oracle big data action plan for finance professionals
TRANSCRIPT
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Big Data Action Plan
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Big Data Action Plan for Finance Professionals
Rich ClaytonVice PresidentBusiness Analytics Product Group
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What’s the Big Deal with Big Data?
US HEALTH CARE
$300 B
“In a big data world, a competitor that fails to sufficiently develop its capabilities will be left behind.”
Increase industry value per year by
McKinsey Global Institute
US RETAIL
60+%
Increase net margin by
MANUFACTURING
–50%
Decrease development
assembly costs by
GLOBAL PERSONAL LOCATION DATA
$100 B
Increase service provider revenue by
EUROPE PUBLIC SECTOR ADMIN
€250 B
Increase industry value per year by
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90%Of the World’s Data
2 YearsHas Been Created in the Last
The World is Making a Digital Copy of Itself
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22×2011-2016
12.5Billion2020
1.3BillionToday
Smart Device Growth Data Production Increase
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Thoughts Things Processes
Datafication of Everything
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Use Data
12%
Executives who feel they understand the impact data
will have on their organizations
Produce Data
Big Problem with Big Data
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MACHINES METHODS
Implications of New Data
METRICS
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MYTH #1 Big Data is for Big Companies
MYTH #2 Big Data is not for Finance
MYTH #3 Big Data is an Unproven Technology
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Small to Medium Businesses Are Taking Action
Gathering Knowledge;
31%
Developing Strategy; 27%
Piloting; 31%
Deployed; 11%
• Enhance customer experience• Improve process efficiency• Define new products/business
models
Source: Gartner, Big Data Primer for SMBs
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MYTH #1 Big Data is for Big Companies
MYTH #2 Big Data is not for Finance
MYTH #3 Big Data is an Unproven Technology
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“Big Data can offer accountants and finance professionals the possibility of reinvention, the chance to take a more strategic, ‘future-facing’ role in organizations.”
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HR Professionals Looking to Big Data toModernize Recruiting and Talent Management
• Data discovery allows exploration of diverse data sets• Companies can improve relationship with workforce
through an understanding of data patterns
Big Data is the New Signal for Finance
Not Just for Data Scientists….
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Potential Benefits of Big Data for Finance
Identifying Accounting Irregularies
Identifying Bad Credit Risks
Determining Financing Amounts for Customers
Measuring Risk
Budgeting/Forecasting/Planning
1 2 3 4 5
3.08
3.19
3.19
3.55
3.55
Source: TATA Consultancy Services, “The Emerging Big Returns on Big Data,” 2013 Global Trend Study
Moderate Benefits Very High BenefitsNo Benefits
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MYTH #1 Big Data is for Big Companies
MYTH #2 Big Data is not for Finance
MYTH #3 Big Data is an Unproven Technology
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By 2015, organizations that build a modern information management system will outperform their peers financially by 20 percent
Mark Beyer, Gartner
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Big data has already improved overall performance by 26%
Big data will further improve overall performance by 41% by 2015
Impact of Big Data on Operational Performance
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Average CEO/President CFO/Treasuer CIO/CTO
2012 2015
Source: Economist Intelligence Unit, .”The Deciding Factor: Big Data and Decision Making“
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Where is the greatest opportunity for Big Data in your company? (choose 3 answers)
GO TO M.POLLEV.COM ON YOUR SMARTPHONE
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Impact on Society
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Finding Solutions to Breast CancerAnswering New Questions; Basis for Personalized Medicine
“Researchers have been able to integrate clinical and genomic information on 140 breast cancer patients.
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Preventing Brain Damage from Concussions
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Changing the Fan Experience
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Nate Silver
Source: nyt.com
And Polling Processes….
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How well prepared is your organization to harness power of new data sources?
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Big Data Action Plan for Finance and AccountingProfessionals
All TasksTasks
Add Tasks
High Priority
Search
More Data in Decisions
New Analytic Methods
Analytic Culture
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Social Media / Sensors
Unstructured data
External sources
1ConsiderMore Data
in Decisions
1
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695,000 Status updates
510,040 Comments 2,000,000
Search Queries
204,166,667 Emails
571NewWebsites
Data Variety Creates Biggest Opportunity
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88% of data is left on the cutting room floor
Forrester Research
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More Data into Decisions
• New relationships• Behavior patterns• Predictive outcomes
BIG DATA YOUR DATA
ERP HCM
CRMSentiment data
Images
Web logs
Documents
Locationdata
Sensor data
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Untapped Insights from Unstructured Enterprise DataExample for Procurement and Spend
Parts Catalogues
Customer Call Center Data
Customer Geocodes
Supply Chain Data
Inventory Data
Customer Surveys
Warranty Data
Supplier Costs
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What are the top obstacles for putting more data indecisions?
