Big Data Driven Transformations
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The document provides an overview of IBM's capabilities in big data and analytics through a presentation given by Piyush Malik. It includes: - Details of IBM's investments in big data and analytics capabilities including over $24 billion spent on acquisitions and 15,000 analytics consultants. - Examples of big data use cases across various industries and IBM's work with clients in areas like customer retention, fraud detection, and supply chain management. - Three case studies including how big data transformed industries like industrial manufacturing, telecommunications, and financial services by providing more personalized services and improving operational efficiency.
![© 2015 IBM Corporation29
Direct Mail
BC
Agent, IVR
Online, Email
ATM
Mobile, SMS
Chat
“Inform” “Learn” “Target” “Present” “Engage” “Measure”
Brilliant
!
Data is highly
integrated and
recent – provides
holistic, detailed
customer view
We have re-
calibrated to the
customer and have
new test and learn
abilities
“[My bank] knows
me and values my
relationship“
“[My bank] seems
to know what I
need and when I
need it.”
“[My bank] isn’t
always selling
something.”
“[My bank] always
gets me to the
right place and
never fails to follow
up.”
“There is real value
to me in getting all
my needs met by
one bank.”
Governance,
Prioritization &
Optimization
Customer Analytics
Integrated Data
We optimize
communication to
maximize value to
the bank and
customer
We deliver the
right information
to the right
channel – we
capture feedback
Staff and leaders
understand our
goals – have the
skill & motivation
to deliver
We understand
the value levers
and have
instrumented it to
“know”
DEPOSITS
INVESTMENTS
MORTGAGE
CARD
CustomerNeeds&SegmentStrategies
MassMarket|MassAffluent|SmallBusiness
Customer
Experience &
Treatment
Strategies
Vision of Target State: “I have a customer – what do they need most?”](https://image.slidesharecdn.com/cioroundableexperiencesharingbigdatatransformationssept2015-150911172127-lva1-app6891/85/Big-Data-Driven-Transformations-29-320.jpg)
Big Data Driven Transformations
- 1. © 2015 IBM Corporation CIO Roundtable Silicon Valley September 1st, 2015 Experiences of Big Data-Driven Transformations - Cases for Learning - Piyush Malik
- 2. © 2015 IBM Corporation2 Experience 25 years of cross-industry experience, multiple domains ~20 Years IT + Business Led & Data-Driven Transformation Currently directing strategic programs serving global clients CTO Emerging Technologies, BA&S Education Engineering - Electronics & Comms MBA - Finance & Systems Organizational Journey Telecom Product Management Software Development High Tech Project Management Management Consulting BI, Analytics, Data Transformations About Me Non Profits
- 3. © 2015 IBM Corporation3 1. Introduction 2. Cases for Transformation 3. Lessons Learned Agenda
- 4. © 2015 IBM Corporation4 Change or Perish Disrupt or be Disrupted What interests you, how YOU influence the world and how would you like to TRANSFORM We live in a data-driven world which is rapidly transforming
- 5. © 2015 IBM Corporation5 Mobile Social Cloud Analytics Business models under constant pressure Demanding and connected customers Great relationships can beat great products Confluence of Forces or Brewing the perfect storm? Security Social
- 6. © 2015 IBM Corporation6 1 in 2 business leaders do not have access to data they need 83% of CIO’s cited Business Intelligence (BI) and analytics as part of their visionary plan 5.4X more likely that top performers use business analytics 80% of the world’s data today is unstructured 90% of the world’s data was created in the last two years 20% of available data can be processed by traditional systems Source: GigaOM, Software Group, IBM Institute for Business Value" Seriously speaking, our world is getting disrupted by data
- 7. © 2015 IBM Corporation7 The IBM Data & Analytics Team IBM has invested more than $24 billion, including over $17 billion on more than 30 acquisitions, to build capabilities in big data and analytics. IBM has 15,000 business analytics and strategy consultants. IBM has over 7,500 Data Integration, Migration and ETL resources. IBM has more than 1,000 developers focused exclusively on Big Data technology development IBM has over 1000 Big Data resources with over 5 years average experience. IBM’s Research division has half of it’s resources focused on data, analytics, and cognitive computing. IBM resource capacity includes Big Data implementation roles around the world IBM is moving Twitter data beyond social listening to drive actionable insights that yield business results. Partnerships A groundbreaking industry- related partnership, the IBM- Weather Channel alliance is seeking to help businesses such as State Farm make better decisions through the use of the internet of things (IoT).
