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RBS - From information to Intelligence

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Right Brain Systems presentation on Agile Analytics and delivering business outcomes

Right Brain Systems presentation on Agile Analytics and delivering business outcomes

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  • 1. RBS on AnalyticsBuilding Smarter Organizationswith AnalyticsSrini KoushikPresident and CEORight Brain Systems LLC.Twitter Handle - @skoushik Right Brain Systems LLC. innovation – agility - execution © Right Brain Systems LLC.
  • 2. Digitization and Connectivity drives Big Data 13 hours of content is uploaded on YouTube Storage Capacity is growing every minute Lower barriers to connectivity at an annual growth rate of drives integration of islands 23% of data Computing Capacity is growing at an annual growth Big 30 billion pieces of content shared on Facebook every rate of 54% Data month 60% of the world’s Over 30 million network population used cell phones sensor nodes in 2010 growing in 2010 at 30% a yearSource – Big Data – The next frontier for innovation, 12% of cell phones are smartcompetition and productivityMcKinsey Global Institute, May 2011 phones and this number is growing at 20% a year © Right Brain Systems LLC.
  • 3. Current trends help drive more data Consumerization Universal Access Internet of Things Cloud Computing Social Business Big Data The pace of change is accelerating and converging © Right Brain Systems LLC. 3
  • 4. Can humans keep up?Human ability to deal with complexity “Avoidable failures are common and persistent, not tohas not changed mention demoralizing and frustrating across many fields – from medicine to finance, business to government. And the reason is increasingly evident: the volume andMachine learning while useful has its complexity of what we know has exceeded our individual ability to deliver its benefits correctly, safely, or reliably. “disadvantages. Example, automated Dr. Atul Gawande, The Checklist Manifestohedge fund tradesSuccess requires the effective “What information consumes is rather obvious: itblending of human intuition and consumes the attention of its recipients. Hence a wealth of information creates a poverty ofdecision making with business attention, and a need to allocate that attention efficiently among the overabundance ofintelligence and machine learning information sources that might consume it.” - Herbert Simon © Right Brain Systems LLC.
  • 5. What is Analytics? Analytics is the discovery and communication of meaningful patterns in data. These patterns lead to business insights which can be translated into specific actions to drive meaningful business outcomes.2/6/2013 © Right Brain Systems LLC. 5
  • 6. How did we get to Analytics? Digitization & Storage Cloud and Connectivity Computing Capability Pervasive Access + + + Availability of different Easy and inexpensive Ability to quickly Visualize and act anytime, types of data access to any data organize and process a anywhere using mobile lot of data devices• Structured data • Enterprise Data • Linear programming • Provide insights and• Semi-structured data • Federated Data • Regression analysis actions in real-time• Unstructured data • Public/Syndicated Data • Markov chain Monte • Deliver them to the where Carlo methods they can be used • Simulations • Access them from any deviceBusiness Intelligence can answer questions such as: what happened; how many, how often, where did it happen; whereexactly is the problem; what actions are needed.Business analytics answers the questions: why is this happening; what if these trends continue; what will happen next(predict) and what is the best that can happen (optimize).2/6/2013 © Right Brain Systems LLC. 6
  • 7. Today’s market leaders have “cracked the code” Uses advanced analytics to identify and propose the “Next Best Offer” based on Customer browsing and buying patterns Pioneered the use of customer segmentation and profitability analysis to target and acquire most profitable customers Uses web analytics and customer loyalty program data to target and drive business through its most profitable customers Uses Cinematch,an advanced analytics engine to make movie recommendations based on rental patternsSource – Competing on Analytics – The new science ofWinning. – Thomas H. Davenport and Jeanne G. HarrisHarvard Business School Press, 2007 © Right Brain Systems LLC. 7
