becoming a data driven organisation - prostrategy...2016/04/03 · becoming a data driven...
TRANSCRIPT
Becoming a data driven organisation
By Patrick Bryan
How do leaders describe data….
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• Being data-driven is the art and ability to leverage all business assetsto exercise judgment in the decision process – Stephane Hamel (Data & Analytics Leader)
• Data Driven Analytics is the mathematics which is the pattern of discovery & anomaly detection - Sammy Haroon (Director Enterprise Data Analytics, Baker Hughes, Inc.)
• Data is a raw material to be mined – Steven Adler (Chairman, Data Governance Council, IBM)
• Data is rapidly becoming a Business Issue, a Business Strategy Issue –Chris Mazzei (Chief Analytics Officer, EY)
• The goal is to move the company to be more insight driven – Hima Patel (VP
Enterprise Integration & Customer Collaboration, Merck)
Data Confidence
33
How bad can it be?
44
Everyone's view of data is different
55
• A man goes into a jewellers and buys an expensive watch …• Is it fraud – in which case the bank must stop it
• Is it money-laundering – in which case the bank must report it
• Does he have expensive tastes – in which case perhaps he would be interested in a loan?
• Has he just won the lottery – should the bank improve the services offered?
Threat
Obligation
Opportunity
Opportunity
How do we change?
66
• Grow a data driven culture…can I change how data is used?
• Governance, Integration and Quality
• Performance
• Analytics
Focus points for a Data and Analytics Driven Organisation
Gartner’s key to establishing a data driven organization
77
1
CDO/CIO Mobile/Web App DevelopersBusiness Users
Develop a curiosity
driven workforceMove from elite few to
empowered many
Imagine what’s possible!
Lead a data-driven
transformation
Fuel their curiosity
and creativity
Innovate faster
and scale securely
An example transformation
88
1 THE ENTERPRISE DATA WAREHOUSE
An example transformation
99
1• Time to deliver business value down from 6 months to 2 months
• Efficiency up 20%
• Daily cost of teams down 40%
• Feature delivery cost down 30%
• 100% of features delivered on time and on budget
• Happy Stakeholders (49% - 20% = NPS 29 )
• Happy Teams (65% - 22% = NPS 43)
The Results
How likely are you to recommend us to a colleague?
How do we change?
1010
• Grow a data driven culture
• Governance, Integration and Quality… can I trust it ?
• Performance
• Analytics
Focus points for a Data and Analytics Driven Organisation
Data governance in action
1111
Canadian National Railway Company – Establishes data governance to
improve decision making
Establishes governance providing an unambiguous way to process and share
information
"IBM empowers users with information so that they can work more autonomously."
— Philippe Chartier, BI Team Lead, Information Delivery,The Canadian National Railway Company
Standardizes terminology into market share, including specific areas of strength
and weakness as compared to competitors
Accelerates analyticsto deliver faster insight from trusted data
The transformation: Standardized its metadata and business
terminology across the enterprise, creating a company-wide
glossary and a universal data model to improve decision-making.
Governance, Integration and Quality
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Information Governance Catalog
Understand & Collaborate
•Catalog technical metadata &
align w/ business language
•Manage data lineage
DataQuality
Cleanse & Monitor
•Analyze & validate
•Cleanse & standardize
•Define, manage & monitor
data rules + exceptions
DataIntegration
Transform & Deliver
• Provide scalability
• Power for any complexity
• Deliver in batch and/or real-time
Information
Governance
Data
IntegrationData
Quality
How do we change?
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• Grow a data driven culture
• Governance, Integration and Quality
• Performance…. can I make it faster ?
• Analytics
Focus points for a Data and Analytics Driven Organisation
Increased performance grows revenue and reduces costs
1414
Carphone Warehouse increases profitability through new revenue streams
& reduced costs
Up to 1200X faster performance; reports that once took an hour to run now take seconds
“IBM provided huge technical advantages & big business advantages. We can now insure devices on behalf of a bank in the UK, which we couldn’t have done before.”
— Paul Scullion, Head of Business Intelligence
50% reductionin time to market for new business intelligence
services
Increased performance grows revenue and reduces costs
1515
Appliances for AnalyticsSpeed - 10-100x faster than traditional custom
systems1
Simplicity - minimal administration and tuning
Scalability - petabyte+ scale user data capacity
Smart - high performance, advanced analytics
1 Based on IBM customers' reported results. "Traditional custom systems" refers to systems that are not professionally pre-built, pre-tested and optimized. Individual results may vary.
Purpose-built analytics appliance
Integrated database, server and
storage
Standard interfaces
Low total cost of ownership
Try it with your dataBring your data to our POC server
Bring our POC Server to your data
How do we change?
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• Grow a data driven culture
• Governance, Integration and Quality
• Performance
• Analytics….. how do I do it better !
Focus points for a Data and Analytics Driven Organisation
Grow customers using data algorithms
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eHarmony Attracts New Members by Understanding Behavior and Fine-
tuning Matching Algorithm
"Through the entire subscription lifecycle, the company tracks everything members do on the website. This process generates an enormous amount of data, which would be completely wasted without the ability to extract hidden insights about how members behave.”
— eHarmony C-Level executive
96% decreasein query run times (from 1 hour to 2 minutes)
100% increaseinto market in subscriber base
Reduced spendingOn low-return promotional activities
Types of Analytics
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DescriptiveGet in touch with reality, a single source of
the truth, visibility
PredictiveUnderstand the most likely future scenario,
and its business implications
PrescriptiveCollaborate for maximum business value,
informed by advanced analytics
CognitiveDeeply analytical computing systems that learn &
interact naturally with people
What happened?
What will happen?
What should we do about it?
Volume (data at rest)
Velocity (data in motion)
Variety (many forms of data)
Veracity (data in doubt)
Watson Analytics
How do we optimize a dynamic, Data
environment?
How to get started…
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Imagine it. Realize it. Trust it.
Build a culture
that infuses
analytics
everywhere
Invest in a big
data & analytics
platform
Be proactive
about privacy,
security and
governance