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Business Analytics Training
IBM offers a business analytics portfolio including Cognos BI, Cognos TM1, and SPSS to provide capabilities across reporting, planning, analysis, and predictive analytics. The suite integrates various data sources and allows different levels of analytics from basic reporting and dashboards to more advanced predictive modeling and optimization. It provides a unified workspace and promotes collaboration.
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Business Analytics Training
- 1. IBM Business Analytics Portfolio Presentedby: Natalija Pavic, Account Manager 647 678 5907, npavic@newcomp.com
- 2. Growing complexity ofbusiness demands for information Why? How are we doing? What should we be doing? … Analysis Reporting Planning INTERNALDATAEXTERNALDATA ERP MAINFRAME EXTERNAL BILLING HR CRM … Dashboarding Scorecarding Budgeting …
- 4. Information Information-driven and accountableculture through Dashboards and Reports Insight Early identification of opportunities and issues through Analysis Action Align resources with decisions through Planning
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- 8. Investing in anAnalytics Platform Risk Management Competence / Skill Level CompetitiveAdvantage Transactional Data Forecasting & Planning Ad Hoc reporting Information Warehouse Standardized Reporting Predictive Modeling Standards: Master Data Dataset Management Common Dimensions Applications: Blue Insight Cognos BI Cognos TM1 SPSS Algorithmics Excel Automation Resulting Capabilities: In Memory Analytics Integrated Planning & Analytics Enterprise Data Scale Real time reporting Advanced analytics Predictive Capabilities Mobile Common Delivery: Finance Analytics Portal
- 10. The Business Analytics“Stack” Degree of Complexity ValueandOperationalExcellence Standard Reporting Ad hoc reporting Query/drill down Alerts Simulation Forecasting Predictive modeling Optimization What exactly is the problem? What will happen next if ? What if these trends continue? What could happen…. ? What actions are needed? How many, how often, where? What happened? Stochastic Optimization Based on: Competing on Analytics, Davenport and Harris, 2007
- 11. COGNOS BI Business Intelligence COGNOSTM1 Table Manager 1 SPSS Statistical Package for the Social SciencesPerformance Management Predictive Analytics Advanced Analytics • Reporting • Data Visualizations • Dashboards • Key Performance Indicators • Scorecarding • For the company wide distribution of Metrics • Can drill down, Ad-Hoc Queries • Maximally customizable • Enterprise-wide and Scalable • Planning, forecasting • “Excel-hell” • Write back • Security, Validation, Webportal • Budgeting, Capital Planning, Cost Analysis • Finance Department • Perfect compatibility with excel, can go back and forth • Can load data from anywhere into a TM1 “cube” • Predicting • Finding correlations, trends and patterns in data sets • Widely used by statisticians and academics • Statistical analysis • Build models, use machine learning • WATSON • Big Data
- 12. BI TM1 SPSS •Maximally customizable • Compatible with all data • Report creation abilities not existent with competitors • Visualizations are not the best when comparing to Tableau or QlickTek • Resiliant to scalability, enterprise ready • Deep integration with other IBM products for the whole stack • Maximally customizable • Compatible with all data • The only software to have a smooth transition from and to excel • Looks like excel so friendly for excel users • Manipulate multiple datasets easily – true sandbox • Can be used by different departments for different purposes • Powerful consolidation of data • User-friendly • Easy to use • Makes powerful statistical tools accessible to a more commercial user • Does not compete with Oracle • SAP cannot compete with it yet • Can be used as a single user licence by one user on a desktop Competitive Comparisons
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- 14. It is thisapproach to link data with analytics capabilities to manage outcomes How are we doing? Why is this occurring? What should we be doing? Dashboards & scorecards Social Analytics Reporting & visualization Sentiment Analysis Real-time Decisions Predictive modeling Forecasting & simulation Planning/ budgeting Analytics capabilities Message sources Relational sources Application sources OLAP sources Modern and legacy sources Unstructured data Varied, unconnected data sources The Data Layer The Analytics Layer
- 15. 18 How are wedoing? Immediate Insights to Business Performance • Scorecards • Dashboards • Reports • Real-Time Monitoring
- 16. 19 Why? Deeper Analysis ofTrends & Patterns • Ad-hoc Query • Analysis and Exploration • Trend and Statistical Analysis
