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BUSINESS INTELLIGENCE – NEXT WAVE REALTIME ACTION

BUSINESS INTELLIGENCE – NEXT WAVE REALTIME ACTION. Major CS Kaushik ex Director(EDWP) Consultant(IT & Banking Domain)- World Bank. Today’s Agenda. Major trend & challenges in BI CEO/CIO Priorities BI- Framework & Information Democracy BI-Priorities for maturity : Metrics

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BUSINESS INTELLIGENCE – NEXT WAVE REALTIME ACTION

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  1. BUSINESS INTELLIGENCE – NEXT WAVE REALTIME ACTION Major CS Kaushik ex Director(EDWP) Consultant(IT & Banking Domain)- World Bank

  2. Today’s Agenda Major trend & challenges in BI CEO/CIO Priorities BI- Framework & Information Democracy BI-Priorities for maturity : Metrics Business Domains –Subject Areas Business Value Creation - ROI Information Governance Framrwork Enterprise Information Architecture and Implementation Use past wave to ride next wave

  3. Building BI On Present technology • Information Governance • Data Governance –Master Data Management, Data Quality, Data Definition, Data ownership, Requirements • Metadata Governance • Business Rules Governance • Building Competency Centre – Bridge Gap of Business & IT (Alignment) – Faster Delivery • Manage Production, DR and Data Back up Resources • Integrate and Innovate by using tools for text and image mining • Adopt agile methodology & grow • Skill and Competence Building • Bridge Knowledge Divide • Use common resources of virtual storage and processing • Building actions with reporting and rationalise reports (Information Overload)

  4. 2010-13 CIO Priorities

  5. Shifting from Operational to decisional to operational – Stake Holders Decisional Strategic Reports (High marginal cost per user) Pre-Planned queries Management Dashboard Operational Data Reconciliation Marketing Campaign Analysis Cross-Selling Trading Risk Position Ad-Hoc Queries Business Performance Monitoring Basel II & Regulation Compliancy Fraud Detection Operational Datawarehouse (Low marginal cost per user)

  6. Information Systems Today CAG, MCG, GLOBL MARKET The reports are different – which, if any, can I believe? I can’t get that? Well… what can I get? TWO WEEKS? I need to make a decision before then. The future initiative is too costly and complex to deliver? How will I ever be able do this? Operational Reports, Analytics DependentEnd-users and Decision Makers Multiple/Custom Data Sourcing Multiple CustomisedData Marts DataSources Large Analyst Staff Disparate Reports Core Banking Solution, IT-FO BRANCHES, RBO LHOs,BO, A&C Trade Finance ATMs RISK, CIS, ALM, CMP INB SBUs PSG, M-banking CMP Treasury Operational Systems Analytical Repositories End users have poor ability to access information, low confidence in the integrity of the information and often cannot get the information needed from this environment. The ability to make superior decisions is compromised.

  7. Information Democracy Empowering Decision Making Enterprise Data Model ORDER ORDER NUMBER ORDER DATE STATUS ORDER ITEM BACKORDERED QUANTITY CUSTOMER CUSTOMER NUMBER CUSTOMER NAME ORDER ITEM SHIPPED CUSTOMER CITY QUANTITY CUSTOMER POST SHIP DATE CUSTOMER ST CUSTOMER ADDR CUSTOMER PHONE ITEM CUSTOMER FAX ITEM NUMBER QUANTITY DESCRIPTION Operational Reports, Analytics Large number of empoweredEnd-users and Decision Makers DataSources Organized Reports Few Analysts Data Warehouse ETL Retail Banking Corporate & Commercial Trading Finance Product Data Market Data Operational Systems Analytical Repositories End users have high ability to access information, confidence in the integrity of the information and often use the information in ways they have not imagined earlier!! Ability to make superior decisions !!

  8. Evolve Faster ACTIVATING MAKE it happen! • Query complexity grows • Workload mixture grows • Data volume grows • Schema complexity grows • Depth of history grows • Number of users grows • Expectations grow OPERATIONALIZING WHAT IS happening? PREDICTING WHAT WILL happen? Event-Based Triggering Takes Hold ANALYZING WHY did it happen? Workload Complexity Business Models- KPIs, Dashboards REPORTING WHAT happened? Batch Ad Hoc Analytics Analytical Modeling Grows Increase in Ad Hoc Analysis Continuous Update/Short Queries Event-Based Triggering Primarily Batch & Some Ad Hoc Reports Data Sophistication 9

  9. Readiness and Maturity (KDD) • Where are we with the current DW (DMs)? • Examine effectiveness of data usage, not develop report cards Data Knowledge BI Information HI Action CI Key BI= Business Intelligence CI= Collaborative Intelligence HI= Human Intelligence Connecting People, Processes, information & Technology

