This document summarizes a presentation about how retail industry leaders are driving growth through agile analytics. The presentation discusses how leaders extensively utilize different types of data and look outside their industry for innovative analytics solutions. It provides examples of innovative analytics applications in different industries. The presentation emphasizes that leaders operationalize analytics by embedding predictive models into business processes and applications. It discusses key steps in the operational analytics journey and assessing an organization's analytic maturity.
Be Digital or Die - Big Data in Financial ServicesFintricity
Leveraging Big Data, disruptive technologies (such as Blockchain) and new business models to digitally transform financial services companies. Presented by Alpesh Doshi at the Big Data Innovation Summit in San Francisco 2016.
Business Intelligence & Technology_Pharmaceutical BIVikas Soni
An overview of business intelligence introduction, trends, components, approaches, functions, architecture and necessity to any successful business and applications of this BI approach for the better decision making in a pharmaceutical or health industry.
Business intelligence systems are also unable to deal with market volatiles. Infosys' business analytics offerings provide the processes, tools and expertise to extract the most from information investments description.
Be Digital or Die - Big Data in Financial ServicesFintricity
Leveraging Big Data, disruptive technologies (such as Blockchain) and new business models to digitally transform financial services companies. Presented by Alpesh Doshi at the Big Data Innovation Summit in San Francisco 2016.
Business Intelligence & Technology_Pharmaceutical BIVikas Soni
An overview of business intelligence introduction, trends, components, approaches, functions, architecture and necessity to any successful business and applications of this BI approach for the better decision making in a pharmaceutical or health industry.
Business intelligence systems are also unable to deal with market volatiles. Infosys' business analytics offerings provide the processes, tools and expertise to extract the most from information investments description.
The purpose of business intelligence is to support better business decision making. BI systems provide historical, current, and predictive views of business operations, most often using data that has been gathered into a data warehouse or a data mart and occasionally working from operational data.
Gartner: The BI, Analytics and Performance Management FrameworkGartner
Further information on BI is available at www.gartner.com. Gartner will also host its Business Intelligence Summit 2011, 31 Jan- 1 Feb, London. More information at www.europe.gartner/bi.
Leverage Sage Business Intelligence for Your OrganizationRKLeSolutions
Learn how Sage Business Intelligence provides the insight you need to make better decisions faster! This informative presentation explores Sage Intelligence and Sage Enterprise Intelligence solutions for Sage 100, Sage 500 and Sage X3.
Next Generation Spend Analytics & Data VisualizationJosh Stancil
This presentation shows procurement and strategic sourcing professionals how to use advanced spend analytics to move the needle from being tactical to strategic.
Day 1 (Lecture 4): Data Science in the Retail Marketing and Financial ServicesAseda Owusua Addai-Deseh
Lecture on "A Practical Exposition of Data Science in the Retail Marketing and Financial Services" delivered by Delali Agbenyegah, Director of Data Science and Analytics, Express, Columbus OH, USA.
The main task of this talk is to see how Data Science can influence big companies to generate new revenue and more profit.
Subjects that will be addressed in this talk are:
• Understanding a value it brings to corporations on long-term (direct revenue generation not only cost reduction);
• Data Science is important part of digital transformation. Are corporations ready?
• Management dedication on investment;
• Lack of Data Science managers acting as a link between Data Scientists and Business managers. Provide motivation/interesting tasks for Data Scientists while validating investments in business environment;
• Lack of skillful Data scientists;
• Compensation of Data Scientists among other Employees (obviously a different scales needs to be applied);
• Examples of Applied Data Science as revenue generators in Telenor Serbia;
The ASCENTOR team is experienced in delivering complex custom made professional trainings in business strategy, finance, risk and fraud. We customise all our training programs to respond to our client's industry issues and real worklife needs. Our main cutomised training solutions cover a range of highly practical topics. We will discuss with your HR and management team to develop the most appropriate programs for the targeted audience.
Expert data analytics prove to be highly transformative when applied in context to corporate business strategies.
This webinar covers various approaches and strategies that will give you a detailed insight into planning and executing your Data Analytics projects.
The purpose of business intelligence is to support better business decision making. BI systems provide historical, current, and predictive views of business operations, most often using data that has been gathered into a data warehouse or a data mart and occasionally working from operational data.
Gartner: The BI, Analytics and Performance Management FrameworkGartner
Further information on BI is available at www.gartner.com. Gartner will also host its Business Intelligence Summit 2011, 31 Jan- 1 Feb, London. More information at www.europe.gartner/bi.
Leverage Sage Business Intelligence for Your OrganizationRKLeSolutions
Learn how Sage Business Intelligence provides the insight you need to make better decisions faster! This informative presentation explores Sage Intelligence and Sage Enterprise Intelligence solutions for Sage 100, Sage 500 and Sage X3.
