
• Demographics of target group
2
• Product and promotion mix
3
• Level of inventory to order and cost
4

9. 1. Real estate, rentals and permission to open the store
Overcoming
challenges
Challenges
1. Gathering
Data needed qualitative data
from competitors’
1. Timeliness of the
stores on layouts,
data.
rentals and store
2. If the permission
1. Obtained from size through
comes in late or if
the land mystery shopping
there is a time lag in
authorities in 2. Using best
response from the
Singapore practices from the
land authorities,
2. Permission has past to plan ahead
Levi’s would lose a
to be sought on on securing
potential
time from the government
opportunity to open
government to permission
a new store.
open the store.

10. 2. Demographics of target group
Overcoming
challenges
Challenges 1. Using economic
indicators such as
Data needed monthly Retail
1. Data gathered from Sales from Census
sentiment analysis, Bureau to predict
1. Level of social networking sites consumer
employment, can lack currency and spending.
family income, integrity. 2. Labour statistics
lifestyle and 2. Customers keep such as level of
customer changing their employment from
preferences preferences. department of
2. Collected through 3. Problems with labour is more
research agencies, accuracy, accurate and
focus groups and completeness, complete.
sentiment analysis. precision of data.

11. 3. Product and Promotion mix Overcoming
challenges
Challenges
1. To ensure product
Data needed 1. Mining of customer
and promotion mix is
relevant to the target
data from other group, recent research
1. Can be determined Levi’s stores can statistics and consumer
through level of lack currency. buying preferences
consumer demand 2. Customers’ level of should be used as a
and level of spending income, yardstick to design
confidence. employment and product and promotion
2. Mining of customer spending behaviour mix.
data from other would have changed
Levi’s stores over time and this
3. Data from will affect their
distributors on fashion trends.
market demand, new 3. Data may not be an
product catalogues accurate
and cost of purchase representation of
from manufacturers reality

12. 4. Level of inventory to order and cost
Overcoming
challenges
Challenges
1. To avoid the
inaccuracy of the
Data needed data, all stores
1. The challenge
associated with data should do a daily
on products from inventory count
1. Level of inventory to 2. Ensure data on
order based on other stores is
accuracy as it depends products is up to
consumer demand. date.
2. Data on fast moving on the audit of the
stock at hand. 3. The new store must
products and slow have a good
moving products can 2. The errors could
happen because of relationship with the
be determined from warehouse to ensure
other stores in wrong counting or
stock unaccounted for stocks are
Singapore. replenished on time.
3. Data on stock if in the back store.
replenishment, 3. Stock replenishment
proximity to nearest from warehouses may
warehouse not be on time.

13. Decision 2
Levi’s decides to increase sales volume for all the existing stores in
Singapore, next year. Hence they need to evaluate the sales performance of
all existing stores and make a sales plan for next year that fits in with the
management goals and objectives.

14. Decision 2
Increase sales volume for existing stores in Singapore
• Average number of customer walk-ins/day and conversion rate
1
• Numbers of transactions per hour
2
• Sales per transaction
3
• Purchase information
4
• Strength of Stock and Stock Turn ratio
5
• Sales promotion data
6
• Net sales per employee
7

15. 1. Customer Walk ins Overcoming
challenges
Challenges
1. The definition of
walk-ins needs to be
Data needed standardized- so is a
1. The challenge in this
family counted as
1. This data will help data is that it may not
one or each
gather information on be all that accurate
individual in the
how many customers and all that reliable
family is counted as
walked into the store since there is no one
one.
daily and what single method to
percentage bought count walk-ins into a
something. store .
2. Customer conversion
rate =Number of
transactions /
customer traffic x 100
3. Action Items ->
Identify peak and
low seasons

16. 2. Numbers of transactions per hour Overcoming
challenges
Challenges
1. It is important that
manual billing should
Data needed be immediately
1. The challenge with
this data is that of entered on to an
conformance and excel sheet and the
1. Determine the POS software should
currency. This
number of billings be allowed to import
happens in a manual
and also average that information and
intervention because
number of billings generate the correct
of an item barcode
per hour report.
missing or the point
2. Helps to identify 2. The backend
of sale (POS)
peak hours and operation should be
software not
lean hours, done at the store
working.
setting store level and should
2. Even if it is entered
hours and staff have restricted
in the backend, it will
schedules access.
not be current and
particularly for
hence data can be
cashiers
skewed

17. 3. Sales per transaction Overcoming
challenges
Challenges
1. It is important that
the process of bar-
Data needed coding is efficient
1. The challenge with
this data is that of and correct with all
reliability. The information about
1. Identifies value of the item. A few
purchase on every smallest error at the
time of generating random quality
billing and also checks should be
provide number of the barcode can give
wrong billing data done when stock
pieces sold in every inward takes place
billing and hence incorrect
2. High volume of sales is data and information.
more important or a
high SGD value on
each sale is important
3. Sales per transaction
= Net sales / number
of transactions

18. 4. Purchase information Overcoming
challenges
Challenges
1. All barcodes should
carry all information
Data needed about the items.
1. The challenge with
this data is manifold. There should be no
All information is duplication of a
1. This piece of data is barcode
captured at the POS. stored in the
barcode. So the 2. Random quality
It will give insights on check to see if a
what are people precision,
completeness, and particular barcode
buying- design, sizes, matches with the
colors, fits etc reliability of the data
become an issue right merchandise
2. This is the most and also when
important piece of scanned gives all the
data which will help required information
the store in buying
and planning of
merchandise

19. 5. Strength of Stock and Stock Turn ratio Overcoming
challenges
Challenges
1. There needs to be
standardization in
Data needed terms of opening
1. The challenge with
this data is the stock and closing
accuracy and stock for the
1. Measures if it is day/month
overstocked or under timeliness of data
as a lot depends on 2. This will ensure
stocked consistency across all
2. Ability to turn stock available of stocks
2. The errors could data points captured
around efficiently to within the store.
yield better profit; happen because of
the more times the wrong counting
store turns its stock, ,stock unaccounted
the more are its in the back store Or
margins stock lying because
3. Ensure that of returns etc.
replenishments
happen on time

20. 6. Sales promotion data Overcoming
challenges
Challenges
1. A loyalty or
membership card
Data needed which will record
1. The challenge with
this data is that it customer buying
may not be complete. details
1. Information on what 2. During promotions,
items got sold, any Sales promotions are
generally for a short billing can be split
old designs and between new
patterns, did the duration and this
gives a boost to sales merchandise and
promotion create promotion
more walk-ins, and for a short period.
Using this to predict merchandise
did the store
promotion have a sales behaviour
complimentary during non-
effect on new promotional periods
merchandise i.e. how could then have a
many new designs negative impact
got sold.

21. 7. Net sales per employee Overcoming
challenges
Challenges
1. The uniqueness of
the specific skills for
Data needed each section should
1. The challenge with
this data is that it be identified and
may not represent also relevant training
1. Determine the sales might be provided to
transaction carried the performance
of individual the employee
out by an employee.
This could employee as
determine the sometime
performance of teamwork is
employee such as involved
convincing of
customer, providing
good customer
service

22. Conclusion
• Organizations need a single source of truth
1
• Quality data is “Data That Is Fit For Use”
2
• Quality data directly impacts decision-making
3 and the bottom line

23. References
1. www.levi.com.sg
2. Davenport, T.H, & Prusak,L. (1998) Working
knowledge: how organisations manage
what they know. Boston: Harvard Business
School Press
1. Levi Strauss Annual Report 2011
2. Images sourced from www.google.com

24. Any questions?