  10. Key Technology Trends – Next Wave Maturity & Value Creation Long overlooked as a critical factor in BI Success. Organizations are making the connection and are now placing a strong focus Intersection of CRM processes and BI. This aims to integrate disparate sets of data and analysis into a single solution. CDI, Analytical capability becomes a key differentiator Data Quality CRM & Customer Intelligence Adoption Key Performance Indicators displayed on a single screen with an ability to drill down at the details Dashboards & Scorecards Creation of virtual databases via real-time access and integration of operational source data Virtual Data Federation/ EII Performance Management Includes all Methodologies, Metrics, Process required to manage performance Involves complex statistical modeling for predictive analysis, data mining, applied analytics. Requires significant skills and competencies in data access and analysis. Advanced analytics experience renewed interest Advanced Analytics Cross Enterprise Analytics A notion of approaching “analytics” as a cross-disciplinary topic that transcends subject-areas and applications SOA Enabled BI Data Warehouse Appliances Web Services based architectures Callable BI Components, Networked BI applications aware of each-other Hardware and DBMS integrated and packaged to provide support for BI applications BI Technology available as part of the open source application development. It is an emerging area. Open Source DBMS 0 – 2 Yrs 2 – 5 Yrs 5 - 10 Yrs Time to Maturity (Plateau of Productivity per Gartner’s Hype Cycle)

  11. Incremental Value Personalization Effect Positive Returns Predictive Analytics Break Even ROI (%) Business Intelligence Cumulative ROI Negative Returns Operational Systems Time (Years) P R E D I C T I V E A N A L Y T I C SROI: Good News/Bad News

  12. Information Democracy Model Sales Force Automation Marketing Automation Sales Planning Configuration Collaborative Design Revenue Management Channel Management Real-Time Personalization Guided Selling Relationship Marketing Order Management Marketing Planning Web / Telephony Self-Service Web Communication (Chat, Web, E-Mail, VoIP) Interaction Management Services Customer Contact Center Field Service Workforce Management

  13. BUILDING INTELLIGENCE Connecting People, Processes, information & Technology

  14. CRM, Corporate MemoryKnowledge Discovery in Databases (KDD)

  15. Collaborate (incentives) Augment (tool) The choice to change work practices requires answering four key questions: - Should we? (Business Value) - Can we? (Technology) - May we? (Governance) - Will we? (Work Priorities) Z 1 2 Tool System Human System Delegate (outsource) Automate (self-service) 3 4 Demand Relationship + Preference Business Value Strategy + Risk Process Automate + Augment Organisation People + Culture Revenue Growth Cost Reduction Transformation Technology 16 Innovation Productivity

  16. Credit Risk - Standardized Approach • Credit Risk - Internal Ratings Based (IRB) • Probability of Default (PD) • Loss Given Default (LGD) • Exposure At Default (EAD) • Effective Maturity (M) • Expected Loss (EL) And Provisions • Securitization Framework • Operational Risk Loss Data store Result Data BII Operational Risk Engine Loss Data Customer Result Data Internal Credit Risk Engine Collaterals Extraction, Validation Result Data Interest Rate Risk Engine Financial Data store Credit Result Data BII Credit Risk Engine Core Banking Products Operational Transformation Data Marts Data source Extraction Data store & calculation Internal Reporting Basel II Reporting (Credit, Op Risk, Interest) Regulatory Reporting Market Disclosures Historic Data store Rating, PD, LGD, CCF Models Reporting Metadata Warehouse Administration Integrated Business Intelligence IFRS, US GAAP,Basel II/III Architecture