- 8. © 2015 IBM Corporation8 Spark – Apache Hadoop YARN – Apache Hadoop Core Hadoop Platforms & tools skills (partial list) Avro – Apache Hadoop Chukwa – Apache Hadoop Flume – Apache Hadoop HBase – Apache Hadoop HCatalog – Apache Hadoop Hive – Apache Hadoop Jaql – Unique to IBM Lucene – Apache Hadoop Oozie – Apache Hadoop Pig – Apache Hadoop Sqoop – Apache Hadoop ZooKeeper – Apache Hadoop Infosphere Streams R SAS Cognos SPSS Tableau YARN – Apache Hadoop Spark – Apache Hadoop Global Coverage of Skilled Resources
- 9. © 2015 IBM Corporation9 Typical Big Data Use Case Patterns we typically encounter Big Data Exploration Find, visualize, understand all big data to improve decision making Enhanced 360o View of the Customer Extend existing customer views by incorporating additional internal and external information sources Operations Analysis Analyze a variety of machine data for improved business results Data Warehouse Modernization Integrate big data and data warehouse capabilities to increase operational efficiency Security/Intelligence Extension Lower risk, detect fraud and monitor cyber security in real-time
- 10. © 2015 IBM Corporation10 Customer Retention and Growth Next Best Action Claims Fraud Smart Meters Asset Performance Management Next Best Action Network Analytics Tax Fraud, Waste and Abuse Consumer360 Insights Provider Outcome Analytics Deliver a Smarter Shopping Experience Merchandise Planning & Optimization Track & Trace Supply Chain Management Actionable Consumer Insight Compliance and Risk Social Program Integrity Banking E & U Government Retail Insurance Telco Healthcare Industrial Big Data Use Cases by Industry
- 11. © 2015 IBM Corporation11 Cost Reduction Growth • Clarity of traceability and data lineage • Complexity reduction • Simplified transition and migration approach • Advanced/Discovery Analytics • Business capability enablement • 360 degree analytics • Customer decision management • Business process transformation • Back end process improvement • Enabled self-service • Governance, compliance and security improvement Transformation Examples BD&A Solutions Operational Efficiency Data Lake Data Lake Operations Decision Model Management Enterprise Other Systems Of Insight New Sources Third Party Feeds Third Party APIs Internal Sources Governance, Risk and Compliance Team Information Curator Catalog Interfaces Raw Data Interaction SAND BOXES Information Integration, Governance, and Security Interaction Service Interfaces Data Ingestion Publishing Feeds Continuous Analytics Other Data Lakes Simple, ad hoc Discovery and Analysis Reporting Analytical Insight Applications Analytics Tools System of Record Applications Systems of Engagement DataLakeRepositories Harvested Data Descriptive Data Shared Operational Data Deposited Data Historical Data View-based Interaction Published Consumers &Contributors Cognitive Services Core Business Transactions Landing Area Zone - Raw, unrefined data I InterchangeArea–isolationlayer = denotes data refinery services Data Lake Architecture Large US Beverage Company Multinational Financial Services Co Large Latin American Insurer
- 12. © 2015 IBM Corporation12 1. Introduction 2. Cases for Transformation 3. Lessons Learned Agenda
- 13. © 2015 IBM Corporation13 1. Industrial 2. Telecom 3. Financial Services Three Cases
- 14. Do you recognize this?
