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Keynote "Out of the box -- Thoughts on Data Evolution" at the plenary of Icfai Business School's BIAKM-2013, April 18th.

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  • Relate each points to Jacobson specific KPIs
  • IBS-BIAKM-2013-keynote

    1. 1. Out of the Box--Thoughts on DataEvolution-- Mahboob Hussain
    2. 2. Contents• whoami• Analytics• BI• Big Data and Logistics• The Box• Future directions : some thoughts• Things I want to explore• Q & A
    3. 3. whoami• VNIT Nagpur, Webster University• Vice President (Technology), Four Soft Limited.Previously with Mukand, Parametric TechnologyCorporation, FedEx• http://bit.ly/mahboob
    4. 4. Tom DavenportUniversity of Houston ISRCNovember 15, 2007Analytics : Starting source
    5. 5. Definitions and Insights• What are analytics?• Comparison with DM, BI• How is it different from before?• Is the claim valid?
    6. 6. 6 | 2007 © All RightsReserved.The Planets Are Alignedfor Analytics• Powerful IT• Data critical mass• Skills sufficiency• Business needSource :http://bauer.uh.edu/uhisrc/ppt/ISRC_CompetingonAnalytics_T.Davenport.ppt
    7. 7. 7 | 2007 © All RightsReserved.What Are Analytics?AnalyticsWhat’s the best that can happen?What will happen next?What if these trends continue?Why is this happening?What actions are needed?Where exactly is the problem?How many, how often, where?What happened?CompetitiveAdvantageDegree of IntelligenceReportingDecision OptimizationPredictive AnalyticsForecastingStatistical modelsAlertsQuery/drill downAd hoc reportsStandard reportshttp://bauer.uh.edu/uhisrc/ppt/ISRC_CompetingonAnalytics_T.Davenport.ppt
    8. 8. 8 | 2007 © All RightsReserved.What Should Organizations Do withAnalytics?• Using analytics is goodo Finding the best customers, andcharging them the right priceo Minimizing inventory in supply chainso Allocating costs accurately andunderstanding how financialperformance is driven• Competing on analytics is bettero Making analytics and fact-baseddecisions a key element of strategy andcompetition Subset of BIhttp://bauer.uh.edu/uhisrc/ppt/ISRC_CompetingonAnalytics_T.Davenport.ppt
    9. 9. Gartner : The source• What is BI? (Gartner)o Integration• BI Infrastructure• Metadata management• Development tools• Collaborationo Information Delivery• Reporting• Dashboards• Ad hoc query• Microsoft Office Integration• Search Based BI• Mobile BIo Analysis• OLAP• Interactive Visualization• Predictive modeling and data mining• Scorecards• Prescriptive modeling, simulation and optimization Our own tool @ 4S
    10. 10. © 2011 FOUR SOFT LIMITED. All rights reserved. “This presentation is for informational purposes only and may not be incorporated into a contract or agreement.”for Informed Decision Making
    11. 11. The Product4S Infotips is a futuristic SCM BI tool which helps the companyCXOs, Managers, Supervisors & executives across all departments; Visualize the Business Performance across various parametersthrough Dashboards *Analyze huge volume of Data to understand relationships, trendsin business through a very simple, powerful and user-friendly GUI Identify exceptional events, analyse the causes and make informeddecisions by studying the required information represented on thedashboard.* Some Features limited for Enterprise Edition User Licenses
    12. 12. What’s Infotips?DATAINFORMATIONKNOWLEDGEDECISIONSo what are the Critical Success Factors?(2) *The Ability to study the infofrom any angle(1) The Ability to combine Datafrom multiple sources(3) The Speed of Analysis* Feature limited for Enterprise Edition User Licenses
    13. 13. 4S PRE DEFINED KPIs4S PREDESIGNED DASHBOARDSCustomerViews with 4S Predefined KPIs* Defines New KPIs with available data fieldsModeleTranseCustomsVisilogVisilog PluseLog4SeProductsDBExternalproductsDB4S Data Modeling & LoadingeTrans-FFeCustoms-CustomsVisilog -VisibilityeLog-WarehousingVisiLogPlus-Shipper4S Creates new KPIs & related changes inData Modeling as per Customer Request* Feature limited for Enterprise Edition User Licenses
    14. 14. Standard KPIs for Shipper Logistics (Visilog Plus)1. Purchase Order Response Time2. Purchase order Quantity Fulfillment3. Purchase Order Lead time4. Carrier delivery efficiency5. Item profitability Against Storage6. Inventory Ageing Analysis
    15. 15. Sample Dashboard What is the current statein the field?
