Demonstrating Big Value in Big Data with New Analytics Approaches
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This document discusses IBM's journey to establishing an Analytics Center of Excellence (ACE) to overcome challenges with big data analytics. It describes how IBM previously had siloed analytics groups across its 400,000 employees and 200 locations. To address this, IBM developed a strategic plan through organizational readiness. This included standing up a virtual ACE team to develop standards, provide services, and align analytics with business strategy across the enterprise. The ACE also focused on quickly enabling a cloud prototype and user community to start realizing value from big data.
Demonstrating Big Value in Big Data with New Analytics Approaches
- 1. Demonstrating Big Value in Big DataDemonstrating Big Value in Big Data with New Analytics Approaches Julie Severance Global Leader, ACE Program IBM Analytics, Customer Programs @analyticalist julieannseverance
- 2. 2 Data is the next natural resource and it will change how decisions are made in the marketplace. Analytics of that data will form the silver thread that weaves through the future of everything we do. Ginni Rometty Chairman and CEO IBM Corporation Early Analytics focus was on physical assets Then Expanded to non physical processes Now Used across the enterprise $24B Analytics Acquisitions & Growth $6B Annual Spend in Research 500+ Ph.Ds $1B Watson Group Formation “ “ Building A Smarter Enterprise at IBM®
- 3. EngagementEngagement requires a systematic approach DataData is the new basis of competitive advantage CloudCloud is the path to new business models The New Era Defined by three key shifts
- 4. Manage Data Host applications Provide App Dev platform DataData Collect, Store Create data Use App Analyze data Provide Insights Share data Use platform Analytic sAnalytic s MobileMobile S oc ialS oc ial C loudC loud Systems of Insights Making the Art of the Possible a reality Announcement of the Pope
- 5. Leading organizations are seizing the opportunity Deriving insights faster will be a differentiator.
- 6. Relatively new business and technical challenges Still striving to reach potential Few organizations have made a deep commitment Successes are difficult to quantify Opportunities are missed Organizations are less competitive 6 How can we overcome these challenges and unlock the potential of analytics? The (ugly) truth About conventional approaches to analytics
- 7. The Importance of Organizational Readiness How effective are centers of excellence? 97%97% 56%56% 6%6%0%0% n = 5748 organizations 5% 65% 9%21% Manual, slow, error prone, cumbersome, fragmented. Data quality concerns Automated, instant, accurate, seamless, predictive, converged. Data governance is in place IBM Study of AQ respondents, 2012 MasterLeaderBuilderNovice
- 8. 8 Lack of management bandwidth due to competing priorities Lack of skills internally in the line of business Lack of understanding how to use analytics to improve the business Culture does not encourage sharing information Ownership of the data is unclear or governance is ineffective Lack of executive sponsorship Concerns with the data Perceived costs outweigh the projected benefits No case for change Ability to get the data 38% 34% 28% 24% 23% 23% 22% 21% 21% 15% Organizational Data Financial Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. Copyright © Massachusetts Institute of Technology 2010. Primarily Organizational Obstacles Inhibit widespread adoption of analytics
- 9. The first step, is admitting the problems. Prior to 2009 IBM® faced the same challenges that most organizations face—on a very large scale. More than spread across an enterprise comprising and more than Storing and processing big data into was redundant, costly and not very effective. 1,000 TBs of data1,000 TBs of data 400,000 people400,000 people 200 locations200 locations 100+analytics silos100+analytics silos around the world. Challenges at IBM® We faced our own problems on a very large scale Analyze all our data Empower all our employees. Analytics everywhere. We needed the cloud.
- 10. 10 Fulfillment HR Marketing Sales Finance Senior Executives Data admin Report authors Analytics admin Analytics infrastructure and solutions Data warehouse data mart Lacking a cohesive approach for analytics Business units worked in silos
- 11. Be proactive about privacy, security and governance. Build a culture that infuses analytics everywhere. Empower all employees to make data-based decisions. Deploy a unified platform that can handle all types of analytics, regardless of form or function. Remove setup cost and time as a barrier to informed decision making. IBM® Analytics strategy assessment Journey to A Smarter Enterprise We needed a cloud solution. We needed an ACE.