- 15. © 2015 IBM Corporation15
- 16. © 2015 IBM Corporation16 16 Social Analytics With an IBM Social Analytics information service, you can decode the psychological genotype of your customer to achieve unprecedented customer intimacy Psychological profile Personality Needs Values Activity profiles IBM FOAK‘s with … Two retailers Three hotel chains Two airlines Two governmental departments Followers analyzed 200+ million Tweets 300K+ users analyzed
- 17. © 2015 IBM Corporation17 Inventions from IBM Research offer new ways to uncover insights from social data Harness viral effects in customer communities to optimize interactions Influencer Analysis Micro-segmentation Use unstructured social media data to build refined segments and detect life event triggers before they happen Watson Personality Insights Build new segments based on an understanding of inherent personality traits to grasp attitudes, traits and needs BigMatch Match social profiles with enterprise data for deeper, more comprehensive views of customers Shortening the time-to-value and easing the burden of data integration
- 18. © 2015 IBM Corporation18 1. Industrial 2. Telecom 3. Financial Services Three Cases
- 19. © 2015 IBM Corporation19 What is changing in the Telecom industry Mobile data explodes Consolidation continues Consumers are seizing control Over-the-top (OTT) providers thrive 15 multi-country (10 or more countries) companies now control > 3 billion subs By 2016, mobile traffic projected to grow to 11 exabytes / mo; 70% of that video content 4 companies make up 70% of the total market value of the top 25 drivers of internet traffic: Apple, Google, Amazon and Facebook Only 18% of people trust information from retailers and manufacturers
- 20. © 2015 IBM Corporation20 Big Data is Transforming Telecommunications Industry Telecommunications Reactive network and services based on limited customer data Highly personalized services based on customer behavior
- 21. © 2015 IBM Corporation21 MEDIA PUBLISHED Published by “The Star” on 3rd January 2012 GBS Led, collaboration with SWG for IBM's Biggest Telco Analytics Win in ASEAN (3Q, 2011), followed by biggest Enterprise Marketing Management – Next Best Action win in ASEAN (1Q, 2012)
- 22. © 2015 IBM Corporation22 Enterprise BI - Deal Timeline Phase III: IBM selected Phase II: Proof-of-Concept (POC) and solution design Phase I: Proposal Development & Submission Q3 2010 22 Q3 2011Q2 2011Q1 2011Q4 2010 Dec Mar Jan Feb Mar/Apr Aug RFI Issued RFP Issued Proposal Submitted Jul Oct POC Team Selected POC Conducted Contract Signed Win Notification Netezza POC Conducted Netezza replaces Teradata Sep
- 23. © 2015 IBM Corporation23 23 Celcom BI “Blue Stack” Solution Telco Data Warehouse Infosphere Datastage Products Services Consulting Services & Systems Integration Application Management Services STG
- 24. © 2015 IBM Corporation24 Data Sources Campaign Fulfillment NBA Solution Unica Marketing Operations AAS Files BI Complex Event Processing (CEP) SMSC Call Center Outbound Calls MMSC Email USSD NGIN Kenan FX People Management Workflows & Approvals Reports Calendar Plan Management Budget CIFM CIFM Campaigns Offers Reports Session Optimization Real-time Campaign Legend Phase 1 Phase 2 Digital Asset Red Font – via file transfer
- 25. © 2015 IBM Corporation25 NBA - Implementation Strategy & Delivery Timeframe NBA Phase 1 Unica Campaign & Unica Marketing operations (limited features) Integration with: SMSC, AAS, NGIN, Outbound dialer and Call center NBA Phase 2 Unica Marketing operations (all in scope features), Unica Optimize & Unica Interact Integration with: MMSC, BI, USSD, Email, Kenan FX, CEP NBA Future Roadmap Integration with: • Additional channels (e.g. Web, Call- Center) • Additional Fulfillment systems (e.g. SMP) ** All campaigns to run on Unica Integrated Marketing Management platform . Foundation • Batch campaigns • Closed loop marketing Outbound real-time • Real-time outbound campaigns • End to end marketing process automation Inbound Real-time • Real time Inbound campaigns • Integration extended to other fulfillment and Communication systems 4.5 Months 5.5 months Future Roadmap Phasing off the current Campaign System Building foundation
- 26. © 2015 IBM Corporation26 1. Industrial 2. Telecom 3. Financial Services Three Cases