- 17. 20 What should webe doing? Foresight to Plan & Allocate Resources • What-If Analysis • Predictive Analysis
- 18. IBM COGNOS BI BusinessIntelligence
- 19. 22 A Unified Workspaceinstantly usable by everyone Built-In Collaboration Progressive Interaction How the full breadth of BI capabilities come together All Time Horizons Unified Workspace Complete perspective on the business Simple to use with unprecedented power one click away Place historical information alongside real- time updates, plans, and predictive results Follow the natural path from viewing, to light exploration, to deeper analysis Engage the right people at the right time to exchange ideas and knowledge Accelerate alignment and improve decision-making
- 20. Definition Dashboards • Contains necessaryinformation to quickly determine the state of affairs for users Characteristics • Should have a simple layout showing summary • May contain scorecard style data, but will often contain other types of data • Will often link to more detailed reports Best Practices • Keep the dashboard simple and easy to comprehend • Information at a glance • No prompt pages • Use drill-through reports to provide more details • Use charts and color palettes to highlight important information
- 21. Definition Interactive Reports • Usedto support daily decision making Characteristics • Fast to load • Information at a glance • Easily move from one report to another using drill-through links Best Practices • Show only the information needed • Be conscious of the limited display area • Avoid `next page` • Avoid horizontal scrolling • Minimize vertical scrolling • Use prompting to limit data or to change layout
- 22. Definition Active Reports • Usedfor High level summarized data • Interactive graphic rich format • Offline (runs disconnected from Cognos server) Characteristics • Meant for `Presentation` type of data • Package in one file Best Practices • Complete requirements are essential • Design for a specific interface (iPad, Android devices..) • Graphic Design mentality required • Story boards, PowerPoint mock ups • Pay attention to file sizes
- 23. Drag-and-drop data, smart filters,and intuitive analysis Modify plans, budgets, and forecasts accordingly Exchange files or publish and extend within the Cognos Family Add compelling visuals, widgets and themes Insight to Action Model scenarios, test assumptions, and optimize Model scenarios, test assumptions, and optimize
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- 26. Cognos Insight When touse? Who? Personal Desktop Analytics Prototyping Ad-Hoc Analysis Workflow Application Design What-if Analysis “Throw-away” Analysis Data Analysts Workflow Contributors Type of Client Skills Required Thick Client Can be launched from the Web Minimal Training Required (1-2 days) Knowledge of Data
- 27. Cognos BI –Report Studio
- 28. Cognos BI –Report Studio When to use? Who? Pixel-Perfect Reports Emailed Reports Scheduled Reports Report Authors Type of Client Skills Required Web-Based / Thin Client Report Studio
- 29. Cognos BI –Active Reports
- 30. Cognos BI -Mobile
- 31. Cognos BI –Active Reports & Mobile When to use? Who? Mobile Device Online or Offline End Users Type of Client Skills Required Web-Based (Mobile Browser) Native iPad or Android App None
- 32. Cognos BI –Cognos Workspace
- 33. Cognos BI –Cognos Workspace When to use? Who? Self-Service Assembly of Existing BI Content Dashboards End Users Type of Client Skills Required Web-Based / Thin Client Cognos Workspace (1/2 day training)
- 34. Cognos BI –Cognos Workspace Advanced
- 35. Cognos BI –Cognos Workspace Advanced When to use? Who? Ad-Hoc Analysis Self-Service Reporting Add in External Data Files Advanced Ad-hoc Users Analysts Type of Client Skills Required Web-Based / Thin Client Cognos Workspace Advanced (1-2 day training) Basic Ad-hoc Reporting
- 36. IBM COGNOS TM1 TableManager 1 Performance Management
- 37. © 2012 IBMCorporation Common Information & Technology Platform IBM BA Performance Management Profitability Modeling & Optimization Management & Performance Reporting Scorecarding & Strategy Management Financial Close Management Sales Performance Management Integration and AutomationHierarchy ManagementAnalytic Data Management Planning Analysis & Forecasting Align resources with corporate objectives and market events through improved visibility and control over the levers of performance
- 38. Finance IT Human Resources SalesMarketing Customer ServiceOperations Product Development Performance Management Finance Operations Sales / Customer Account Analysis & Close Financial Consol Reporting & Analysis Disclosure Mgmt & XBRL Sales and Ops Planning Capital Expend. Planning Product Profitability Incentive Comp Mgmt Quota Planning Territory & Channel Mgmt Planning Analysis & Forecasting Profitability Modeling & Optimization Performance Reporting & Scorecarding Governance, Risk, and Compliance Industry Specific Blueprints Industry Specific Blueprints 41 IBM BA Performance Management Solutions