- 12. 1 Acknowledge the need, urgency, willingness for change with an Executive Sponsorship. Measure success and recognize value of improvement to ensure Business Effectiveness. Where to start? Critical to building the foundation Charter Roadmap Think strategically, but act tactically in incremental steps that add immediate value. Develop a strategic plan through organizational readiness. Interlocking Business and IT to Build a guiding team was critical to the success. 2 3 4 5
- 13. 13 Naming variations but common theme: Analytics Center of Excellence (ACE) Analytics Capabilities Enablement (ACE) Analytics Community Enablement (ACE) Business Intelligence CoC (BICC) BI Center of Excellence (BI COE) Performance Management CC (PMCC) Business Analytics CC (BACC) Business Analytics Community of Practice Business S trategy Alignment Communication & Evangelism Community S ervices Enterprise Technical Architecture Advise & Consult S upport IT Governance Alignment Data Governance Alignment Education Business S trategy Alignment Best Practices & Standards Management Communication & Evangelism Community S ervices Enterprise Technical Architecture Advise & Consult S upport IT Governance Alignment Data Governance Alignment Education Keys to Business Analytics Success What is an ACE? A virtual and structured team of people within an organization who work cross-functionally to enable and apply the keys to analytics excellence Is the analytics strategy linked to the business strategy? What analytics resources, skills and process are needed? What analytics capabilities or product solutions are needed? Organizational Structure Operational Framework
- 14. Business S trategy Alignment Communication & Evangelism Community S ervices Enterprise Technical Architecture Advise & Consult S upport IT Governance Alignment Data Governance Alignment Education Business S trategy Alignment Best Practices & Standards Management Communication & Evangelism Community S ervices Enterprise Technical Architecture Advise & Consult S upport IT Governance Alignment Data Governance Alignment Education Phase 1: Focus on bringing quick value Enable a cloud based prototype to build a foundation. Provide a technologyProvide a technology architecture that supports thearchitecture that supports the enterprise that is scalable &enterprise that is scalable & extensibleextensible Gain broader support andGain broader support and interest in the value ofinterest in the value of information.information. Provide a user community withProvide a user community with value-added shared servicesvalue-added shared services of analytics information assetsof analytics information assets
- 15. Sales IT BACC Transform Decentralized Centralized CIO Shared Service C ommon Proc es s es S hared S ervic es BACC Run Adopter BI Teams (TE) Projec t Management Res ourc eAdvis e Business Analytics Competency Center(BACC) People, Process and Technology HR MarketingFullfillment Finance Business S trategy Alignment Best Practices & S tandards Management Communication & Evangelism Community S ervices Enterprise Technical Architecture Advise & Consult S upport IT Governance Alignment Data Governance Alignment Education ACE
- 16. Data admin Report authors Analytics admin Analytics infrastructure and solutions Data warehouse data mart FulfillmentFulfillment MarketingMarketing SalesSales FinanceFinance HRHR ITIT Blue Insight Blue Insight is born