- 27. © 2015 IBM Corporation27 A Large Latin American Bank asked us to help them define an information management transformation roadmap The high-level roadmap justifies the transition from current to future state, as well as describing the initiatives needed to realize the strategic vision Information Management Transformation Agenda Understand Primary Business Challenges Assess Current Information Capabilities and Prioritize Gaps Identify Potential Business Value Develop Recommendations and Potential Roadmap Web Enterprise Portals Composite & Collaborative Applications Mobile Devices & Disconnected LOB Applications Productivity Applications InformationServices TransportandDelivery Data Sources Analytical Metadata Data Domains Information Delivery Channels Enterprise Search Unstructured Data Master DataOperational Security,PrivacyandCompliance Information Infrastructure Network & Middleware Systems Management & Administration Systems Query & Reporting BI & Performance Management Dashboards & Visualization Exploration & Analysis Operational Intelligence Metrics & Scorecards Planning, Budgeting, Forecasting Data Management Enterprise Information Foundation Metadata Management Content Management Industry Models, Solution Templates, Analytical Applications Mining OrchestrationandCollaboration Storage Trusted Information Managed Trusted Information Information Integrity Information Lifecycle Management Hierarchy Management Event Management Records Management Content-centric BPM Information Integration Balance & Controls Strongly addressed Not addressedNeeds improvement Not applicable
- 28. © 2015 IBM Corporation28 Delivery of transformation followed an ambitious 3 year roadmap Transforma- tio n PM OData gov ern anc e mo del Data def init ion & qu alit y Data model (op era tio nal an d inf or- ma tio nal ) Operational dat a arc hit ect ure Informa- tio nal dat a arc hit ect ure Business val ue pro gra ms 1 2 3 4 5 6 7 Collect requirements for applications Run ongoing PMO activities Build reference MDM Define data owne rs per OU TextTextData cleansing efforts Build the data dictionary (metadata) Risk and Finance Wave 1 Wave 2 Wave 3 Consolidation Design the conceptual data model Customer Products Transactions Corporate model Build / adjust the logical data model Customer Products Transactions Define tools for logical model Staff and laun ch the CD MOStand up Gov. Com mitt ees TextTextPilot and implement OU data quality committees Build data servicesDesign data services Evaluate existing data services solutions within <Client> Assess s o l u t i o n f o r r e f e - r e n c e M D M Develop MDM strategy and access solutions TextTextCustomer Products Transactions Map, assess and adjust provisioning points Customer Products Transactions Build ETL and DB environments Solution Outline Build/adapt Repositories ( DW and ODSs ) Release 2 TextTextOngoing data quality efforts Collect business requirements per OU Risk and Finance Wave 1 Wave 2 Wave 3 Consolidation Map and prioritize of business initiatives Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct NovJan Dec 2013 2014 - 2016 Implement quick wins Common ops dashboard Improved Lead Generation Updated Fee Policies Detail, build and implement business initiatives Cross-company risk optimization initiatives Cross-sell improvement initiatives Setup the PMO structure Changes to data related application projects Prioriti- ze Assess and ali-gn with target Adjust applications to align data sources with target architecture Run ongoing quality committees Business initiatives to deepen customer relationship Business initiatives to control risk & fraud Build/adapt Repositories (DW and ODSs)– Risk & Customer Build/adapt Repositories ( DW and ODSs ) Release 3 Build/adapt Repositories ( DW and ODSs ) Release 4 Redesign roadmap and execution of CIC to target architecture (involved parties MDM) Release 1 Release 2 Adjustments Redesign roadmap and execution of Fluir/V9 to target architecture (product MDM) Release 1 Release 2 Adjustments Data Management Transformation is an ambitious program, fully integrated into the Bank ▪ Incorporates several current critical in- flight initiatives (Fluir, CIC, DW/BI, …) ▪ More than 500 development resources in peak ▪ Interface with all of Bank’s Operating Units (business requirements, governance setup, business capabilities) and ATEC areas (systems, infrastructure, architecture, ...)
