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Advanced Analytics Turin April, 2016 Index ■ Advanced Analytics Approach – Architecture Overview – Methodology – Professional Skills ■ Impacted Areas / Goals 2 Advanced Analytics Approach Business Business Intelligence Structured & Traditional Analysis Answers the Questions • • • • Asks questions What happened? When? Who? How many? IT Advanced Analytics Approach (Big Data) Discovery & Predictive Analysis Delivers a platform to collect data and enable discovery activities Answers the Questions • • • • Why did it happen? Will it happen again? What will happen if we change a variable? What else does the data tell us that we never thought to ask? IT Structures data/reporting to answer business questions IT & Business Explores what questions could be asked Advanced Analytics approach requests: Platform Methodology Skills 3 Platform Analytic Layer NoSQL Layer HAWQ Data Lake Ingestion Internal Data Sources External Data Sources Big data Suite on DCA DIA PHD + HAWQ PHD (Admin) 4 Methodology Iterative Approach Perform each phase in an agile manner an iterate as required Phase 1 Problem Formulation: Make sure to formulate a problem that is relevant to the goals and plain points of the stakeholders Phase 4 Actions Tips and sharing of action / strategic intervention areas, priorities and quick-win. Identification and sharing of the evolutionary roadmap about touch points or support systems to address business requirements. Building a Narrative Create a fact-based narrative that clearly communicates insights to stakeholders Business Opportunity Prioritize more relevant use cases to cover the business needs Phase 2 Data and Modeling Step: Identification of the appropriate analysis models based on data acquisition processes analysis and relevant data sources Phase 3 Presentation Results representation through dashboard and relative report production (positioning matrix and SWOT) Creativity Take the opportunity to innovate at every phase 5 Professional Skills – Data Scientist Programming Parallelized algorithms Expert Statisticians Machine learning Data Scientist Database practitioners Domain Knowledge Process Experience 6 Impacted Areas / Goals Quality Manufacturing After Sales Connected Car Connected Car Supply Chain Supply Chain Plant Customer Customer Plant Production processes Quality gates Order change analysis Eco:Drive MyCar Production Plan Product Engineering Supply Chain management Technical service support Warranty claim Parts sales order Connected Car How to: quality production process, recall campaign and technical support knowledge analysis Early Warning System Connected Vehicles Complexity & Forecasting Goal: − Plant: Proactive prevention Anticipate detection of emerging issues from the plant through correlations analysis between Quality manufacturing issues and Warranty claims − After Sales: Early detection Improve capabilities and timing of issue detection leveraging all aftersales available data 7 Impacted Areas / Goals Quality Manufacturing Connected Car After Sales Connected Car Supply Chain Supply Chain Plant Customer Customer Plant Production processes Quality gates Order change analysis Eco:Drive MyCar Production Plan Product Engineering Supply Chain management Technical service support Warranty claim Parts sales order Connected Car How to: car usage, alarm cockpit and drive style analysis Early Warning System Connected Vehicles Complexity & Forecasting Goal: − Driver segmentation Improve target campaign management based on real usage of the car and better knowledge of our customer − Vehicle pedigree: Propose maintenance services − Alarm warning detection: Improve loyalty of customer through the action based on risk score definition of failure 8 Impacted Areas / Goals Quality Manufacturing Connected Car After Sales Supply Chain Marketing Supply Chain Plant Customer Customer Plant Production processes Quality gates Order change analysis Corporate Website Lead Generation Production Plan Product Engineering Supply Chain management Technical service support Warranty claim Parts sales order Connected Car How to: best sellers configurations, sell seasonality and processes analysis Early Warning System Connected Vehicles Complexity & Forecasting Goal: − Product Complexity: Complexity reduction in order to enhance production and supply chain processes Support Product Manager in Product grid definition and updates Guide customer within decisional process while configuring the product suggesting possible/best optional of interest − Order Forecasting: Automatic creation of Production MIX forecast with high level of accuracy Reduction of real orders requirements due to planning reworks Reduction of real material costs due to urgent transportation and scrapping costs of build out processes 9 Backup Approaches Hindsight Insight Foresight Dynamic and automatic plan and actions adjustments based on future events Value of Analytics ($) Units sold due to specific marketing campaign proposed to dealers 3.000 units of 500 X sold in the last month Proposed campaign to increase units sold by 2% Keys Data Science Business Intelligence How can we make it happen? Prescriptive Analytics What will happen? Predictive Analytics Why did it happen? Diagnostic Analytics What happened? Data Science Descriptive Analytics What is Advanced Analytics? Complexity Business Intelligence 11 Main Benefits Analysis timing reduction and manipulations evolution New Data Availability time-lag reduction (no preliminary transformation to load data) Flexible and seamless access and manipulation of structured/ unstructured data High reduction of processing time of mining operations and application of statistical functions Improvement statistical performance of the models (i.e. the statistical iterations can be multiplied for better performance) 12