Target Corporation is an upscale discount retailer providing high-quality merchandise at attractive prices. It has 1,774 stores in the US and was founded in 1902. Target uses data analytics and predictive modeling extensively. It analyzes customer purchase data to personalize offers, which led to controversy over predicting a customer's pregnancy. Target continues investing in analytics, hiring experienced leaders from competitors to develop analytical capabilities. Recommendations include benchmarking analytical maturity, integrating data across functions, and emphasizing tools and dashboards.

1. TARGET CORPORATION
CASE STUDY
Joel Allman | Bryan Bronchik | Kendra Royal
Indiana University – Purdue University at Indianapolis
School of Informatics and Computing
INFO B585 Biomedical Analytics
Saptarshi Purkayastha
9-NOV-2016

2. DELTA Framework & Analysis
SWOT Analysis
Recommendations
Agenda
Company Overview
• Financial Information
• Competitors
• Timeline
1
2
3
4

3. Company Background
Target, the second largest discount retailer in the US, is an
“upscale discount retailer that provides high-quality, on-trend
merchandise at attractive prices in clean, spacious and guest-
friendly stores.”
Product Categories
•Groceries
•Electronics
•Apparel
•Office Supplies
•Toys
•Household Essentials
•Pet Supplies
•Home Furnishings/Decor
Purpose & Beliefs
“We fulfill the needs and fuel
the potential of our guests.
That means making Target
their preferred shopping
destination by delivering
outstanding value,
continuous innovation, and
an exceptional guest
experience — consistently
fulfilling our Expect More.
Pay Less.® brand promise.”
Overview
•Founded:
George Dayton
1902-Dayton Dry Goods Co.
1962-Target
•Headquarters:
Minneapolis, MN
•Nickname: "TAR-ZHAY"
•Stores: 1,774 (US)
•Distribution Centers: 37 (US)
•Employees: 341,000
•2015 Revenue: $73,226 (bi)
•Website: www.target.com

4. Financial Information
Total
Segment
Sales
$73.8
Billion
Financial
Highlights
Stock Price (TGT): $67.05

5. Revenue
Size
External Environment
#6 Retailer
www.target.com
•Stores: 1,774
•Distribution
Centers: 37
•Employees:
341,000
$73,226,000
#1 Retailer
www.walmart.com
$353,108,000
•Stores: 5,182
•Distribution
Centers: 150+
•Employees:
1,500,000
#8 Retailer
www.amazon.com
$61,619,000
•Stores: NA
•Distribution
Centers: 104
•Employees:
230,800
#20 Retailer
www.searsholdings.com
$22,129,000
•Stores: 1,611
•Distribution
Centers: 28+
•Employees:
178,000
TARGET
SEARS
HOLDINGS, INC.
AMAZON.COM
WALMART
STORES, INC.
Global
Presence
LOW
Intl.target.com,
India
MEDIUM
28 countries,
6200 locations
HIGH
76 countries
LOW
306 Canada,
66 Mexico,

6. Timeline
1960 Transitioned
to discount
store chain
1960 Opened 1st
distribution
center
1967 Expanded
nationally
1962
1st
Target
1902
Dayton Dry
Goods Co.

7. Timeline
1988 Unveiled UPC
scanning
1974 Used
planograms
1988
1974
The planogram, a diagram that
shows how retail products
should be placed on shelves to
maximize sales, was Target’s
first use of strategic tools in the
area of visual merchandising.
1979 Achieved $1
billion in
annual sales
Planogram
The Universal Product Code
(UPC), a barcode that uniquely
identifies each product with a
12-digit number, was Target’s
first electronic means of
capturing data with scanning
systems .
UPC

8. Expect More. Pay Less.®
2000 Released
weekly ad
1994
2001 Operated
Target.com
on AWS
2005 Exceeded
$50 billion in
annual sales;
Established
Target India
2007 Introduced
credit card
2000
Timeline
1994 Unveiled
brand
promise
1995 Launched
Target.com
1995 Offered
credit cards,
gift cards,
registries

9. 2015
Timeline
2013 - 2014
2013 Introduced
coupon app,
subscription;
Innovation
Center;
Experienced
data breach
2014 Enabled
cards with
chip-and-pin
technology;
Acquired
Powered
Analytics
2010 - 2012
2010 Presented at
Conference;
Relaunched
Target.com
2011 Slowed
growth
2012 Included in
NY Times
article;
Expanded
mobile
presence;
Implemented
Teradata
2010 Selected
Emnos for
customer –
centric
insight
2010 Planogram
Optimization
and Space
Optimization
provided by
SAS
2014 Piloted eBay
global
shipping
program
2014 Launched
Wish List
app
2014 Launched
Cartwheel
digital
savings app
2011 Expanded
into Canada

10. Timeline
Broadened
relationship with
GroupM Media
Business
Tested new look in
stores (LA25)
2016
Created guest
center of excellence
Opened Cyber
Fusion Center
Created data,
analytics, and BI
center of excellence Explored use of
RFID and Beacon
technology in stores
Equipped stores
with secure chip
card payment
technology
Invested $1 billion in
technology areas
2015
Enabled
international sales
with Borderfree
Began shopcurbside
.com pickup
Shut down Canadian
operations
Launched
Wonderlist gift
guide
Consolidated
mobile and desktop
target.com sites

11. ANALYTICAL COMPANIES
ANALYTICAL ASPIRATIONS
LOCALIZED ANALYTICS
ANALYTICALLY IMPAIRED
ANALYTICAL COMPETITORS
DELTA Maturity Model
5
4
3
2
1
Data Enterprise Leadership Targets Analysts