  • 8. The RBS Approach to Agile Analytics 2/6/2013 © Right Brain Systems LLC. 8
  • 9. RBS on Analytics Our approach to Analytics is focused on building the organizational capability that can sense changes, understand them, respond to them through business actions and refine these actions continuously to deliver better business results We want to build Smarter Organizations that deliver meaningful business results through secure, seamless context-aware experiences in a data driven world2/6/2013 © Right Brain Systems LLC. 9
  • 10. Building a Smarter Organization INSIGHTS: ACTIONS: INFORMATION: What do we do? BETTER Why did it happen? DATA What happened? BUSINESS What data? OUTCOMES • Ability to sense and understand changes ANALYTICS DRIVEN in marketplace BUSINESS BUSINESS ORGANIZATION • Rapid decisions ANALYTICSDATA & INFORMATION INTELLIGENCE • Predict / optimize driven byMANAGEMENT • Correlation across • Aggregation of internal and external business decisions Information• Understanding the data Information – primarily • Translate insights into data sources • Enable ecosystem – Structured, from Structured data actions through Semi-structured and • Identify patterns and differentiated and within the enterprise operations Unstructured data causal relationships in seamless context • Historical view aimed historical and real-time • Experiment, aware experiences• Creating and maintaining at enabling business data implement, measure data as an asset planning and improving and improve business performance © Right Brain Systems LLC. 10
  • 11. Building an Analytics Driven OrganizationBuilding an analytics driven organization takes more than good technologyThe RBS approach for building an analytics driven Dataorganization focuses on five key domains: Foundation 5 • A data foundation that provides an enterprise view of data, its types, 4 sources, latency and how it is understood and used (metadata) in the 3 organization Information Active Business 2 Design and • An Information Design that describes how users will visualize, access, Sponsorship 1 Visualization 0 utilize and act on the insights generated • Analytics Capabilities which includes the foundational practices, skills and approaches for driving agility into the organization Analytics Analytics • An Analytics Operational Framework that helps establish where and how Operational Capabilities analytics can be used within the enterprise and Framework • Active Business Ownership from Operational leaders within the company who understand and use the insights generated to make informed decisions © Right Brain Systems LLC.
  • 12. Building the Data Foundation Real-time and Batch Queries (OLTP and Real-time queries The Data Foundation defines: OLAP) Data Warehouse, Data marts and Real-time In-memory Databases 1. How data is organized and Operational Data Stores used in the Enterprise Enterprise Data Governance Customer Financial Functional Operational (Semantics) (HR, IT, Marketing, (Product, Sales, Service, Enterprise Risk Fraud Detection, Operations 2. How data is persistently Management etc.) etc.) Metadata, Data Modeling, Master Data Management stored and accessed Enterprise Extract Unstructured Data Loads Real-time Integration (Structure) and Application Transform (pattern matching, stop Integration (EAI) & Load word filtering, backward 3. How data is managed and (ETL) pointers etc.) understood (access, inquiry, Structured Data Operational data from internal Unstructured Data Digital data (audio, video), Semi-Structured and Real- time Data replicated, updated etc.) and external data sources text data (from social networks) etc. Data from real-time sensors, high volume transactions etc. Source: Enterprise Data (Internal), Federated Data (External), Syndicated Data (External) Volumes: Streams, High Volume, Low Volume Latency: What is the latency of the data – real-time, near real-time or batched © Right Brain Systems LLC.