- 17. Provide the userProvide the user community, advise &community, advise & consult guidance withconsult guidance with knowledge transfer forknowledge transfer for greater self-servicegreater self-service ContinuouslyContinuously improving theimproving the skill set of theskill set of the community forcommunity for greater self-greater self- sufficiencysufficiency Provide readilyProvide readily available expertise toavailable expertise to answer questions &answer questions & resolve problemsresolve problems ShareShare experience andexperience and standardizingstandardizing operation foroperation for greater efficiencygreater efficiency and lower riskand lower risk Phase 2: Expand and Scale Enable LOB analytics groups, expand and scale offerings. Business S trategy Alignment Communication & Evangelism Community S ervices Enterprise Technical Architecture Advise & Consult S upport IT Governance Alignment Data Governance Alignment Education Business S trategy Alignment Best Practices & Standards Management Communication & Evangelism Community S ervices Enterprise Technical Architecture Advise & Consult S upport IT Governance Alignment Data Governance Alignment Education 17
- 18. Business Domain Analytics Groups BACC • Cloud Delivery - BI, Predictive - ETL •Boarding services •Standards/Goverance - Architecture - Solutions •Education consulting •Support structure • Cognos BI • Cognos TM1 • SPSS® • Social Analytics Business Domain Knowledge Requirements Solution design Components Solutions Strategy | Value |Strategy | Value | PeoplePeople || ProcessProcess || TechnologyTechnology Solution Delivery process at IBM® Business requirements to analytics insights Transformation Executive (TE) •Project management •Data extract •Data modeling •Intelligent analytics
- 19. Blue Insight High performance, low cost acceleration Structured and unstructured data sources Marquee suite of integrated IBM Analytics capabilities Accessible on the road or in the office PureData 100-100,000x100-100,000x faster and reduced latency by days 10x10xsavings in data preparation 20%20%projected efficiency gain in administration 2 1 3 4 Source: IBM internal project benchmark results Analytics Accelerators Speeding up processing time for all types of data
- 20. Quality Early Warning System - IBM® detects quality problems up to six weeks earlier using cumulative sum technology Preventive Maintenance and Quality 2.0 - Quality Early Warning System (QEWS) is now part of PMQ 2.0 $50 M Cost savings, approximately $10M / year Proactive Quality Management QE WS Improved Brand Value Challenge Improve detection of emerging defects on manufacturing lines Solution Quality Early Warning System provided earlier warning with fewer false alarms20
- 21. Customer Optimization for Profitability boosts sales effectiveness with advanced analytics to align sales resources to true market opportunity Challenge Increase Sales Solution Recommendation Engine $300Mestimated additional revenue during 2013 due to sales force productivity increase 3000% ROI for 2013, based on a yearly ongoing investment Solution components:Solution components: - IBM® SPSS Modeler, Statistics - IBM® Cognos BI - IBM® Netezza C OP =Increase Decrease Maintain
- 22. WW S pend IBM simplifies and standardizes spending analysis processes by leveraging a single multi-dimensional cube on a worldwide basis 18+ Spending Cubes Consolidated 2700+ Users Solution components: - IBM® Cognos TM1 - IBM® SPSS Modeler All previous cubes used Essbase All Spending and Resource data for all IBM units and geographies Challenge Get a holistic view of worldwide spending Solution Create single cube for all of spending to enable management 22
- 23. We reclaimed 7,000 m2 of floor space We deliver over 30,000 megawatts of energy $5 million 99% for business units We conserved We reduced analytics costs by efficiency savings Blue InsightBlue Insight movedmoved enterprise-wideenterprise-wide analyticsanalytics operations ontooperations onto the cloud,the cloud, consolidatingconsolidating 100+ silos to a100+ silos to a single analyticssingle analytics environment.environment. Blue Insight Enterprise-wide analytics operations in the cloud Gaining increased insights, savings and adoption rates Blue Insight changed everything at IBM.Blue Insight changed everything at IBM. And, best of all, we transformed big data into big dollars, adding hundreds of millions in business value.hundreds of millions in business value.