Next Generation Spend Analytics & Data VisualizationJosh Stancil
This presentation shows procurement and strategic sourcing professionals how to use advanced spend analytics to move the needle from being tactical to strategic.
Day 1 (Lecture 4): Data Science in the Retail Marketing and Financial ServicesAseda Owusua Addai-Deseh
Lecture on "A Practical Exposition of Data Science in the Retail Marketing and Financial Services" delivered by Delali Agbenyegah, Director of Data Science and Analytics, Express, Columbus OH, USA.
The main task of this talk is to see how Data Science can influence big companies to generate new revenue and more profit.
Subjects that will be addressed in this talk are:
• Understanding a value it brings to corporations on long-term (direct revenue generation not only cost reduction);
• Data Science is important part of digital transformation. Are corporations ready?
• Management dedication on investment;
• Lack of Data Science managers acting as a link between Data Scientists and Business managers. Provide motivation/interesting tasks for Data Scientists while validating investments in business environment;
• Lack of skillful Data scientists;
• Compensation of Data Scientists among other Employees (obviously a different scales needs to be applied);
• Examples of Applied Data Science as revenue generators in Telenor Serbia;
The ASCENTOR team is experienced in delivering complex custom made professional trainings in business strategy, finance, risk and fraud. We customise all our training programs to respond to our client's industry issues and real worklife needs. Our main cutomised training solutions cover a range of highly practical topics. We will discuss with your HR and management team to develop the most appropriate programs for the targeted audience.
Expert data analytics prove to be highly transformative when applied in context to corporate business strategies.
This webinar covers various approaches and strategies that will give you a detailed insight into planning and executing your Data Analytics projects.
Building a Complete View Across the Customer Experience on Oracle BICSShiv Bharti
Many organizations today are using a Modern Business Intelligence Platform or Big Data to eliminate Customer Blind Spots. When most firms refer to Big Data, they are not necessarily using “BIG” data, the term is used interchangeably with Analytics by most of our Customers.
Organizations today are increasingly relying on Data to make strategic decisions. Marketing Departments are using Predictive analytics to identify the Prospects or segments that will give their firms the most “lift” and thus highest ROI.
What are Customer Blind Spots?
Gaps in your view of the customer relationship across time
No formal social media listening data
Lack of cross-device identity
Inability for organizations to deliver personalized customer experiences
Inability to apply predictive analytics to customer behavior to optimize products and services
What are the Challenges to eliminate blind spots?
Disparate Data sources
Multiple Sources of the truth
Growth in Data Volumes
Data Migration Challenges
Fundamental Considerations for a Customer 360 project
Customer 360 project should focus on making substantial improvements in 5 key areas: Improve data quality, create Linkages across our various systems, centralize disparate information, transform the data to enable action and insights, and streamline the manner in which data is accessed and available.
Each pillar contains a stream of work broken into parallel paths to accelerate the rollout and adoption of the platform.
If you’re attending @Oracleopenworld (#oow16) and are considering a project to build a Customer 360-degree view by eliminating Customer Blind spots, please join us for our session to learn more on this subject including a customer case study. We look forward to a great session and stimulating conversations.
Building a Complete View Across the Customer Experience on Oracle BI Cloud Service [CON3730]
Monday, Sep 19, 4:15 p.m. – 5:00 p.m. | Moscone West – 2006
An introduction to BRIDGEi2i - Analytics Solutions company focused on solving complex based problems based on data mining and advanced analytics on big data. Visit http://www.bridgei2i.com
The consumer has been the king for quite a while now. Why then are organizations struggling to engage the consumer, personalize its offering and maximize the value that they can realize.
BRIDGEi2i presents a comprehensive, end to end Consumer Analytics solution that helps you know your consumer better, predict purchasing decisions and personalize recommendations
Predictive Analytics & Decision Solutions [PrADS], a subsidiary of Dun & Bradstreet provides cutting edge analytics solutions and actionable insights to leading organizations globally , The following presentation provides an overview of the services offered
Operationalizing Customer Analytics with Azure and Power BICCG
Many organizations fail to realize the value of data science teams because they are not effectively translating the analytic findings produced by these teams into quantifiable business results. This webinar demonstrates how to visualize analytic models like churn and turn their output into action. Senior Business Solution Architect, Mike Druta, presents methods for operationalizing analytic models produced by data science teams into a repeatable process that can be automated and applied continuously using Azure.
