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What's New in Predictive Analytics IBM SPSS
- 1. What’s New in IBM Predictive Analytics IBM SPSS & IBM Decision Optimization Fuel for the Cognitive Era Jane Hendricks, Portfolio Marketing Manager, IBM SPSS Predictive Analytics Ioannis (Yianni) Gamvros, WW Technical Sales Leader, IBM Decision Optimization
- 2. Session Topics Analytics in the Cognitive Era IBM Advanced Analytics Conceptual Overview Product Alignment Key New Features IBM SPSS Predictive Analytics IBM Decision Optimization Demonstration Next Steps Q&A
- 4. Analytics Driven Organizations Reap Rewards Business outcomes (69%) Revenues (60%) Competitive advantage (53%) Front Runners outperform on Source: IBM Institute for Business Value (IBV) by using data and analytics
- 5. Breadth of analytic use, as reported by respondents: In 2014, 10% of organizations were using advanced analytics in three or more functional areas of their business In 2015, 71% of organizations are using advanced analytics in three or more functional areas of their business and 33% of organizations are using advanced analytics in six or more functional areas of their business Advanced analytics are defined as the extensive use of predictive, prescriptive or cognitive analytics within a business function Organizations have rapidly expanded the use of advanced analytics across business functions Source: Analytics: The upside of disruption. IBM Institute for Business Value 2015 Analytics research study. © 2015 IBM Institute for Business Value.
- 6. IBM Advanced Analytics Today Data Preparation Analytics at Scale Insight to Action ALL Data (Structured, Unstructured, Streaming) All Decisions (People, Systems, Strategic, Operational, Real-Time) • Predictive models • Machine Learning • Statistical Analysis • Decision Optimization • Real-Time Scoring • Optimized Decisions • APIs & services • Dashboards / Interactive apps • Data models • Data connectors • Data Wrangling Analytic ServerModeler CPLEX StudioStatistics IBM® (SPSS®) Predictive Analytics IBM® Prescriptive Analytics Decision Optimization Center (DOC) DOCloud
- 7. Torchbearing CEOs look to predictive analytics in a changing business landscape More digital interaction More competition expected from other industries 82% 60% 60% 40% Business landscape changes (in 3 to 5 years) +37% +50% 2015 2013 2015 2013 Insights from IBM’s Global C-suite Study – The CEO Perspective ibm.com/csuitestudy 66% 50% Use Predictive Analytics Market Follower CEOsTorchbearer CEOs more 32%
- 8. Predictive analytics can use virtually any data to improve virtually any decision Donor management Fraud detection Student success Sales forecasting Employee turnover Insurance claims fraud Cross-sell and upsell Customer retention
- 9. Oak Lawn Marketing, Inc. employs a predictive analytics solution to understand customer buying patterns and to target infomercials Fourfold increase in total revenue expected over a three-year period as a result of infomercials and other campaigns Targets marketing messaging and campaigns to enhance the customer experience and encourage retention 159% boost in the average monthly rate of customers who return to shop compared to the previous year Solution components • IBM® SPSS® Modeler • IBM Training • IBM Business Partner AIT Business challenge: Although Oak Lawn Marketing, Inc. was gathering and generating enormous amounts of data about its programs, the company couldn’t conduct a thorough analysis of customers’ buying patterns using its outdated business intelligence tools or unwieldy spreadsheets. Oak Lawn Marketing needed a predictive analytics solution that would accurately portray and predict customers’ buying trends and help it drive marketing campaigns. The smarter solution: The solution combines predictive analytics, rules, scoring and modeling algorithms as it analyzes transactional and demographics information to help Oak Lawn Marketing understand which products customers are most likely to purchase and to guide the company in its decision-making processes. Using this information, the company can customize its multitude of infomercials with messaging appropriate for various TV channels and time slots and tailor other marketing campaigns, such as Internet and direct mail. “We want to establish a brand that is used by our customers over a long period of time.” —Harry Hill, president and chief executive officer