- 39. © 2012 IBMCorporation Key Contacts For Performance Management WHO MAIN CONCERNS CFO Accountability & Timeliness Integration across all LoBs Insightful Info to drive business VP Planning Accuracy, Forecast/Actual deltas Frequency of collection Amount of detail, value of info Controller Accuracy Adequate Controls Flexibility to react Accounting/Finance Manager Time spent collating No time to check, value add activity Evenings and weekend work CIO / IT Audit, Controls, IT Standards Finance system integration Reporting & Data management VP Sales Territory Planning challenges Complex Compensation plans Integration w/ Finance
- 40. IBM BA PerformanceManagement – Better Outcomes Drive efficiencies and scale • Eliminate intensely manual efforts • Structure and automate dynamic processes • Scale to large user communities and data sets Gain agility and preparedness • Link operational and financial performance management • Support advanced analytic techniques (e.g., scenario • and predictive analytics, narrative performance reporting) • Eliminate delays in coordinating around emerging realities Improve effectiveness and outcomes • Dramatically reduce risk of errors • Cost-effectively address compliance • Drive new confidence in analytics-driven decision making Confidence Control Time
- 41. What is TM1? Created in 1984 64-bit In-Memory OLAP Database Designed for Writeback Supports Real-Time Calculations Secure and Centralized Integrated with Excel, Cognos BI
- 42. IBM Cognos TM1Solutions Compensation Management Sales Performance Management Staffing Optimization Training Certification Intranet Employee Portal Retail Sales Analysis New Product Planning Customer Profitability Customer Churn Analysis Financial Consolidations Financial Reporting Planning Driver Based Budgeting Rolling Forecasts Risk Analysis Demand Analysis Inventory Optimization Logistics Planning Product Profitability Production Planning Financial Operations Workforce Customer Complete Performance Management Applications • Read/Write Planning & What-If • Ad Hoc Analysis and Formatted Reporting
- 43. TM1 Terminology Dimension– A collection of Elements and their relationships to one another (e.g. Chart of Accounts). Cube – A collection of dimensions whose intersections (cells) store data (e.g. Sales). Element – A single member within a dimension (e.g. one account from the Chart of Accounts). Attribute – A piece of information that describes an element (e.g. an inactive flag on an account). Subset – A Subset of Elements within a Dimension (e.g. all revenue accounts) Rule – A formula that describes business logic Process – An ETL script that can import, export, and transform data.
- 44. TM1 Interfaces TM1Applications / Workflow Cognos Insight TM1 Perspectives (Excel Add-In) TM1 Web TM1 Architect Performance Modeler Cognos BI
- 45. TM1 Applications /Workflow
- 46. TM1 Applications /Workflow When to use? Who? Data input Approvals and Rejections Email Notification Status Reporting End Users in a Workflow Process Type of Client Skills Required Web-based / Thin Client for End Users Performance Modeler for Admin None
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- 48. TM1 Web When touse? Who? Data Input Ad-Hoc Analysis Reporting End Users Power Users Type of Client Skills Required Web-Based / Thin Client None
- 49. TM1 Perspectives (ExcelAdd-In)
- 50. TM1 Perspectives (ExcelAdd-In) When to use? Who? Template and Report Creation Data Input Reporting Template Authors End Users Power Users Type of Client Skills Required Excel Add-In Requires Client Installation Excel
- 51. CAFÉ (Excel Add-In) CognosAnalysis for Excel
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- 53. CAFÉ (Excel Add-In) Whento use? Who? Ad-Hoc Analysis Slice and Dice Data Entry End Users Power Users Type of Client Skills Required Excel Add-In Requires Client Installation Excel
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- 55. TM1 Architect When touse? Who? Modeling Importing and Exporting Data Managing Security Modelers Administrators Type of Client Skills Required Thick Client - Windows Requires Client Installation TM1 Modeling
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- 57. Performance Modeler When touse? Who? Modeling Importing and Exporting Data Managing Security Workflow Application Design Modelers Administrators Type of Client Skills Required Thick Client Can be launched from the Web TM1 Modeling
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- 59. What does SPSSstand for? Statistical. Package. for the Social. Sciences.
- 60. What does SPSSstand for? Statistical. Package. for the Social. Sciences. It should be SPFC: Solving. Problems. For. Customers.
