IBM Predictive Analytics Solutions Koenraad De Cock Wannes Rosius 2014 IBM Corporation 2014 IBM Corporation 1
Agenda Overzicht van de IBM oplossingen De Academische- vs de Business-wereld, een reflectie Statistische toepassingen binnen de bedrijfswereld Demo Data Mining met IBM SPSS Modeler 2014 IBM Corporation 2
Overzicht van de IBM Oplossingen op het vlak van statistische analyse en Data Mining
Predictive Business Intelligence Predictive Business Intelligence IBM SPSS Predictive Analytics Optimized decisions made possible by pervasive, predictive, real-time decisions at the point of impact Predictive Customer Analytics Predictive Operational Analytics Acquire Grow Retain Data Collection Predictive Threat & Fraud Analytics Manage Maintain Maximize Social Media Analytics Statistics Monitor Detect Control Modeler Decision Management Collaboration and Deployment Services 4 2014 IBM Corporation 4 2014 IBM Corporation
De Academische vs Business wereld, enkele reflecties
Op sommige punten zijn er significante verschillen Doelstelling: Academisch : Perfectie zo dicht mogelijk benaderen Business: Verbetering Tijdsdruk: Academisch: Aanwezig, maar minder cruciaal Business: Tijd = Geld! Collega s en management Academisch: Statistisch geschoold Business: Vertalen van modellen naar business drivers en objectieven/roi 2014 IBM Corporation 6
Enkele voorbeelden van geïntegreerde analytische oplossingen
IBM Predictive Customer Intelligence Offering powerful customer experiences to help make the right offer 2014 IBM Corporation 2014 IBM Corporation 8
Move from react to engage with a nearly 360-degree view of customers Enhance customer loyalty Increase lifetime value Identify social influencers Monitor brand loyalty Make best offer recommendations Drive smarter service delivery Report, measure and share customer service efforts Automate and enhance delivery of service Increase customer retention Predict churn Capture customer feedback Analyze sentiment 2014 IBM Corporation 9
IBM Predictive Customer Intelligence enables clients to extract a wealth of insights and predictions hidden in customer data HOW? Interaction data Email and chat transcripts Call center notes Web clickstreams In-person dialogues Attitudinal data Opinions Preferences Needs and desires WHY? WHO? Descriptive data Attributes Characteristics Self-declared information Geographic demographics Behavioral data Orders Transactions Payment history Usage history WHAT? 2014 IBM Corporation 10
Predictive Customer Intelligence provides deep analytical insight to meet customers with a pitch tailored to them Five points of customer lifecycle management (Use cases) Loyalty and profitability Target cross-selling and up-selling of customers, based on loyalty and profitability, to grow customer relationships Churn and lifetime value Respond to customer needs and sentiment in the engagement. Is the customer using the product or service? Service Marketing and selling Customer acquisition Identify and segment customers, target them for profitable marketing and acquisition efforts (wisdom of the crowd) Market-basket analysis Tailored offers are targeted to a customer s basket of existing or new goods and services at the point of purchase for up-sell and cross-sell Social analytics Offer optimization Develop offers, tailored to business objectives and targeted to customer profile Real-time text analytics 2014 IBM Corporation 11
Predictive Analytics Customer Enterprise Intelligence Solutions Predictive Analytics Enterprise Solutions Solving business challenges with predictive analytics 2014 IBM Corporation 2014 IBM Corporation 12
Analytics-driven organizations are distinguished by their ability to leverage a variety of resources All information Transaction data Application data Machine data Social data Enterprise content All perspectives Past (historical, aggregated) Present (real time) Future (predictive) All people All departments Experts and nonexperts Executives and employees Partners and customers All decisions Major and minor Strategic and tactical Routine and exceptions Manual and automated 2014 IBM Corporation 13
Predictive analytics enterprise solutions span a variety of core business objectives Evidence-based medicine Improving patient care and satisfaction Reducing costs through optimized allocation of resources Measuring and improving patient outcomes Human capital management Acquiring, growing and retaining employees Helping ensure optimal staff levels Increasing performance, efficiency and engagement Crime prediction and prevention Identifying predictors of threat and fraud Optimizing force deployment Anticipating and visualizing crime hot spots Supply chain management Increasing visibility into virtually all areas of the supply chain Decreasing downtime and unpredictability Improving customer satisfaction Process optimization Improving accurate responses at the point of impact Decreasing costs through operational efficiency Transforming threat and fraud identification processes 2014 IBM Corporation 14
Predictive and Business Business Intelligence Predictive Maintenance and Quality IBM Predictive Maintenance and Quality Reducing costs and improving operational performance 2014 IBM Corporation 2014 IBM Corporation 15
The IBM solution: IBM Predictive Maintenance and Quality Improve asset productivity Reduce Operational costs Increase process efficiency Accelerate time to value Real-time capabilities Big data, predictive and advanced analytics Quicker and more-accurate decision making IBM Maximo integration Open architecture Business intelligence 2014 IBM Corporation 16
Predictive Maintenance and Quality analyzes data from multiple sources and provides recommended actions, enabling informed decisions Generate predictive and statistical models #1 Collect and integrate data Structured and unstructured, streaming and at rest #2 #3 Predictive Maintenance and Quality Data agnostic User-friendly model creation Interactive dashboards Enables faster decisions Attain analytical insights #4 Display alerts and recommend actions #5 Act upon insights Asset performance Process integration 2014 IBM Corporation 17
With a proven architecture End user reports, dashboards, drill downs Predictive analytics Decision management Analytic data store Business intelligence (Prebuilt data schema for storing quality, select machine and production data, and configuration) Integration bus (Prebuilt data schema for storing quality, select machine and production data, and configuration) Advanced analytics powered by IBM SPSS and Cognos software Data integration provided by IBM WebSphere Message Broker and IBM InfoSphere Master Data Management Collaborative Edition software, which feeds a prebuilt, data schema based on IBM DB2 software Process integration with automatic work-order generation from Maximo software Telematics, manufacturing execution systems, existing databases, distributed control systems High-volume streaming data Enterprise asset management systems Data models, message flows, reports, dashboards, business rules, adapters and key performance indicators 2014 IBM Corporation 18
Predictive and Business Business Intelligence Predictive Maintenance and Quality Forward-Looking Business Intelligence Know the past, understand the present, shape your future 2014 IBM Corporation 2014 IBM Corporation 19
Predictive analytics enhances the value of deploying BI reports, dashboards and scorecard capabilities across the enterprise with visibility into your businesses past, present and future Provide insights: Use a trusted platform for delivering forward looking business information Leverage data: Analyze information in any volume, combination and complexity Make confident decisions: Complete visibility into your business with predictive analytics Outperform expectations: Transform your business from a reactive operation to a proactive market leader With business intelligence and predictive analytics from IBM, transform data into useful insights. Help make confident decisions and improve operational efficiencies with historic, current and predictive views of your business. 2014 IBM Corporation 20
The IBM difference 2014 IBM Corporation 2014 IBM Corporation 21
Why IBM? Simplicity without sacrifice An easy-to-use visual approach to predictive analytics, with the depth and breadth of data access, manipulation and algorithms that meet the needs of a data scientist Open and integrated The ability to access nearly any data source (including Hadoop for big data) and any data format (structured and unstructured); integration with marketplace-leading BI capabilities; and the combination of predictive analytics and business rules within multiple operational environments Flexible deployment Predictive intelligence at scale to support a line-ofbusiness function with insight and to drive decisions across the enterprise 2014 IBM Corporation 22
Dankuwel, tijd voor een demo... 2014 IBM Corporation 2014 IBM Corporation 23