What is Business intelligence
Core Capabilities of Business Intelligence
Elements of Business Intelligence
Why Companies opt for Business Intelligence
Benefits of Business Intelligence
User of Business Intelligence
Reports of Business Intelligence
Business Application in Extended Enterprise
Business Analytics
Golden Rules for Business Intelligence
5 Stages of Business Intelligence
The advent of ‘big data’ has completely changed the way businesses can harness the information about customers to make powerful business decisions. Data could be of any type – campaign information, customer demographics, individual transaction behavior, interactions on social networks, web usage, or satisfaction surveys etc. BRIDGEi2i has the ability and experience to mine this wealth of unstructured and structured information to help businesses identify prospects, target them through the right channel, maximize cross sell and up-sell opportunities and thereby enhance the life time value of customer relationships. To know more visit: http://www.bridgei2i.com/customer-intelligence.html
Business Intelligence, Data Analytics, and AIJohnny Jepp
Data is the new currency. In this session, best practices on data collection, management dashboards, and used cases will be shared using Azure Data Services.
Video accessible at bit.ly/APACSummitOnDemand
Shwetank Sheel
Chief Executive Officer
Just Analytics
Poonam Sampat
Cloud Solution Architect - Data & AI
Microsoft Asia Pacific
Similar to NRF BigIdeas_Big Data in Retail_AN16 (20)
4. Objective of this Session
Demonstrate how industry leaders are driving significant growth
through agile analytic innovation and integration with traditional
in-house ERP, CRM, and Operational data.
In Summary:
• What Distinguishes Analytic Leaders
• Retail Innovation
• How to Operationalize Analytics
5. Analytics is a Competitive Arms Race
Explosion of activity in Discovery to Drive Competitive Advantage
• Data
CRM, ERP, Operational Data
External & 3rd Party
Internet of Things
Digital & Social
• People
• Process
• Technology
• Culture
6. Agile Analytic Leaders are Growing their Business
Extensive Data Utilization
1. Unstructured Internal Data (email, text files, documents, forms, logs)
2. External Transactional Data (e.g. partners, distributors, suppliers)
3. Transactional Data from ERP, CRM, and other Operational application
4. Customer Data (360 view)
5. Internet of Things and device/sensor data
6. Customer Mobile Device (e.g. geolocation, wearables)
7. Unstructured beyond Text (audio & video)
8. Unstructured External (social media, blogs, web pages)
Leaders
81%
78%
77%
70%
56%
53%
53%
47%
Others
59%
50%
60%
41%
31%
22%
28%
31%
Gap
Base: 166 BI & Analytic Decision Makers, Leaders n=98, Others n=68
Source: Forrester Consulting on behalf of HP, February 2015
22
28
17
29
25
31
25
16
7. Industry Leaders look Outside for Innovation
Financial Services Consumer Industries
and Retail
Manufacturing Public Sector
‒ Regulatory compliance
‒ Capital optimization
‒ Customer-centricity
‒ Cost management
‒ Growth/increase wallet share
‒ Omni-channel success
‒ Enabling optimal store execution
‒ Digital transformation
‒ New product launch success
‒ Risk management
‒ Supply chain visibility
‒ Trade Fund Management
‒ Warranty and quality analytics
‒ Fraud detection
‒ Predictive MRO Forecasting
‒ Vehicle Diagnostics Analytics
‒ Early Warning Detection
‒ Predictive Vehicle and Plant
Maintenance
‒ Asset protection
‒ Counter terrorism / citizen safety
‒ Transparency in governmental Agencies
‒ Traffic flow optimization
‒ Situational awareness
Energy Health & Life Sciences Travel and
Transportation
Communications, Media and
Entertainment
‒ Customer Acquisition & Retention
‒ Customer Lifetime Value/Loyalty
‒ Optimize operations
‒ Improve computing throughput
‒ Deliver information remotely
‒ Accelerate customer insights
‒ Trading/Power Procurement
‒ Dynamic Energy/Power Pricing
‒ Fraud and abuse
‒ Patient engagement
‒ Optimizing patient care
‒ Reducing healthcare costs
‒ Supply chain / distribution
‒ Drug development / scientific
research
‒ Improving operations
‒ Maximizing ancillary revenues
‒ Customer loyalty
‒ Predictive MRO analytics
‒ Yield and revenue management
‒ Supply chain visibility
‒ Irregular Route Operations
‒ Customer Acquisition & Retention
‒ Customer Lifetime Value/Loyalty
‒ Broadcast monitoring
‒ Churn prevention
‒ Advertising optimization
8. Customer Mobil Device: Levi’s Stadium
• Turn-by-turn directions (seat & services)
• Wait times for concessions & restrooms
• Promotions to optimize inventory
• Order from seat & delivery service
• Traffic Flow
• Safety & Security
Grow Revenue, Improve Customer Experience
9. 3
Road to Daytona 2/5/13 – 2/13/13
Identifier Comparison
Top Influencers
Although the official #FueledBySunoco
was established, there were numerous
instances where the organic string
“Fueled by @SunocoRacing” was used
as a reference.
