Business Discovery @ Make My trip

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Look at how one of India largest travel portal is using QlikView Business Discovery for fact-based decision making. The CIO of Make My Trip shares his views on how Qlik is enabling them in their Business Intelligence, Data Discovery & Analytics approach.

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Business Discovery @ Make My trip

  1. 1. QlikView Case Study @ MakeMytrip 1 Sanjay Kharb Vice President – Business Intelligence and Infra
  2. 2. Vision and Requirements • Make Data Hub rather than DataWareHouse • Single source of truth for serving needs of reports, dashboard, analysis for MMT • Automation, Reconciliation, Trends & Predictive Analytics • Integration of Big Data platform • Help Business User by Self BI • Easy, accurate access to information 2
  3. 3. What were the Challenges • Reporting and Analysis existed in silos • Data analysis & tracking trends was nearly impossible • Inconsistency issues with stale/offline data • Heavy dependency on Excels • Unable to process large amount of transactional data • TAT was more, due to the use of MS Excel • Predictive analysis was missing • SOX compliance does not favor core Financial tasks to be done on Excel 3
  4. 4. Why Qlik View? • Association Model suited our data integration • Feature set matched our needs for rapid development and information availability • Best fit Single stack for entire BI requirement • It provisions for multi geography, multi lingual options for MMT group of companies • We could tailor it for Actions- postings, workflow, hooks to our other systems • Jan 2012 – implementation kick-off Qlikview in MMT 4
  5. 5. Data Hub and Analytics Platform 5
  6. 6. Projects and Products on QlikView - A sneak peek 6
  7. 7. •Bucketed in 4 Areas –Finance –Marketing –Operations –Management 7 Focus Areas
  8. 8. Finance – Air Operations 8 • Background • Reconcile data from Airlines, Banks and Payment gateways • ETL from multitude sources like API’s Web crawling, Emails, CSV dumps • Auto posting of reconciled data into ERP • MIS, Leakage, Predictive Reports
  9. 9. Finance – Air Architecture: 9
  10. 10. Finance – Land Operations • Tracking booking during life cycle from sales till operations to mmt agents • Typical Analytics – Product ,Vendor Payment tracking system – Customer outstanding Alert System – Outstanding Debtors – MTD, YTD , QoQ and DoD trendings 10
  11. 11. Finance - Statuary Report System • Ratios allocation for different entities • LOB wise Dimension Analysis for Different Entities • Chart of Account Analysis for Different Entities • Trail Balance Analysis for Different Entities • Profit & Loss Analysis based on LOB • Historic data analysis and trending • Operating Matrix for Quarter earning/growth 11
  12. 12. Marketing - Demand Calendar • Search and Travel Hotspot Analyzer • Hooked with Events • Real time demand in upcoming months by – destinations, dates/ events, origin cities and LOB(s) – Predictive analysis based on booking & search analytics 12
  13. 13. Marketing - Loyalty Decision System • Prediction analysis on WoW, MoM based on points earned/redeemed • Trending of earn/burn points per booking by LOB, Activity, Tier, Date • Tier activity tracking system 13
  14. 14. Marketing – Campaign Management 14 • Automation of segments & bucketing of customers • Identifying New Acquisitions • Handling Reactivation Base • Promoting Mobile App Downloads • Data management(standardize and normalize) • Preference Management
  15. 15. Marketing - Bidding Automation • Cheapest Rate Bidding Analyser • DMC/Hotels Response-Performance Dashboard • Meta/TA Cache Rate Integrity Analyser 15
  16. 16. Operations -Call Center WorkFlow Automation • WorkFlow For Call Center Operations • Help to resolve VISA, Payment, Vouchers, Customer Queries • Integerated with CRM • Streamlined the Call Centers Queues 16
  17. 17. Management Dashboard • Single View for Finance, Operations, Business, Marketing and Technical Performance • Daily, Weekly Dashboards for overall Performance, trend Analysis • ROI, Margin Dashboard • Outliers 17
  18. 18. Learning • Needs patience, first victory will seem far fetched • Build incrementally • Have a long term view on Data Model and Design • Functionality first, data representation later • Savvy Engineers - Inhouse or SI 18
  19. 19. What can Qlik can do better • Use of Flash Disks a/w In-memory • More Qlik’s Consultants in India • More Flexible Licencing 19
  20. 20. Thank You Contact: sanjay.kharb@makemytrip.com 20

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