- 29. © 2015 IBM Corporation29 Direct Mail BC Agent, IVR Online, Email ATM Mobile, SMS Chat “Inform” “Learn” “Target” “Present” “Engage” “Measure” Brilliant ! Data is highly integrated and recent – provides holistic, detailed customer view We have re- calibrated to the customer and have new test and learn abilities “[My bank] knows me and values my relationship“ “[My bank] seems to know what I need and when I need it.” “[My bank] isn’t always selling something.” “[My bank] always gets me to the right place and never fails to follow up.” “There is real value to me in getting all my needs met by one bank.” Governance, Prioritization & Optimization Customer Analytics Integrated Data We optimize communication to maximize value to the bank and customer We deliver the right information to the right channel – we capture feedback Staff and leaders understand our goals – have the skill & motivation to deliver We understand the value levers and have instrumented it to “know” DEPOSITS INVESTMENTS MORTGAGE CARD CustomerNeeds&SegmentStrategies MassMarket|MassAffluent|SmallBusiness Customer Experience & Treatment Strategies Vision of Target State: “I have a customer – what do they need most?”
- 30. © 2015 IBM Corporation30 Executive Sponsors Bank Executive(s) IBM Executive IBM Executive Service Delivery Committee Bank Executive(s) IBM Service Delivery Program Executive Program Management Office Contract Management Functional Committees Data Management Analytics Center of Excellence Technical Steering Business Initiative Prioritization Program Management End-User Change Management LOBs Card CRE GCSBB GCIB GWIM HR Finance … Finance ERP Operations BusinessCase Review Transition Management Executive Committee Bank Executive(s) IBM Executives Teradata Executive SAS Executive Management Committee Bank Executive(s) IBM Executives Teradata Executive SAS Executive Application Development / Maintenance Project Managers (PMs) Delivery Project Executives (DPE) Card CRE GCSBB GCIB GWIM HR Finance … Auto Cards Comm’l Loans Cons Loans Customer Demand Deposits Finance Insurance Mktg/Sales MortgageLoans /RE Risk TimeDeposits Treasury Wealth BASE INITIATIVE Transformation Delivery Metadata Lead Logical Modeling Lead ETL Lead Release Manager(s) Physical Modeling Lead Semantic Modeling Lead SAS Optimization Lead Transformation Project Executive Key “what’s different” organizational recommendations Chief Data Officer Organizational model and governance structure impact
- 31. © 2015 IBM Corporation31 1. Introduction 2. Cases for Transformation 3. Lessons Learned Agenda
- 32. © 2015 IBM Corporation32 Lessons from Successful transformations A clear vision, and strong consistent execution Strong flexible technology as key enabler Top management support and business -IT joint responsibility. Complex program management approach A visionary leader in the transformation Focus on supporting the change HOW DO WE TRANSFORM? Don’t lose customer intimacy on the way Don’t underestimate market differences Don’t save on “best people for the job” Expect resistance to change - Be ready PITFALLS TO WATCH
- 33. © 2015 IBM Corporation33 Improve data quality and accesscontrols Lessons learned from successful transformations Reduce complexity Reduce operatingcosts Enhanceand/or create new analytical capabilities Keys to transformation success Program Governance Change Management Innovation Run the Program like an acquisition Leverage a partner who will force you to stop doing things which prevent you from meeting your objectives Recognize that the level of change is directly proportional to the level of innovation Embed business case review in the Program to ensure benefits are delivered and promoted Create powerful and influential Functional Committees to inform, direct and advise the Program These committees include a significant focus on prioritizing Business Initiatives and ensuring that Data Management has a seat at the current 7 Initiative Prioritization groups Leverage those committees to drive a closer connection between the LOBs and IT Appoint a Chief Data Officer (CDO) who has tangible authority within IT and Business domains Launch an early-and-often dedicated Change Management program Leverage assets you already own to accelerate process re- engineering tied to analytic Transformation Address the human dimension of end-users in the face of process, data and technology change Begin with the End in Mind and leverage innovation during the transformation Leverage a Big Data Center of Excellence to drive Innovation and Adoption Transformation priorities
