Welcome to the session!

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1 Welcome to the session! Experience the ease of an efficient AFTER SALES with Warranty Predictive Analytics solution Krishnan Jayaraman Principal Consultant Tech Mahindra John Hardigree Chief BDO Revolution Analytics Moderator: Kannan Marghasahayam Principal Consultant; Tech Mahindra

2 Agenda Speaker Designation Agenda Krishnan Jayaraman Principal Consultant Tech Mahindra Tech Mahindra s lean Analytics Platform Warranty Analytics Solution Overview John Hardigree Chief BDO Revolution Analytics Revolution Analytics Warranty & Sensor Data Analysis Overview Expert interaction Q&A session

3 Lean Analytics- Simplify, Optimize, Accelerate Simplify Common Storage Infrastructure Business Insights Business Recommendations Predictive Models Optimize Shared Services Accelerate Frameworks & IP Self Service Development Platform Intellectual Property Analytics Platform Business Frameworks Data Management Platform Analytics as a Service Shared Services Domain Experts Data Scientists Data Specialists Authoring/Development Platform Storage Infrastructure A Superior Way to Unlock Value from your Data - In a Box!

4 Lean is Better! Traditional Lean People-centric model Data / Analytics-led approach Domain-specific or Project-specific methodology Capex. lead times and costs Pricing model based on Time and Material (T&M) 100% transfer of delivery/business risks to clients Value-centric model IP and Consulting-led approach Cross-Domain and Best Practices methodology Opex. and business outcome based model Pricing model based on Value Realization and Proof of Value Delivery (POVs). Minimal transfer of delivery/business risks

5 Our Value proposition Traditional Analytics Delivery Approach Engage with Business for Hypothesis Define the KPIs from multiple client meetings Validate the KPIs and finalize the list Seek data and transform as per KPIs Model creation w ith KPIs and refine based on business understanding Show the output of model and seek business feedback Business value realized post solution deployment Accelerated Value Delivery TechM s Lean Analytics Approach Engage w ith business to tick the predefined KPIs from the framew ork Seek the available data points from client Model creation and review the output simultaneously w ith the business for validation and refinement Deliver reports and dashboards Business value delivered immediately after business GO Lean Analytics can significantly reduce the time to delivery and Business Risk More than 50% reduction in time to delivery analytics services

6 Detail Reference Architecture

7 Key benefits of Lean Analytics to Business Value Delivery Accelerate Analytics Value Potential acceleration through analytics framework standardization Head start with built in business KPIs Framework and Industry Domain Use Cases Reduced time to market by 50% Optimize workload for Data Scientists Reuse Analytics Assets Reuse existing knowledge base (Assets KPIs) for new use case creation Reuse existing use cases for faster time to delivery and optimization Leverage internal asset base created within the organization over a period of time Single point Analytical Model Repository Analytics Governance Single point Analytics KPI repository End-to-End business users control on analytics delivery Traceability of legacy use case deployment Standardization of predictive analytical model building initiatives Focus on core skills: Business Insights and Analysis Lean Analytics: Simplify, Optimize, Accelerate Analytics Value Delivery

8 Tech Mahindra- Lean Analytics Platform

9 Tech Mahindra - Lean Analytics Platform

10 Warranty claim cost are becoming one of the major factor of concern for the automobile companies due to higher cost involved & increasingly more incidents of consumer coming for claims under warranty. The automobile manufacturers need a predictive analytics platform to know more about future scenarios about the claims cost so as to plan their fiscal year budgets & take pro-active actions accordingly. The solution predicts the warranty cost for different dimensions like warranty cost for a region & vehicle models. Problem Statement Warranty Forecasting Analytics The claim rates of each month are taken as time series data, considering Trend, Seasonality, Cyclicity and some irregularity, data also includes parameters like labor hours spent, parts used, operations performed Business Solution Modeling Technique : Multiple forecasting models have been built using Arimax (Auto Regressive Integrated Moving Average with External Variables) & linear Regression Solution not only predicts the future claim cost but also provide multiple forecast at various dimensions like the number of vehicles to come for claim in future in different vehicle categories, under different claim types Solution Developed Proactively identifies systematic error patterns and their dependencies, hence enabling to reduce failure. Enabling the finance department to estimate the future cost of warranty claims, so to proactively arrange warranty reserve fund. Helps to identify optimal warranty term based on cost, improving terms and conditions for supplier, manufacturer and customers. Helps organizations to plan their inventory of spare parts & labor required accordingly. Business Benefits Data Preparation Seasonality and Cyclicality Analysis Predictive Analysis Forecasting Time Series Data Analytical Engine Final Outcome analysis & dashboards

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12 OUR COMPANY OUR PRODUCT SOME KUDOS The leading provider of advanced analytics software and services based on open source R, since 2007 REVOLUTION R: The enterprise-grade predictive analytics application platform based on the R language Visionary Gartner Magic Quadrant for Advanced Analytics Platforms,

13 Game Changing Analytics Examples Marketing: Clickstream & Campaign Analyses Digital Media: Recommendation Engines Social Media: Sentiment Analysis Retail: Purchase Prediction Insurance: Fraud Waste and Abuse Healthcare Delivery: Treatment Outcome Prediction Risk Analysis: Insurance Underwriting Manufacturing: Predictive Maintenance Operations: Supply Chain Optimization Econometrics: Market Prediction Marketing: Mix and Price Optimization Life Sciences: Pharmacogenetics Transportation: Asset Utilization 13

14 Model Development for Vehicle Data Analysis >Warranty & Sensor Data Analysis >R/Revolution R Enterprise Training Key Technology and Services: Revolution R Enterprise for Big Data Analytics, Consulting, T raining Analytic Approach Warranty Data Analysis: Estimating the life of an automobile component using Survival Analysis with Cox proportional hazards. Models are trained using historical data, consisting of warranty claims, and region and weather related variables such snow, rain, temperature etc. Outcome: New analytics paradigm for existing processes introduced, with potential for millions of dollars in cost savings through improved warranty contracts, and redesigned automobile components. Profile: T he Analytics R&D team of the multinational automobile manufacturer worked with Revolution Analytics Consultants to perform Survival Analysis, and to build and deploy Decision T rees and T ime Series models Analytic Approach Sensor Data Analysis: Use sensor data from vehicle components to build Decision T rees for classification, and to establish range of predicted values for sensor readings so that actual readings can be analyzed for outliers. Bottom line: New analytics initiative for building an intelligent automobile system that s capable of guiding the driver upon detection of anomalies in driving patterns. The consultants and training instructors from Revolution Analytics were very knowledgeable and supported me very well. I am looking forward to taking my learnings to the larger analytics team at my company. Senior Researcher, Analytics R&D

15 Lean Analytics Platform Sample Screen Shots

16 Potential Impacts Improved warranty cost accuracy

17 Potential Impacts RCA analysis for significant contributors

18 Potential Impacts Reduction in significant warranty cost.

19 Potential Impacts Defect patterns and dependencies.

20 Potential Impacts Reduce failures and improve customer satisfaction.

21 Potential Impacts Improve process efficiency.

22 Q & A session For Demo, Please send request to: [email protected] [email protected] [email protected]