    16. 16. Current State• Descriptive to Diagnostics• Emphasis on DD (what is it)• Big Data: The ability to find patterns, correlations andinsights across multistructured data will become amainstream requirement as companies try to betterinnovate and find operational efficiencies acrossbusiness processes that leverage data. These includecapabilities that enable thecollection, storage, management, correlation, organization, exploration and analysis of multistructured data.(Gartner 2013)(JasperSoft with native interfaces to MongoDB, / HBase, Oracle Big Data Appliance, Tibco Spotfire for Big DataAnalytics, SAP Data Integration with Hadoop / Hive etc).
    17. 17. The source
    18. 18. Key points• Term origin• Definition• What it is not?• Three major mindset shiftso N = allo Loosen up our desire for exactitudeo Correlation over causality• Datafication Let’s talk about what’s happening in the enterprise.
    19. 19. 8 Business Functions TCS Explored for Big Data PracticesIn addition to surveying IT and analytics executives, TCSalso wanted to collect the experiences of senior managersin eight core business functions:• Marketing and Sales• Customer service (post-sale)• Manufacturing (or production in services companies)• R&D/product development/product engineering• Logistics/distribution• Human resources• Finance/accountingThese managers accounted for 62% of the total surveypopulation.http://sites.tcs.com/big-data-study/big-data-pie-business-function/
    20. 20. Cutting the pieHow Companies Cut the Big Data Pie by Functional Area
    21. 21. Departmental ImpactHighlights:• Sales and marketing get the biggest shares of the Big Data pie• However, finance and logistics expect the highest ROI on Big Data• Eight business functions vary significantly in where they see the benefitsfrom Big Data – and the biggest challenges they face in gaining thosebenefitshttp://sites.tcs.com/big-data-study/findings-business-functions/
    22. 22. Logistics : The source
    23. 23. The Story• Gripping story of globalization• McLean’s total involvement• Coastal route – container ships
    24. 24. Cargo cost of the pastCash Outlay Percent of CostFreight to U.S. port city $341 14.3%Local freight in port vicinity $95 4.0%Total port cost $1,163 48.7%Ocean shipping $581 24.4%European inland freight $206 8.6%Total $2,386Cost of Shipping One Truckload of Medicine from Chicago toNancy, France (estimate ca. 1960)
    25. 25. The SS Warrior : Cost and TimeNumber of Pieces Percent of weightCase 74,903 27.9%Carton 71,726 27.6%Bag 24,036 12.9%Box 10,671 12.8%Bundle 2,880 1.0%Package 2,877 1.9%Piece 2,634 1.8%Drum 1,538 3.5%Can 888 0.3%Barrel 815 0.3%Wheeled vehicles 53 6.7%Crate 21 0.3%Transporter 10 0.5%Reel 5 0.1%Undetermined 1,525 0.8%Total 194,582 98.4%5,015 tons, 194582 individual items, 95 days, $237577, 36.8%
    26. 26. Impact of the box• Cut costs• Cut time• Destroyed old economy• Helped build a new economy• Massive global trade• Combined with the computer, it lead to JIT
    27. 27. Pondering : Out of the boxThe Box Big DataA self – made ruthless businessmagnate???Excessive focus on cost cutting ???Consolidating items into the container ???End to end innovations ???Standardizations ??? A couple of Box inspired innovations mentioned in the book. And I want to explore more.
    28. 28. Things I want to explore• Hazy• Big Data and Philosophy• Brain : The ultimate domain
    29. 29. Questions ???Thanks