- 34. © 2015 IBM Corporation34 Skills Matter.. No matter how rare.. Acquire, Hire or Partner
- 35. © 2015 IBM Corporation35 Adopt a Sound Analysis Approach Understanding • Current Situation • Performance • Aspirational & Business Objectives (Casita) • Challenges Previous Analysis Banorte Information Public Information Executive Interview Findings • Opportunity Areas • Gaps Solutioning • Enablement • Projects • Quick Wins Roadmap • Project Domains • Dependencies • Sequencing Business Case • KPIs • Benefits Partnership Model • Scenarios • Timing • T&C Next Steps 1 2 3 4 5 6 7 35
- 36. © 2015 IBM Corporation36 This streamlines business and technology processes enterprise-wide Step 1: Insight: Prioritize future develop areas from economic and strategic focus Economic Assessment Contribution of Components Competency Map – Competency Requirements of Components Customer Relationship Management Portfolio/Risk Management Loan Origination andServicing Accounting andAudit Reconciliatio nand Settlements Finance Planning & Analysis Monitor & Control Operations & Execution Regulatory & Compliance Budgeting & Forecasting Portfolio Management and Hedging Customer Relationship Trade Execution Credit Analysis Loan Underwriting Bank Policies and Procedures Credit Risk Management Pipeline Management Collateral Analysis Marketing and Syndication Collateral Management Portfolio Risk Management Trading Management Loan Portfolio Acquisition Market Risk Management Research Analytics Loan Funding & Setup Loan Servicing & Administration Pricing Document Management Reconciliation and Control Cash Control Treasury Management Compliance Guidelines & Control Management Reporting Financial Reporting GL & Accounting Operational Control Customer Relationship Management Portfolio/Risk Management Loan Origination andServicing Accounting andAudit Reconciliatio nand Settlements Finance Planning & Analysis Monitor & Control Operations & Execution Customer Relationship Management Portfolio/Risk Management Loan Origination andServicing Accounting andAudit Reconciliatio nand Settlements Finance Customer Relationship Management Portfolio/Risk Management Loan Origination andServicing Accounting andAudit Reconciliatio nand Settlements Finance Planning & Analysis Monitor & Control Operations & Execution Regulatory & Compliance Budgeting & Forecasting Portfolio Management and Hedging Customer Relationship Trade Execution Credit Analysis Loan Underwriting Bank Policies and Procedures Credit Risk Management Pipeline Management Collateral Analysis Marketing and Syndication Collateral Management Portfolio Risk Management Trading Management Loan Portfolio Acquisition Market Risk Management Research Analytics Loan Funding & Setup Loan Servicing & Administration Pricing Document Management Reconciliation and Control Cash Control Treasury Management Compliance Guidelines & Control Management Reporting Financial Reporting GL & Accounting Operational Control Regulatory & Compliance Budgeting & Forecasting Portfolio Management and Hedging Customer Relationship Trade Execution Credit Analysis Loan Underwriting Bank Policies and Procedures Credit Risk Management Pipeline Management Collateral Analysis Marketing and Syndication Collateral Management Portfolio Risk Management Trading Management Loan Portfolio Acquisition Market Risk Management Research Analytics Loan Funding & Setup Loan Servicing & Administration Pricing Document Management Reconciliation and Control Cash Control Treasury Management Compliance Guidelines & Control Management Reporting Financial Reporting GL & Accounting Operational Control 654 3 2 1 5. Fees& Commissions4. Collateral Management 1. Management Reporting 3. Risk Management 6. System Rationalization 2. Sales Support Step 3: Investment: Create detailed roadmap and business case Cluster: Develop customized activity-focused view of Bank Step 2: Architecture: identify detailed gaps in organization procedures and systems against plan Current State Application Submission Straight Through Processing (STP) Workflow External Partners Contract Policy Set-up Cost Savings Revenue Reputation Impact H H H H H L L L H M H L Base Level Differentiating Paper submissions of applications. Applications checked manually for accuracy and completeness at point of sale No STP Manual processes to route work across departments. Cases are not differentiated (e.g. $1MM policy