Becoming a data driven organisation - ... 2016/04/03  · Becoming a data driven...

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  • Becoming a data driven organisation

    By Patrick Bryan

  • How do leaders describe data….


    • Being data-driven is the art and ability to leverage all business assets to 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


  • How bad can it be?


  • Everyone's view of data is different


    • 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?





  • How do we change?


    • 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



    CDO/CIO Mobile/Web App DevelopersBusiness Users

    Develop a curiosity

    driven workforce Move from elite few to

    empowered many

    Imagine what’s possible!

    Lead a data-driven


    Fuel their curiosity

    and creativity

    Innovate faster

    and scale securely

  • An example transformation



  • An example transformation


    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?


    • 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


    Canadian National Railway Company – Establishes data governance to

    improve decision making

    Establishes governance providing an unambiguous way to process and share


    "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 analytics to 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


    Information Governance Catalog

    Understand & Collaborate

    •Catalog technical metadata &

    align w/ business language

    •Manage data lineage

    Data Quality

    Cleanse & Monitor

    •Analyze & validate

    •Cleanse & standardize

    •Define, manage & monitor

    data rules + exceptions

    Data Integration

    Transform & Deliver

    • Provide scalability

    • Power for any complexity

    • Deliver in batch and/or real-time




    Integration Data


  • How do we change?


    • 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


    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% reduction in time to market for new business intelligence


  • Increased performance grows revenue and reduces costs


    Appliances for Analytics Speed - 10-100x faster than traditional custom


    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


    Standard interfaces

    Low total cost of ownership

    Try it with your data Bring your data to our POC server

    Bring our POC Server to your data

  • How do we change?


    • 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


    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% decrease in query run times (from 1 hour to 2 minutes)

    100% increase into market in subscriber base

    Reduced spending On low-return promotional activities

  • Types of Analytics


    Descriptive Get in touch with reality, a single source of

    the truth, visibility

    Predictive Understand the most likely future scenario,

    and its business implications

    Prescriptive Collaborate for maximum business value,

    informed by advanced analytics

    Cognitive Deeply 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


  • How to get started…


    Imagine it. Realize it. Trust it.

    Build a culture

    that infuses



    Invest in a big

    data & analytics


    Be proactive

    about privacy,

    security and