  17. BST • Customer Complaints • Delinquency Analysis • Customer Loyalty • Market Analysis • Campaign Analysis • Cross Sell Analysis • Customer Attrition Analysis • Customer Behavior • Lead Analysis • Customer Interaction Analysis • Customer Investment Profile • Individual Customer Profile • Wallet Share Analysis Relationship Marketing • Profitability Analysis • Channel Profitability • Customer Lifetime Value • Customer Profitability • Location Profitability • Product Profitability • Product Analysis • Organization Unit Profitability • Performance Measurement • Business Procedure Performance • Transaction Analysis • Activity Based Costing Analysis • Insurance Product Analysis • Investment Arrangement Analysis Profitability • Interest Rate Risk Analysis • Customer Credit Risk Profile • Credit Risk Assessment • Credit Risk Mitigation Assessment • Securitization Analysis • Operational Risk Assessment • Authority Profiling • Credit Risk Analysis • Debt Restructuring • Involved Party Exposure • Location Exposure • Non Performing Loan • Operational Risk Loss Analysis • Outstandings Analysis • Portfolio Credit Exposure • Security Analysis • Liquidity Risk • Collections Analysis • Insurance Risk Profile Risk • Net Interest Margin Variance • Structured Finance Analysis • Equity Position Exposure • Income Analysis • Capital Allocation Analysis • Capital Procurement • Credit Loss Allowance • Funds Maturity Analysis • Interest Rate Sensitivity • Liquidity Analysis • Short Term Funding Management • Financial Management Accounting Asset & Liability Management • Central Bank Reporting • Financial Capital Adequacy Analysis • Structure Of Regulatory Capital • Foreign Financial Account Analysis • Suspicious Activity Analysis • Transaction Activity Analysis • SOA Balance Sheet Analysis • SOA Cash Flow Analysis • SOA Statement Of Change In Shareholders' Equity Analysis • SOA Statement Of Income Analysis • Cash Flow Direct Financial Institution Analysis • Cash Flow Indirect Financial Institution Analysis • Income Statement By Function Analysis • Income Statement By Nature Analysis • Income Statement Financial Institution Approach Analysis • Statement Of Changes In Equity Analysis • Balance Sheet Portfolio Basis Approach Analysis • Balance Sheet Classified Approach Analysis • Balance Sheet Order Of Liquidity Approach Analysis • Balance Sheet Net Assets Approach Analysis • Cash Flow Direct Analysis • Cash Flow Indirect Analysis • SOA Analysis Compliance

  18. Realise Information Democracy • We need more efficient internal systems • Design, implement, and manage internal systems that support effective decisions • Our Challenges include • Taxonomy, Metadata, Data Dictionary, Business Rules, Data Quality, Data completeness • Leveraging existing assets while maximizing investment in new systems by IT governance • With major focus on integration and controls • Reducing non-value-added processes related to internal systems while promoting interoperability and reusability by integration of transactions and information architecture • Stretching budgets while facing increased requirements related to financial and tax reporting • Getting disparate systems to communicate by architecture

  19. Modern operational BI platform requirements • The architecture must be designed to : • Integrate into business processes and organizations, creating interactions between Business Intelligence and Transactional processes • Produce a consolidated picture of the business (master data, ODS, physical/virtual data marts, pre-built cubes, dashboards…), integrating the archive of detailed historical data • Shorten latency between transactional and analytical worlds BI together with Transactional processes run the business “We can't solve problems by using the same kind of thinking we used when we created them.” Albert Einstein « Database technology generated the concept of datawarehouse. If technology was powerfull enough, there would be no need for separating operational and analytical environments.» Pascal Paulin, Head Architect Dexia Group

  20. We Need to Move Look for Resilience Not Sustainability Performance Management IT Governance Enterprise Risk Management Customer relationship Management Corporate Memory KMS Dynamic Reporting Dynamic Actions Technology (Transactions & Information)

  21. Sales+Market Basket+Customer+Profitability+Inventory Analysis AnalysisAnalysisAnalysis Supplier Data Business Value Financial Data Customer Data Transaction Data EDW Investment Product Data Data Mart Consolidation Leveraging the Value of EDW

  22. REAL-TIME ENTERPRISE

  23. Metrics for Readiness and Maturity Level

  24. XBRL • XBRL :Goal • XBRL for active information management(AIM) • Information Re-Engineering through :Global Ledger & Financial Reporting • Realising new world of standards : SOA • XBRL : Continuous Audit Framework • XBRL Taxonomy & Metadata : SBI Context • XBRL Application Advantage : Impact • XBRL Evaluation Criteria : ROI & Green IT FDIC/25

  25. BI Framework Business Drivers, Priorities & Metrics Enterprise Information Architecture Guiding Principles, Models, Policies, Standards and Procedures, Projects and Business Actions “DNA-Deoxyribonucleic Acid ” Data Definitions, Business Rules, Sources and Usage “Master” Data Business Data Organizational Accountability, & Methodology Information Management Databases and Documents Compliance Transactional Decisional Operational Data Data Data Information Value Chain Information Security / Privacy Information Security / Privacy Access, Classification, Auditing, Protection Access, Classification, Auditing, Protection Technology Infrastructure Technology Infrastructure EAI, HW/SW, ETL, Metadata Repository, Web, etc. EAI, HW/SW, ETL, Metadata Repository, Web, etc.

  26. Phased Subject Areas 10 6 Phase 1 Deployed to Production Phase 2 Deployed to Production Phase 1 Prototype 1 Phase 2 Prototype 1 Transition Phase 1 Prototype 2 Phase 2 Prototype 2 Conceptual Architecture Phase 1 Prototype 3 Phase 2 Prototype 3 ____________________________ 1 2 3 4 5 7 8 9 11 SEP OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Phase 1 Requirements Phase 2 Requirements Deliverable # Milestone

  27. Q Q U E S T I O N S A N S W E R S & A Thanks

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