An introduction to analytics is a small presentation made for increasing awareness on analytics with some case studies of applying analytics in different functions. These case studies are from informs.org which were openly available when the presentation was made. Due to confidentiality related obligations my personal experiences were shared - without naming clients - during the presentation. However, the case studies cannot be share on the PPT here. For more details or inputs on analytics you can reach me at twitter - @krdpravin or LinkedIn - https://in.linkedin.com/in/krdpravin

1. By – KRD Pravin
© 2014 KRD Pravin
Introduction to Analytics
Source of case studies - https://www.informs.org/Sites/Getting-Started-With-Analytics/Analytics-Success-Stories
© KRD Pravin 2014

2. +Usage of analytics
+Example
CONTENTS
+What is?
+Why analytics
 What and
Why
 How
example &
impact
2 31
 Intro
© KRD Pravin 2014

3. What is Analytics
A scientific process
Utilizes Mathematics & Statistics
Transforms data into insight
Discovers meaningful patterns
Two types – reporting & Analysis
Predicting- What happenED? What WILL happen
© KRD Pravin 2014

4. Analytics – “Evolution”
B
u
s
i
n
e
s
s
V
a
l
u
e
HIGH
LOW
A
B
C
D
D – Prediction –What will happen? Modeling, Data mining, Statistics
1980 1990 2000 2010
What are reporting and what are analytics
phases of these evolution?
A – Reporting – What happened? Static & interactive reports
B - Analysis – Why did it happen? OLAP, SQL
C – Monitoring –What is happening? Dashboards / Scorecards
Decade
© KRD Pravin 2014

5.  Companies utilizing analytics outperform peers
 Lower cost
 Higher Revenue
 “I (company) will make an offer you (customer) cant resist”
 Optimization
 Impulse purchase
 Brand perception, Revenue increase and improved User Experience
 Fact Based Decision making
Why Analytics
© KRD Pravin 2014

6. +Usage of analytics
+Example
CONTENTS
+What is?
+Why analytics
 What and
Why
 How
example &
impact
2 31
 Intro
© KRD Pravin 2014

7. How, example & impact (in Retail)
Business Decisions
• Strategy planning
• Operations, Marketing, HR & others
• Localization and Clustering
• Real Estate Optimization
Marketing & Customer analytics
• Customer-Driven Marketing
• Marketing Mix Modeling
• Pricing Optimization
• Product Recommendation
• Test and Learn
Inventory and Operations
• Supply Chain Analytics
• Forecasting
• Workforce Analytics
In-store
• Assortment Optimization
• Shelf Space Allocation
• Fraud Detection and Prevention
© KRD Pravin 2014

8. Opportunity
• world's largest
healthcare services
company – McKesson
• revenues over $120
billion
• Its supply chain, serves
all pharmaceutical
manufacturers and
25,000+ clients
• Opportunity in
Operations and Supply
chain
Proposition
• Scenario Modeler
analytical engines
• distribution network
• inventory policies
• supply flows
• vehicle routes
• sustainability, financial &
operational metrics
• creation of new supply
chain
• updating pricing models
• service improvements
• profit opportunities
Impact
• Application
• 60,000 active items
• 30 distribution
centers
• shipping 2M
pieces/day
• 25,000 customer
locations
Example – Supply Chain
© KRD Pravin 2014
Source of case studies - https://www.informs.org/

9. Opportunity
• Dell from Direct Sales
to Channels
• Different channel
different customer
needs
• Developing the right
product offerings
• Challenge
• determine the best
possible
configurations
Proposition
• Demand cluster
analysis
• identify naturally
occurring patterns
• Maximize the
conversion rate
• competitive
benchmarking
Impact
• Retail Margin Maximizer
• Demand sensing
• Promotion uplift model
• Inventory risk management
• Margin improvement
Promos
• Pricing Intelligence
• Network Optimization
• Marketing Investment
Optimization
• Support affinity analysis
Example – Business Strategy & inventory Management
© KRD Pravin 2014
Source of case studies - https://www.informs.org/

10. Example – Strategy & Decision Making
Opportunity
• Kroger
• 2,422 supermarkets
• 339,000 associates
• 1,950 in-store
pharmacies
• Objective
• reduce the overall cost
• Pain point
• pharmacy inventory
management
• predict pharmacy demand
• reduce out-of-stock
Proposition
• Model empirical
distributions,
visualize inventory
results
• development of
inventory simulation &
optimization model
• built fast optimization
algorithms
• visualization of the
modeling
Impact
• reduced out-of-stock
1.5M
• additional revenue of
$80M
• inventory costs
reduction $120+M
• labor cost reduction
~$10M
• YEARLY
© KRD Pravin 2014
Source of case studies - https://www.informs.org/

11. Open forum - Discussion
Discussion what we can do
Question & answers
Action points
Please volunteer for taking notes?
© KRD Pravin 2014

12. THANK YOU!
KRD Pravin
Twitter - @krdpravin
© KRD Pravin 2014