  • 13. Information Design Visualization User Specific Context and Information Information Interaction • What role do they play – • What is the context of the • How do we represent the consume content or create interaction? information being consumed? content? • Where is the interaction • How does the system accept • What are their happening? inputs from the user? preferences? • What is the nature of the • What does the interaction look • What are the capabilities interaction? – support, like if there is no human of the device they are transactional etc. involved? using? • What are the constraints? – • What are the requirements for Device capabilities, Location data access? – Fire and Forget, awareness, Network Request/Response, Complex capabilities etc. Event Processing etc. © Right Brain Systems LLC. 13
  • 14. Analytics Capabilities - Governance Understand Data Domains Information Classification Model Governance Model Customer Confidential Personal Information – Name, Address, • One Enterprise Governance SSN, Credit Car # etc. Board for all confidential Financial Performance Data etc. data, compliance and Finance Privileged regulations Non-identifiable individual data Historical data Customer interaction data Product/Pricing Public • Information and IT security Syndicated data policies are driven by the Public data Enterprise Governance Board Operational Historical data • Business ownership and stewardship for data Operational domains and Metadata Information Privacy, Security, Regulatory and Compliance Rules and Guidelines Enterprise Risk Management2/6/2013 © Right Brain Systems LLC. 14
  • 15. Analytics Capabilities – Core Competencies The ability to integrate with, ingest, understand all types of Data data from internal and external Integration sources Implementing metrics, Co-relate outcomes to Embedding decision making Analytics Analytic facts and events and build structures and a closed into Modeling models based on patterns feedback loop to take Operations discovered in these advantage of insights relationships Visualization and User Experience Rapid Prototyping, Agile design to present insights in Visualization Delivery incremental delivery, a meaningful way that built-in retrospectives and results in the desired action continuous improvement © Right Brain Systems LLC. 15
  • 16. Analytics Capabilities - Agile Analytics Rendering and Visualization Data Ecosystem and relationships Information design Analytics Patterns Access and Integration Use and Implementation Analytics Solutions Analytics Epics Analytics Story Maps Agile Delivery Analytics Personas User Stories © Right Brain Systems LLC.
  • 17. Analytics Capabilities - Reference Architecture Visualization and User Interaction Interaction Model – Fire-and-forger, Request-Response, Complex Event Processing (CEP) Analytics Solutions – Social Analytics, Value Chain Performance Analytics, Customer Interaction Analytics etc. Advanced Statistical Quantitative Analysis Linear Programming Markov Chain, Regression Models Simulation Modeling Monte Carlo Methods Real-time and Batch Queries (OLTP and OLAP) Real-time queries Data Warehouse, Data marts and Operational Data Stores Real-time In-memory Databases Enterprise Data Governance Customer Financial Functional Operational (HR, IT, Marketing, Enterprise Risk (Product, Sales, Service, Fraud Detection, Management etc.) Operations etc.) Master Data Management, Distributed Map Reduce Enterprise Application Extract Transform & Unstructured Data Loads Real-time Integration Integration (EAI) Load (ETL) (pattern matching, stop word filtering, backward pointers etc.) Structured Data Unstructured Data Semi-Structured and Real-time Data Operational data from internal and external data Digital data (audio, video), text data (from Data from real-time sensors, high volume sources social networks) etc. transactions etc. © Right Brain Systems LLC.
  • 18. Analytics Capabilities - Workforce Model • 20% Specialized skills • Data Scientists – Mix of statistical and quantitative skills (Left Brain) and pattern detection/matching skills (Right Brain) Sustainable • Product Owners – Ability to breakdown complex problems into product features and Workforce backlog that can be delivered incrementally • Visualization and UX Designers – Creative and Design Thinking skills (Right Brain) • 80% Delivery skills – Architects, Developers, Software Quality analysts etc. • Mix of soft skills and technical skills, delivered a 10-20-70 learning model Immersive • Formal and informal mentor-apprentice model Learning • Campus relationships with arts and science schools • Industry-Academia interactions to drive new perspectives and to facilitate updates on new techniques • Job rotations to drive cross-skilling and enforce knowledge management requirements Experience • Retrospectives at all levels of delivery and operations to drive experiential learning Management • Formal and informal knowledge sharing sessions to drive collective learning • Client-specific relevance maintained through single-point of contact for business-specific details • Use of Social networking tools to establish informal knowledge and experience networks © Right Brain Systems LLC.
  • 19. Analytics Capabilities - Hybrid Delivery On Site Shared Analytics Center Business Stewardship and Agile Analytics will Governance require a hybrid delivery Product Owners Data Scientists model that takes into Visualization and UX Designers account the data and privacy concerns and Operations Monitoring and Reporting balancing with the need Analytics Solutions for agility and the scarcity of key skills Private Data Privileged Public Data © Right Brain Systems LLC.
