Transcript Big Data Lever

Big Data Lever
Mrs. Agnes Mak
Executive Director
Hong Kong Productivity Council
Discussion Topics
1. Big Data Evolution Landscape
2. What Business Problems are Industries
Addressing with Big Data
3. Leveraging Customer Big Data Use Case
4. Leveraging Transaction Big Data Use Case
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Discussion Topics
1. Big Data Evolution Landscape
2. What Business Problems are Industries
Addressing with Big Data
3. Leveraging Customer Big Data Use Case
4. Leveraging Transaction Big Data Use Case
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1.1 The History Of Big Data In The Past 70 Years
Source: HCL, Daniel Tuitt, A History of Big Data, 2013
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1.1 The History Of Big Data In The Past 70 Years
Source: HCL, Daniel Tuitt, A History of Big Data, 2013
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1.2 February 2010 - Data, Data Everywhere
The Economist published a report titled, Data, Data
Everywhere. Kenneth Cukier writes: “…the world
contains an unimaginably vast amount of digital
information which is getting ever vaster more rapidly…
The effect is being felt everywhere, from business to
science, from governments to the arts."
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1.3 What Happens On The Internet Every 60 Seconds?
Source: Qmee.com, What Happens on the internet every 60 seonds,2013.
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1.4 Business Analytics With Big Data
What
Happened?
Why Did
It Happen?
What Should I
Do About It
What Is Likely
To Happen?
Analytic Linkages
Structured
Data
Document
Content
Public
Opened Data
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1.5 2012 The 3Vs --> 4Vs
•
“Big data is high volume, high velocity, and/or high variety information
assets that require new forms of processing to enable enhanced decision
making, insight discovery and process optimization” ( Gartner / Doug Laney 2012 ).
•
Some other organizations added veracity to define it.
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1.6 March 2012 – Critical Questions For Big Data
Defined big data as “a cultural, technological, and
scholarly phenomenon that rests on the interplay of:
Technology
• maximizing computation power and algorithmic
accuracy to gather, analyze, link, and compare
large data sets.
Analysis
• drawing on large data sets to identify patterns in
order to make economic, social, technical, and
legal claims.
Mythology
• the widespread belief that large data sets offer a
higher form of intelligence and knowledge that
can generate insights that were previously
impossible, with the aura of truth, objectivity, and
accuracy.”
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Discussion Topics
1. Big Data Evolution Landscape
2. What Business Problems are Industries
Addressing with Big Data
3. Leveraging Customer Big Data Use Case
4. Leveraging Transaction Big Data Use Case
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2. What Business Problems are Industries Addressing with Big Data?
Source: Gartner, Lisa Kurt, Big Data Industry Insight, 2014.
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Discussion Topics
1. Big Data Evolution Landscape
2. What Business Problems are Industries
Addressing with Big Data
3. Leveraging Customer Big Data Use Case
4. Leveraging Transaction Big Data Use Case
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3.1 Source Of Customer Big Data?
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3.2 Leveraging Customer Big Data
Function
Big Data Lever
Marketing
 Sentiment Analysis
 Marketing Campaign
Cross Selling
Location Based Marketing
In-store Behavior Analysis
Customer Micro-segmentation
Multi-channel consumer experience
Merchandising
Assortment Optimization
Pricing Optimization
Placement and Design Optimization
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3.3 Sentiment Analysis
“3E” Social Media Analytics
Model:
Exposure
to Enthusiasm
to Experience
from
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3.4 Social Media Marketing Campaign
Social Media Sites
Celebrities Social Web
Site
On-Line News / OnLine Media Sharing
Websites
Discussion Forum,
Blogs
• E.g. Facebook
• E.g. Sina Weibo
• E.g. Youtube
• E.g. HKGolden
200+
CN/HK
Social Media
Non-structure /
Structured Data
BI System
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3.4 Social Media Marketing Campaign
Opportunities to Company:
•Effective online analysis of Marketing Campaign Effectiveness
•Detailed Analysis of positive / neutral / negative web posts of industry
players (own brand vs. competitive brands for a given period)
Results:
•In-depth understanding of response of marketing efforts of a very
large pool of consumers
•Identified new marketing directions
•Facilitated follow-up actions by respective parties and departments
(e.g. MKT Dept.)
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Discussion Topics
1. Big Data Evolution Landscape
2. What Business Problems are Industries
Addressing with Big Data
3. Leveraging Customer Big Data Use Case
4. Leveraging Transaction Big Data Use Case
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4.1 Leveraging Transaction Big Data
Function
Supply Chain
Big Data Lever
 Distribution and Logistics Optimization
 Inventory Management
Supplier Negotiations
Operations
Performance Transparency
Labor Inputs Optimization
New Business
Models
Price Comparison Services
Web-based markets
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4.2 Demand/Supply Chain Predictive Planning
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4.2 Demand/Supply Chain Predictive Planning
Opportunities to FMCG Retailer :
•Location of distribution center and
warehouse capacity planning
•Long history of sales and logistics operation
data
•Determining optimal inventory levels and
replenishment policies for all DC
Results:
•In-depth understanding of dynamic mix of
potential consumer needs and growth
•Reduced Day Sales On Hand (DSOH) by
13.21days, equivalent to approx.
RMB109.69M
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Big Data Revolution – Call For Actions


What big data
analysis and
outcome will
enhance the
quality of life of
the community
What data can
be opened
Gov’t

Big Data
NGOs

Business goals
and outcome.
End users need to
prove the value.
Enterprises
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Conduct Hong Kong Industry Network Clusters
Gauge the views of industry on big data development
Ms. Betty Fung
Tel : (852) 2788 6202
E-mail : [email protected]
Mr. Kevin Ng
Tel : (852) 2788 5843
E-mail : [email protected]
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