treated the same way as a $100k policy) No or limited use of external partners for activities such as mail processing, document imaging, applications data entry, application processing & medical information collection Paper (and fax & phone, if applicable) and stand-alone electronic application submission for electronic apps, accuracy and completeness checked in real-time. Incentives for electronic submissions. Partial STP – certain processes require human intervention (e.g. app received electronically, but reviewed by human for underwriting/suitability review) Workflow is largely automated, using smart logic for routing and prioritizing work. Paper documents are imaged for workflow. Timely follow-through on missing information. Quality reviews built into workflow for some processes (e.g. for processing certain products) Use of external partners for low-end activities such as mail processing, document imaging and application data entry Paper and integrated electronic application submission. App submission integrated with front- end used by producers. App checked for accuracy and completeness for STP. Acknowledgement of receipt and proactive notification of status to producers & clients Full STP capability with no human intervention for selected products or channels. Expert engine for automated underwriting/suitability review, automated set-up and issue. Selected financial transactions and postings are electronic Workflow is fully automated using imaging. Work is dynamically prioritized and routed based on performance targets. Continuous process to reduce missing information. Quality processes based on international standards (e.g. Six Sigma, TQM) Strategic outsourcing of low and high-end activities, including application review. Leverage offshore resources to reduce cost and improve cycle time Competitive Target quantitativeand qualitative financialim pactevaluations (scenario based) Over Extension Gaps Duplication - IBM’s Differentiator Business Direction Setting Business Control Functions Execution Functions Customer Sales and Servicing Planning Channel Administration Operational Risk Management Business Dev Planning Bus Strategy & Planning Business Unit Tax Admin Market Risk Management Campaign Planning Product Portfolio Planning Interaction Analytics Sales Administration Channel Operations Account Services Oversight & Fails Handling Fraud/AML detection and resolution Customer SegmentationBusiness Unit Admin & Accting Business Systems & Enterprise Arch Audit Product Develop. Oversight Campaign Management Product Portfolio Management Human Resource Mgmt Legal Services & Regulatory Compliance Facilities & Procurement IT Service Delivery Correspondent Bank Admin Credit Facility Management Customer Accounting Funds Transfer & Payments Correspondence Admin. Market Research Product Development Product Reference Information Campaign Execution Non Cash Inventory Admin Cash and Currency handling Customer Sale and Cross Sell/Up Sell Applications Customer Service Brokered Product Sales & Market Trading Contact/Event History Customer Reference Information Customer Credit Decisioning Customer Relationship Management Case & Exception Handling Product Deployment Financial Planning and Budgeting Financial Control and Reporting Account Reconciliation Treasury Operations Financial Ops & Position/ Balance Management Accounting General Ledger Collections & Recovery Document Management & Archive Collateral Admin Business & Resource Administration Customer Sales & Servicing Customer Management New Business Development Channel Services Operational Services Financial Management Asset & Liability Management Market Information Channels (Assisted) & Transaction Consolidator Comms & External Relations Enterprise Portfolio Management Asset and Liability Oversight Asset Liability Tracking Asset Securitization Customer Behaviour Modeling Customer Relationship Oversight Customer Credit Oversight Channels (Self Service) Trust & Investment Services Rewards Admin. Shareholder & Custodial Services,Clearing & Settlement Transaction Services Operational Effectiveness Enterprise Management Effectiveness Sales & Servicing Customer, Proposition & Marketing Pricing Credit Risk Management 1 Product Development & Deployment Market Research Customer Segmentation Customer Behaviour Modelling Customer Reference Information Business Development Product Reference Information Campaign Management Business Dev Planning Business Unit Tax Admin Regulatory