- 10. • IBM® PureData™ System for Analytics (powered by Netezza® technology) • IBM SPSS® Collaboration and Deployment Services • IBM SPSS Modeler • IBM SPSS Modeler Desktop • IBM SPSS Modeler Server • IBM Training: SPSS 80% reduction in serious accidents among trucking company customers Solution Components Business Challenge: To meet customers’ demands, FleetRisk Advisors needed to extract even deeper predictive insights regarding truck driver safety from an ever-growing range of measured parameters and get it done faster so that customers would have the time to take truly preventive action. The Smarter Solution: For each of the company’s customers’ truck drivers, a powerful new predictive modeling solution translates some 4,500 data elements, from a diverse and ever-growing range of sources, into quantitative risk ratings related to the likelihood of on-the-job accidents, giving operators the cue they need to intervene proactively to prevent such accidents and to save lives. “Our new solution has enabled us to push the boundaries of predictive risk analysis, which has translated into real value for our trucking operator customers that rely on it.” —Patrick Ritto, chief technology officer 20% reduction in the incidence of minor accidents 30% increase in driver retention rates, with commensurate decreases in recruiting and training costs FleetRisk Advisors helps trucking operators prevent more accidents by building stronger and faster risk prediction models
- 11. What’s New in IBM SPSS Predictive Analytics Empower every user Unlock more data, faster Ground to Cloud deployment options Code optional, open to open source Big Data for the desktop Predictive everywhere
- 13. Uncover the Value of the Silent Data Majority 80% of data is unstructured; therefore, invisible to computers and of limited use to business. By 2020, 1.7MB of new information will be created every minute for every human being on the planet. Incorporate GeoSpatial Data Text Analytics with Sentiment Analysis Entity Analytics Massively Parallel Algorithms …delivered to your desktop!
- 14. Simplicity… Without Sacrifice Automatic data preparation Automated model creation Infinitely complex workflows Advanced capabilities (text analytics, entity analytics, scripting)
- 15. Code-Free Deployment at Scale: Activating Analytics Parallel In-Database Optimized for Big Data environments Reduce network traffic Improved processing speed Reduce data movement SQL pushback Optimize performance with in-database adapters Increase analytic flexibility with in-database mining Advanced Model Management (including A/B Testing, Champion/Challenger) In-Database/In-Hadoop Batch/Real-Time/Streaming Point of Impact (Analytical Decision Management)
- 16. Ground to Cloud: Deployment Flexibility • Full breadth of analytical capabilities • Collaboration and enterprise-wide best practices • Customize for (virtually) any use case • On-premises, hybrid and software-as-a-service LOB & Personal Analytics Developer Tools • Analytic tools built for business • Digitally delivered, digitally fulfilled • Variety of licensing and packaging options • Available for Windows or Mac • Build smarter data applications -- quicker • Endless possibilities • No installation, no configuration • Mix & match components Enterprise Analytics IBM SPSS Modeler Gold IBM Cloud Marketplace (SPSS & DOCloud) IBM Predictive Analytics on Bluemix
- 17. Predictive Analytics on BlueMix https://www.ng.bluemix.net/docs/#services/PredictiveModeling/index.html#pm_service
- 18. IBM SPSS & Decision Optimization in Marketplace https://www.ibm.com/marketplace/cloud/us/en- us
- 19. Open Source and IBM Predictive Analytics First R, then Python, now Spark Make coding optional FacilitateEmbrace Extend Make it massively useful
- 20. Extend Capabilities through Open Source: R R Integration R Build/Score, Process and Output node support Scale R execution by leveraging database vendor provided R engines Custom Dialog Builder for R Provides the ability to create new Modeler Algorithm nodes and dialogs that run R processes Makes R usable for non-programmers
- 22. NEW! Python for Spark Data Scientists can create extensions for novice users to exploit R, MLlib algorithms and other Python processes Spark & its machine learning library (MLlib) Other common Python libraries • e.g.: Numpy, Scipy, Scikit-learn, Pandas Abstracting code behind a GUI makes Spark usable for non-programmers