- 61. Purpose • Introduce focuson Customer Experience • Spin the SPSS story from the Customer Experience perspective • Organize SPSS solutions into the customer experience theme • Define Predictive Analytics (PA) market
- 62. Studies have shownthat the objects people chose to surround themselves with are indicative of their personalities. Gosling, Sam. Snoop: What Your Stuff Says About You. New York: Basic, 2008. Print.
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- 65. Questions to answer: •How can we use data to alter the customer experience? • How does data impact brand perception? • How do customer interact with data? • How is data integrated in the shopping experience?
- 66. OF CUSTOMERS’ EVERYDAY POTENTIAL INTERACTIONWITH AN ORGANIZATION’S DATA EXAMPLE
- 67. Meet Henry Hipster •Received phone calls at 8pm • Bank selling him accounts he has • Service provider can’t remember him • Customer service reps annoy him • Receives Junk Mail • Mailbox filled with SPAM NOW • No-logo philosophy • Obscure bands • Whole-foods • Hipster
- 68. Meet Serene Serena •Trip to Bahamas • Coupons on the way • Exclusive product launches • No problems with service provider • Pizza remembers favorite order • Issues resolved in advance • Receives messages she wants NOW • Blogger • Superstar • Fan base • Lucky
- 69. Meet Serene Serena •Trip to Bahamas • Coupons on the way • Exclusive product launches • No problems with service provider • Pizza remembers favorite order • Issues resolved in advance • Receives messages she wants NOW • Blogger • Superstar • Fan base • Lucky
- 71. By effectively analyzingand utilizing:
- 72. Sell the SPSSsolution as a data-centric way to improve the customer experience.
- 73. What is theData-Driven Customer Experience? Using data, data mining methods, and predictive analytics to: • Create the best buying environment for your customers. • Facilitate communication with your customers that is effective and consistent. • Anticipate and predict customer needs.
- 74. Using data toimprove the customer experience by focusing on… Buying Environment Communication Customer Needs
- 75. Categorizing and grouping SPSSsolutions thematically so they are relevant to Enterprises.
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- 77. Buying Environment Digital Optimization Creating abetter user interface that improves the sales funnel. Preventing Fraud/Theft Creating a safe environment for customers that encourages spending. Targeted Advertising Creating personalized message and content to increase impact. Market Basket Analysis Grouping relevant items to facilitate increasing the single purchase price. .
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- 79. Communication Customer Segmentation Understanding customermicro- niches to better align products with customer interests Targeted Marketing Sending customers they want to see in their preferred deliver methods to increase engagement. Text Analytics Understanding customer sentiment in free form text to create an informed communication strategy. Churn Analytics Identify customers at risk of leaving to resolve customer issues faster. .
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- 81. Customer Needs Recommendation Engine Making targetedrecommendations to facilitate customers finding what they are looking for. Promotional Analytics Identifying ROI for promotions in order to continue offering customer discounts. Store Planning Identifying new markets in order to provide services to new potential customers. Merchandising Analytics Anticipating demand in order to stock inventory levels appropriately. .
- 82. Buying Environment Communication Customer Needs Digital Optimization Preventing Fraud/Theft Targeted Advertising MarketBasket Analysis Customer Segmentation Targeted Marketing Text Analytics Churn Analytics Recommendation Engine Promotional Analytics Store Planning Merchandising Analytics Summary Reference Tables of SPSS Solutions Categories
- 83. Big Data AnalyticsMarket Size by Business Category
- 84. Big Data AnalyticsMarket Size by Business Category
- 85. Most Opportunity forAnalysis
- 86. Most Opportunity forAnalysis
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- 88. Predictive Analytics Market– Global Industry Analysis from Transparency Market Research • PA predicted to grow from $2.08B today to $6.54B in 2019 globally • Banking, FinServ, Insurance sectors largest market share • Retail and manufacturing expected to grow faster than any other segment • Fast growing consumer driven digital data • Need to extract strategically critical information • Rise in fraud, payment defaults, over or under stock inventory levels, stringent regulations
- 89. Predictive Analytics Market– Global Industry Analysis from Transparency Market Research • Companies to adopt predictive models to gain futuristic insights • Leading segments: customer intelligence, fraud and security, campaign management – accounted for 50% market revenue 2012 • Target Departments: sales and marketing, customer and channel management, operations and workforce management, finance and risk management. • Finance and Risk 40.9% of revenue share in 2012.
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