GO TO M.POLLEV.COM ON YOUR SMARTPHONE
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Data Discovery
Predictive Analytics
Machine Learning
1Develop
New AnalyticMethods
2
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Amazing Volume of Data @ High Speeds
300Sensors
3,000Data pointsper second
1GBRaw dataevery sailing day
Mast Strain
Hull Stability
Sail Tension
Wind Speed
Sail Strength
Hull Pitch
Amazing Volumes of Data in Real-Time
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Finance’s Opportunity is to Make Big Data small
HOW TO SEPARATE THE SIGNAL FROM THE NOISE?
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BUSINESS INTELLIGENCE
DATA DISCOVERY
Data Discovery Provides Fast Insights to New Data
Determine value of data to business
Incorporate new data into
enterprise model
UNKNOWNQUESTIONS
KNOWNQUESTIONS
DATAVALUE
UNKNOWN
DATAVALUE
KNOWN
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• 20% increase in volumes, 30% increase in profit
• Quickly explore across 50 diverse sources
• Saved 1.5 years and $4M implementation costs
• 2013 Gartner BI Excellence Award
Maximize sales of seed and crop protection products
Finding New Patterns in Agriculture
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Driving Growth Through Predictions
Anticipate Behavior and Forecast Business
Adoption is Low
70% Predictive Analytics
Is Critical 8%Use Predictive
Extensively
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Open Source Technology Lowers CostsR Statistical Programming Language
Open source language and environment
Used for statistical computing and graphics
Strength in easily producing publication-quality plots
Highly extensible with open source community R packages
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• Potential loss: millions of dollars• 100 TB compressed data
• 10 billion records/day
• Data volumes double annually• Shortened turnaround by 4 hours
Managing Risk in Real-Time
Turkcell
Preventing Fraud in Prepaid Calling cards
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“The sophisticated analytics solutions that statisticians and scientists devise must be embedded into frontline tools so simple and engaging that employees will be eager to use them daily.”
McKinsey
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$132MIncremental
Revenue in 2012Increase in
Conversions
30%Increase in Satisfaction
30%
Big Data Farm
MachineLearning Algorithms
Machine Learning Case Study: Dell
Offline Customer Data
Social Media
Website
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Invest in analytic competencies
Form a center of excellence
Learn to tell visual stories with data
1Extend
Your AnalyticCulture
3
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Get Ahead in the War for Analytic Talent
1.5 million more data-savvy managersneeded to take full advantageof big data in the United States
In which of the following areas do you think your direct reports most need to improve your skills and capabilities?
Change Mgt.TechnologyLeadershipAnalytical
Communications
21%
24%
24%
29%
33%
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Constellation of Data Science Programs
Wide range of MBA, MS and Certificate programs available.
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DATA CLUBHouse Rules
The first rule of data club:You don’t admit to being in data club
The second rule of data club:You don’t admit to being in data club
The third rule of data club:no spreadsheets
The final rule of data club:SELECT DISTINCT = Poor data knowledge
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CapabilityGAP Analysis of our skills and capabilityTraining focussed on the right areas Partnering with business and 3rd party consultant
OrganisationWorking with existing headcount and no new hiresEstablish clear data ownership with the businessClear roles and responsibilities across the organisation
ProcessDefining how we operateTesting with the business and refining to suit the culture Being agile and meeting the business needs
Competency building
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The accountants and finance professionals who succeed in the future will form a bridge between data science and data art, combining analytical skills and sophisticated models developed by statisticians with the skills of data art and ‘storytelling’.
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Sexy Dashboards Must Have Clear Purpose
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Telling Stories with Data
turn it upside down
learn todistill
thinkinfographic
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Source: Bloomberg BusinessWeek
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All TasksTasks
Add Tasks
High Priority
Search
More Data in Decisions
New Analytic Methods
Analytic Culture
Big Data Action Plan for Finance and AccountingProfessionals
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Count what is countable, measure what is measurable, and what is not measurable, make measurable.