Mentions
•#Gen6 = 2,260
•@SunocoRacing = 443
•#FueledBySunoco = 342
Most Discussed Terms
Gather
Analyze Share
Engage
Daytona 500
3
Conversation Trend During Race
“Drivers and
Danica”
Wreck 2
Johnson
Wins
Erin Andrews
and 50 Cent
Total Mentions: 303,857
Final Laps
Race starts
Wreck 1
Danica leads lap
Transform
Consumer 360: NASCAR
Grow Revenue, Improve Customer Experience
10. Predictors of Shrink – Store Segments (Clusters)
Hybrid Data Integration & Analytics: Retailer
Reduce Retail Shrink
11. What is a common theme?
Operationalize Analytics
def. the interoperation of multiple disciplines that support
the seamless flow from initial analytic discovery to
embedding predictive analytics into business operations
process, applications and machines
14. Operational Analytic Journey
1
Discovery - new methods,
technologies and processes to
support agile discovery
Application Integration -
cross-enterprise business process
integration
Information Delivery –
ubiquitous multi-channel insights
delivery
Workflow – Model
management, technologies and
processes to support agile
discovery
Methods – CRISP-DM V2.0
Change Management and
Organizational Transformation
– strategy for becoming an
analytically enabled enterprise
Hybrid Data Management–
Hybrid data integration, EDW,
Data Discovery Environment
Information Governance –
multi-disciplinary structures,
policies, procedures, processes
and controls implemented to
manage analytic information
15. Prioritization of Capabilities
Predictive Maintenance
Warranty & Quality Analytics
Promotion Analytics
HR Training & Management
Forecasting
Pricing Architecture
Fraud & Shrink Analytics
Security Analytics
Performance Analytics
Early Defect Detection
Brand Clout
360° View of Customer
Inventory Optimization & On Shelf Availability
Assortment Mix Planning
Labor Optimization
Regulatory Risk & Compliance
IOT Analytics
Supply Chain Analytics
Evaluate opportunities based on Corporate Readiness and Speed to Value
Readiness
BusinessValue
18. Manage Analytic Performance
BI & Analytics Management
1. Well Established Methodology for Measuring ROI of BI &
Analytic Efforts
2. Constantly Measure and Analyze BI and Analytic
effectiveness (e.g. self service ease and adoption)
3. Can monitor usage, efficiency and effectiveness of all BI and
Analytic Tools
4. Constantly measure and analyze BI and Analytic Utilization,
and Proactively Adjust
Leaders
82%
82%
79%
74%
Others
49%
50%
53%
56%
Gap
Base: 166 BI & Analytic Decision Makers, Leaders n=98, Others n=68
Source: Forrester Consulting on behalf of HP, February 2015
33
32
26
18
Industry Leaders Focus on Measurement
19. Plan Analytic Center of Excellence
Cross-functional governing body
– Improves analytical capability through collaboration, tool
standardization and cross functional working teams
– Develops common understanding of analytic issues and ideas
throughout the enterprise
– Establishes integration of information
– Establishes common execution through standards and
guidelines
– Provides ability to expand and contract teams as demand
increases and decreases
BD ACE
Departments
Analysis
Information
Support
Departments
Departments
Departments
Departments
Departments
Departments
People
Education /
Certification
Standards / Guidelines
Technology
Business
objectives
Corp
Strategy
Corp.
Ed.
Shared
Serv.
Corp.
Comm.
PMO
SME
Governance
Framework
Departments
20. Implications
Market Leaders are data driven and agile
• Place greater importance on leveraging a variety of data sources
• Operationalize analytics and insights in real or near real-time
• Implement tools that are intuitive, easy to use and enable self service
• Continuously Measure BI & Analytic ROI and Efficiency
• Make analytics pervasive throughout the organizational culture
21. How do we Begin?
• Start Small Think Big – Develop Strategy and Roadmap
• Develop Prototypes and Proof of value – Rapid Prototyping
• Create Roadmap to Future State - Build for the Future
22. Analytic Maturity Assessment
Take the operational analytics
self assessment to assess the maturity of the 10 key
process areas at: http://hpe-oamia.com/
You will also find a link to our view point Paper.
1. Analytic Discovery
2. Analytic Production and Management
3. Decision Management
4. Application Integration
5. Information Delivery
6. Hybrid Data Management
7. Analytic Workflow
8. Analytic Governance
9. Analytic Culture
10. Analytic Platform