- 24. IBM Decision Optimization for Python Model & solve optimization problems writing pure Python Notebook ready. Community-based documentation and samples Solving on cloud or locally is invisible to APIs* Access the Technology Preview at : pypi : docplex Github : docplex IBM market leading Decision Optimization technology, CPLEX, is now accessible as a Pure Python package under the Apache license (*) Solves the same program for free with IBM DOcloud free trial subscription or IBM CPLEX Optimization Studio Community Edition installation
- 26. Beyond Predictive Capture price, product, location and date for each transaction. Historical & Master Data ETL Determine important variables, predict trends, seasonality etc. Predictions and Insights Allow multiple users to experiment with multiple scenarios. Collaboration & What-if Set policies, promotions etc. Allow reviewers and auditors to have a say. Rules & Process Managemen t Automatically generate decisions, allow user interaction with decisions. Decision Making Key steps for a mature decision support application leveraging advanced analytics Descriptive Predictive Prescriptive
- 27. Advanced Analytics Solutions Documented Value 2 Chilean Forestry firms Timber Harvesting $20M/yr + 30% fewer trucks UPS Air Network Design $40M/yr + 10% fewer planes South African Defense Force/Equip Planning $1.1B/yr Motorola Procurement Management $100M-150M/yr Samsung Electronics Semiconductor Manufacturing 50% reduction in cycle times SNCF (French RR) Scheduling & Pricing $16M/yr rev + 2% lower op ex Continental Airlines Crew Re-scheduling $40M/yr AT&T Network Recovery 35% reduction spare capacity Grantham Mayo van Otterloo Portfolio Optimization $4M/yr Source: Edelman Finalists, http://www.informs.org or http://www.scienceofbetter.org
- 28. Uncertainty is everywhere … Each planning cycle is afflicted by future uncertainties - prices, demand, supply, weather effects… We get caught in a costly reactive cycle where we fix issues after the fact, instead of anticipating and planning for them. We don’t have a clear vision of possible future scenarios, and their effect on plans. Plans are out of date as soon as they are created
- 29. A new approach to planning Contingency Planning Create multiple scenarios using averages Evaluate each as a separate what-if Pick a conservative scenario and act conservatively Robust/Stochastic Planning Create multiple scenarios using confidence intervals Create a single plan of action that balances all tradeoffs
- 30. Benefits – stability, profit Supply chain planning for a motorcycle vendor 2% increase in profits vs. deterministic optimization Inventory optimization for IBM Microelectronics Division Greater than 7x increase in feasibility vs. deterministic optimization Energy cost minimization for Cork County Council 30% value-add in cost reduction vs. deterministic optimization Leakage reduction for Dublin City Council 10 times increased stability vs. deterministic optimization
- 31. One of the Largest North America Logistics Companies Size of operations: Over 15,000 loads per day Over 10,000 trucks and drivers Over 30,000 trailers Over 150 facilities world-wide Looked at intermodal operations and resource placement across 2014 Key challenge is to ensure enough resources are allocated to rail yards on a weekly basis Allocating 50 trailers to Chicago when only 30 are needed Allocating 100 trailers to New York when 150 are needed Repositioning resources takes time and costs money
- 32. Latest Comparison Start 12 instances 1st of every month 20 day horizon Deterministic Single existing forecast Stochastic Create multiple forecasts by varying demand forecast by +/- 10% Deterministic Make decisions based on single forecast Stochastic Make decisions based on multiple forecasts Deterministic Compare with actual demand realization to determine revenue and cost Stochastic Compare with actual demand realization to determine revenue and cost
- 33. Taking Uncertainty Into Consideration -0.1%-20% improvement ~5.1% on average ~$23.9M annually ~$1.3M on average over 20 days
- 34. Robust Planning Scenarios Plans Feasible (darker = better) Infeasible (darker = worse) RobustplansDeterministicplans Infeasible for many random scenarios More stable plans across more random scenarios
- 36. Please contact us for further information: Phone: 800-543-2185 E-mail: [email protected] Website: www.ibm.com/tryspss