12. DELTA
ANALYTICAL COMPETITOR
Background
Father gets mad after Target sends
teenage daughter promotional mailers
for pregnancy/baby products based on
an analysis of customer data.
Methodology
• Identified data set
• Looked for buying patterns and
behaviors
• Create action items based on
analysis
Organizational Value
• Increase sales
• Provide competitor advantage
• Strengthen customer relationships
Pregnancy Algorithm • Demonstrated passion for leveraging insights
gained through analytics
• Strategic use of large quantities of different types
of data from multiple channels (e.g., online,
mobile, in-store)
• Remediation of security vulnerabilities exposed in
data breach (e.g., new leadership, new POS
terminals, chip-and-PIN cards, data sharing
initiatives)
• Connection of organizational objectives to data
across the enterprise
• Employment of experienced individuals to ensure
usability of data to meet business needs
• Partnership and collaboration with key vendors of
data-related technologies (e.g., Teradata, Hadoop)

13. DELTA
ANALYTICAL COMPANY
ENTERPRISE
IT STRATEGY
DRIVES
ANALYTICAL
VALUE
SALES
&
MARKETING
SUPPLY
CHAIN
HUMAN
RESOURCES
Guest Center of Excellence is designed
to enable the organization to develop a
greater sense of advocacy and
empathy for the consumer in the
retailer’s business decisions.
A distribution infrastructure enhanced
to reduce the complexity of its
operations, through the use of data
across the supply chain, to deliver a
seamless experience for guests.
HR positions focused on benchmark
analysis and the development of
metrics to ensure competitive
compensation and benefit packages to
attract highly qualified talent. Potential of Analytics Validated
Pockets Of Success Achieved

14. DELTA
ANALYTICAL COMPETITOR
• Prioritization of the development of an analytic
culture and analytical capabilities throughout the
organization, especially in leadership
• Recruitment of strong leaders, many from
competitors, who are subject matter experts in
business intelligence and analytics
• Presentation of analytic techniques at industry
conferences (e.g., Andrew Pole’s keynote at
Predictive Analytics World in 2010 titled, “How
Target Gets the Most out of Its Guest Data to
Improve Marketing ROI”)
• Executive sponsorship of professional, in-house
network of analytical team members that
provides mentoring, skill development, and
collaboration (e.g., Target Analytics Network)
“Colbourn will lead
the development of
data-driven
marketing strategies
that drive traffic and sales,
deepen brand engagement and
build guest loyalty, including
Target’s current portfolio of
loyalty programs such as the
popular savings app, Cartwheel,”
• Hired January 2016
• Experienced in retail data
analytics
Keith Colbourn
Senior Vice President, Loyalty
& Lifecycle Marketing

15. DELTA
ANALYTICAL COMPETITOR
• Communicating Guest insights into Value
o Personalized coupons based on
visits/purchases
o Community driven weekly ads
o Focus on the community to provide “one
stop shop” for Guests needs
• Focus on Value
o 2016 Holiday plan increases 20% [year
over year] on the value category
• Mobile Localized Intelligence
o Increase usage and redefining stores and
fulfillment centers remote Guests

16. “Led a 500+ person analytics team that
was responsible for all BI and analytics
functions, including predictive analytics,
optimization, data science, big data, data
quality, business intelligence and reporting
across all business functions of the entire
company.”
DELTA
ANALYTICAL COMPETITOR
Vice President,
Enterprise BI & Analytics
Ujjwal Sinha
Oversees enterprise strategy, innovation,
data analytics and business intelligence, as
well as new business integration and
operations with a “main goal of ‘infusing a
digital Mindset’ in a company that has
long been defined by brick and mortar
operations.“
Chief Strategy & Information Officer
Casey Carl
Studied data using machine learning
algorithms to “identify and locate Target’s
ideal market, informing its marketing
strategy and overall reach,” which led to
controversy around their use of data
mining.
Director, Guest Management
Andrew Pole
Uses his “background in designing and
delivering support systems using various
advanced analytics algorithms” in the
retail industry to accelerate Target’s data,
analytics, and business intelligence
capabilities by leading a center of
excellence.
Senior Vice President,
Enterprise Data, Analytics, & BI
Paritosh Desai

17. Weaknesses
• [International] E-commerce sales
• Wide variety of product offerings
• Store associates’ application of analytic
insights
• Supply chain optimization
• Grocery offering
differentiation
Strengths & Weaknesses
Strengths
• Expertise in digital advertising
• Number/variety of tools available to
capture customer activity
• Algorithms and predictive analytics
techniques
• Enterprise use of analytics
Opportunities
• Expanded online and mobile offerings
• Exploration of new technology:
o Wi-Fi/RFID generated heat maps
o Internet of Things
o Artificial Intelligence
• Expanded use of competitive shipping
options/services
Threats
• Data breach recovery
• Competitor advancement in emerging
technologies (i.e., Walmart Pay)
• Competitor advancement in analytics
(i.e., WalmartLabs)
• Competitor acquisitions
(i.e., Walmart’s acquisition of Jet.com)
SWOT
Analysis

18. • Benchmark current analytical maturity level for future research/improvement
• Integrate data across business functions, including social media and public census
information
DELTA
Moving to the Next Level
• Create a rotational program (e.g. Walmart)
• Find middle-ground between the current organizational structure and retraining or re-
staffing analytical positions
A
• Continue to invest into big data and predictive analytics tools
• Emphasize use of digital dashboard and visualization solutions
D
• Continue creating “centers of excellence”
• Fill future open leadership positions with data-driven individuals
L
E
• Jeff Jones improving “Guest experience”
• Support within the community with Community Relations, Global Affairs and Sustainability
teams as well as Target Foundation
T