  • 20. Analytics Operational FrameworkManaging a smarter business with Analytics • We help businesses integrate analytics with Financial Analytics Operational Analytics the key metrics that are tracked on an organization’s Balanced Scorecard1 • This framework: • Defines and measures key business performance metrics across all four quadrants of the balanced scorecard • Synthesizes findings and delivers insights to business leaders • Performs analysis on metrics including variation and Customer Workforce root cause analysis Analytics Analytics • Implements a closed loop feedback mechanism that helps understand results and refine the insights and actions through agile delivery1 Kaplan, R. S. and D. P. Norton. 1992. The balanced scorecard - Measures that drive performance. Harvard Business Review (January-February): 71-79. © Right Brain Systems LLC.
  • 21. Examples of Analytics in a Smarter Business Customer Analytics Operational Analytics Financial Analytics Workforce Analytics Marketing Sales Supply ChainCUSTOMER CUSTOMER SALES FORCE DEMAND-SUPPLY FINANCIAL WORKFORCEANALYTICS INTELLIGENCE ALLOCATION PLANNING REPORTING & OPTIMIZATIONHelp determine Next Best Improve customer share of Drive sales coverage across Reduce demand-supply ANALYTICS Allocation / matching ofAction or Next Best Offer wallet through target addressable segments mismatch through better (Budget and forecasting, P&L workforce for efficient usage marketing forecasting / Balance Sheet review)CUSTOMER SALES ATTRITIONINTERACTION MARKET EFFECTIVENESS INVENTORY MODELINGANALYTICS INTELLIGENCE OPTIMIZATION Enable effectiveness of sales COMPLIANCE & RISK Identify attrition propensityImprove Customer Provide insights into market pursuit and conversion Reduce own and channel based on characteristics & Continuous monitoring,Experience and reduce cost trends and customer inventory costs drivers SALES better audit sampling to testof service behavior COMPENSATION PROCUREMENT controls and enable revenueSOCIAL ANALYTICS MARKETING ANALYTICS hedging Design and track sales EFFECTIVENESSDrive brand loyalty and compensation for Drive savings from spendservice recovery actions Drive returns from better optimization forecasting and CUSTOMERbased on sentiment analysis marketing spend allocation consolidation PRODUCT SALES PROFITABILITYon social media PRICING ANALYTICS PERFORMANCE Continuous monitoring and Provide price / discount Monitor sales performance optimizing of customer and insights for specific sales by product / solution product profitability © Right Brain Systems LLC.
  • 22. An ExampleDetermining the “Next Best Action” for a customerDescriptive Data (S, E) Business Intelligence • Attributes What do our customers say • Characteristics they want? • Self-declared info Historical Analysis Device data (U, P) • (Geo)demographics Correlation of data What are the major life events • LocationInteraction data (SS, E) Pattern recognition for the customer? • Camera • E-Mail / chat transcripts • Microphone • Call center notes How do customers interact • Multi-touch • Web Click-streams with the organization? • Sensors • In person dialoguesAttitudinal data (U, E, P) Business Analytics • Business Analytics Opinions What is the customer’s Propensity to • Preferences Next Best Action buy? • Needs & Desires UX • Sentiment MCMC Methods Visualization Next Best Offer What are the indicators of customer Regression Analysis retention/attrition? CEPBehavioral data (S, F,E) Customer • Transactions Pattern Matching Scoring Management Action • Payment history What is the Customer Profitability? • Service history • Credit history Service Recovery What is the Product Profitability? S –Structured U – Unstructured SS – Semi Structured F – Federated P – Public E - Enterprise © Right Brain Systems LLC. 22
  • 23. Conclusion• Analytics enable business agility• Building an analytics driven organization requires a comprehensive set of capabilities• Its a huge waste without business and operational buy-in• RBS has the IP and experience to help you get there 2/6/2013 © Right Brain Systems LLC. 23
  • 24. Srini KoushikLinkedin – http://www.linkedin.com/in/srinikoushikTwitter - @skoushikSlideshare – http://www.slideshare.net/rightbrainsystemsBlog – http://rightbrainsystems.tumblr.com © Right Brain Systems LLC. 24