Compliance Credit Risk Management Operational Risk Management Market Risk Management Treasury Operations Financial Control and Reporting Risk&FinancialManagement Financial Planning and Budgeting Asset Securitization Business Unit Accounting Enterprise Portfolio Management Facilities & Procurement Business Unit Admin Human Resource Mgmt Bus Strategy & Planning Comms & External Relations Business Systems & Enterprise Arch Business Infrastructure Accounting General Ledger Legal ServicesAudit Interaction Analytics Customer Services Case & Exception Handling Customer Sales Customer Interaction Cross Sell/ Up Sell Customer Relationship Management Channels (Assisted) Market Trading Brokered Product Sales Sales/Channel Admin Customer Transaction Consolidator Channels (Self Service) Merchant Relations & Operations Production Fund Transfer and Payments Cards Admin & Servicing Issuance and Placement Trust Services Cards Authorization Fund Asset Administration MortgagesDeposits Consumer Lending eTradingBank Guarantee Order Management Corporate Advisory Services Cash Management Bancassurance Trade Finance Services Investment Portfolio Management Corporate Lending Collateral Admin Credit Facility Management Non Cash Inventory Admin Non Correspondent Banking Shareholder Services Cash and Currency handling Market Information Correspondence Admin Customer Accounting Fraud/AML detection and resolution Collections & Recovery Account Reconciliation Account Services Oversight Correspondent Bank Admin Document Management and Archive Operational Services Rewards Admin Clearing and Settlement WIRE (SWIFT) Channel Operations Custodial Services Payments Fails Handling Position/ Balance Management Financial Operations Major Gaps Needs improvement Analysis Key Fit for purpose Limited Data/NA Financial Margin Expected Losses Financial Cost OPEX Earnings Financial Income Operational Cost Admin Cost Other costs Fee Income Lending Asset Growth Rate (%) Deposits Growth Rate (%) Corp BankingFee Income Retail BankingFee Income Other FeeIncome Brokerage Volume Growth Rate (%) Investments AUM Growth Rate (%) Trust Admin AUM Growth Rate (%) Investments Performance Growth Rate Insurance Premium Growth Rate (%) Collections Volume Growth Rate (%) Payments Volume Growth Rate (%) Trading Volume Growth Rate (%) Trade Finance Volume Growth Rate Other Revenue Lending Origination Cost Improvement Loan Servicing Cost Improvement Deposits Servicing Cost Improvement Equities Servicing Cost Improvement Servicing Cost Improvement IT Cost Improvement Fixed Assets Cost Improvement Admin Cost Improvement In Progress Use a Proven Transformation methodology to translate business value to specific projects
- 37. © 2015 IBM Corporation37 Reference Architectures GBS Agile Method, DevOps Adoption Framework Industry Models Including Deployment Patterns Frameworks, ETL/ELT Patterns, and Testing Assets A proven frameworks for building reusable enterprise Big Data, Analytics, MDM and Integrationsolutions that are extensible, robust, and easier to maintain A proven approach for accomplishing the timely and cost- effective delivery of the Big Data, Analytics, MDM and Integrationsolutions. This includes Continuous Integration & Virtualized Services An insurance specific Industry framework that includes accelerators focused primarily around requirements, data architecture, and data deployment patterns From infrastructure to to A component-based approach that accelerates delivery and lowers total cost of ownership by creating reusable data integration analysis, design, and construction models, components and code Change Management Framework A proven approach for driving organizational alignment and ensuring the adoption and use of delivered capabilities Leverage IP and Acceleration Assets
- 38. © 2015 IBM Corporation38 Analytics: The real world use of big data Fundamentals of big data Analytics: A blueprint for value Extracting value from data and analytics 2012 2013 2014 Big Data to Fast Value Analytics: The Speed Advantage Information Governance in a big data world Information Governance for big data landscape IBM Big Data Platform IBM RTAP with Streams Analytical Accelerators Intro to Big Data Lake Solution Models for Big Data Analytics Emerging research & concepts in big data IBM Institute of Business Value Though Leadership Studies Big Data Analytics use cases in action Leverage IBM’s Big Data Thought Leadership, Publications, Assets & Accelerators
- 39. © 2015 IBM Corporation39