- 24. Determining strategiesDetermining strategies based on businessbased on business priorities for maximum ROIpriorities for maximum ROI and added valueand added value Aligning with data governanceAligning with data governance processes to provide trustedprocesses to provide trusted information for effectiveinformation for effective decision makingdecision making Plan for growth, aligning withPlan for growth, aligning with IT management andIT management and operational processes foroperational processes for greater efficiency & lower riskgreater efficiency & lower risk Phase 3: Alignment on strategic initiatives Collaborate and innovate across the enterprise Business S trategy Alignment Communication & Evangelism Community S ervices Enterprise Technical Architecture Advise & Consult S upport IT Governance Alignment Data Governance Alignment Education Business S trategy Alignment Best Practices & Standards Management Communication & Evangelism Community S ervices Enterprise Technical Architecture Advise & Consult S upport IT Governance Alignment Data Governance Alignment Education
- 25. Benefits of the Blue Insight transformation 25 HundredsHundreds of millionsof millions In added business value annually Business intelligence IBM® Cognos® Business Intelligence IBM Cognos Insight IBM Cognos Mobile Predictive analytics IBM SPSS® Statistics IBM SPSS Modeler IBM SPSS Collaboration & Deployment Services IBM Social Media Analytics Information management and big data IBM InfoSphere® Information Server for Data Integration IBM InfoSphere Information Server for Data Quality IBM InfoSphere BigInsights™ IBM InfoSphere Streams Analytics accelerators IBM DB2 Analytics Accelerator IBM PureData™ for Analytics Blue Insight Offerings today Analytics as a service, fulfill the promise of Smarter
- 26. IBM® Analytics Ecosystem What's Next? Blue Insight DATA ANALYTICS
- 27. • SUPPLY CHAIN analytics first introduced •BACC (ACE) established •BLUE INSIGHT born • Marketing • Social Insights • HR • DATA • CDO Office • FINANCE analytics group established •Appoint CDO •DATA Council •Analytics Council •Watson Analytics IBM® Analytics Transformation Timeline Journey to A Smarter Enterprise 20052005 20092009 20102010 20112011 20122012 20132013 20142014 20152015 • SALES analytics group established • BAT (4 E's) analytics transformation team established • SUPPLY CHAIN analytics group established •Business Analytic Transformation (BAT) •Supply Chain (formal) •HR •Finance •Sales•BACC • DATA data transformation council established • ANALYTICS @IBM council established 66K66KBLUE INSIGHT CONSUMERS 160K160K 450K450K BACC STAFF 1515 4040 6363 200200 800800%% Growth in c ons umers 1 • DATA data transformation group established
- 28. 28 2 3 4 1 Executive sponsorship Services not controlled by solution organization Consolidate analytics investment across the enterprise Extensible architecture Communication and support of analytics strategy Governance of licensing and infrastructure delivery of analytics solutions Cloud approach provides the tenant with central tools, not central solutions (2 tier approach) Needs to be “self-service” model with extended services available (education, services, support) Control points in procurement/infrastructure delivery for new analytics solutions Inventory and review planned investments in analytics enterprise-wide Ability to grow your architecture vertically without change Ability to grow your architecture horizontally to fit non-functional and functional needs as an instance of your service Lessons Learned Journey to A Smarter Enterprise
- 29. 29 Step 1 Affirm Vision Step 2 Assess Strategy Step 3 Grow & optimize adoption Program OptimizationProgram Optimization Measure value and success Alignment and Governance Skills and talent development Implementation methods (PMO) Proven Practices & Standards Communication program Executive SponsorshipExecutive Sponsorship Organization & process assessment Skills assessment (business) Business alignment assessment Stakeholder awarenessStakeholder awareness Understand maturity, challenges, needs Catalysts for change Charter & guiding team "Art of the possible" ACE Proven Practices Technology OptimizationTechnology Optimization Performance tuning Application Design optimization Data design optimization Security optimization Maintenance & Admin optimization Technology ReadinessTechnology Readiness Skills assessment (IT) Performance assessment Application design assessment Security assessment Maintenance & Admin assessment Technology Strategy&Value People&Process Technology ScopeTechnology Scope Current Architecture Application inventory Projects (active & pipeline) Current IT Organization Technical issues Step 1 Inventory the enterprise Step 3 Grow & optimize operation Step 2 Assess technology foundation Goals:Goals: Goals:Goals: ACE Proven Approach Practical steps to improve analytics delivery programs.
- 30. Analyticszone.com ACE Community This community offers various resources (e.g. whitepapers, reports, books, etc) on ACE that can help build a business analytics strategy, demonstrate the value of analytics, organize it's people and process and architect a technology solution that fits the needs of the business. 5 Keys to Business Analytics Program Success This is a great starting point and offers a lot of valuable information. You can download the book for free on Analyticzone. Analytics Across the Enterprise How IBM® Realizes Business Value from Big Data and Analytics Showcases Analytics use cases across IBM. Pick up your free copy here today. Where to find more information
- 31. 3131 “ “ The most competitive organizations are going to make sense of what they are observing fast enough to do something about it while they are still observing it. Jeff Jonas IBM Fellow and Chief Scientist, Entity Analytics Big Data in Motion THINK
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