Analytics Innovation Consortium: Virtual Event

Transcription

1 Accenture Analytics Accenture and MIT Alliance in Business Analytics Analytics Innovation Consortium: Virtual Event June 10, 2014

2 Analytics Innovation Consortium, Virtual Event June 10, 8:00 10:00am EST Agenda of Proceedings Timing Topic Facilitator 8:00 8:15 (15 min) 8:15 8:45 (30 min) 8:45 9:15 (30 min) 9:15 9:35 (20 min) 9:35 9:55 (20 min) 9:55 10:00 (5 min) Welcome & Brief Introductions Consortium-Led Topic: The Analytics Journey One company s analytics journey outlining where they have been, where they are headed & the key challenges along the way. Consortium-Led Topic: An Analytics Problem Statement Description of a specific analytics problem currently faced by one company, their initial approaches and consortium collaborative input on a solution. Consortium Input to the October Event Agenda Confirm and rank topics of interest and determine approach for collaborating in preparation for the live event. Glimpse into Fraud Detection Research Snapshot of preliminary visualizations in fraud detection with city services and how these models can be applied cross-industry. Reflections & Closing David Simchi-Levi, MIT Brian McCarthy, Accenture Terry Hemken, ABI Srinivas Reddy, P&G Brian McCarthy Abel Sanchez, MIT David Simchi-Levi Brian McCarthy 2

3 Agenda Welcome & Brief Introductions Consortium-Led Topic: The Analytics Journey Consortium-Led Topic: An Analytics Problem Statement Input to October Event Agenda Glimpse into Fraud Detection Research Reflections & Closing Prof. David Simchi-Levi Brian McCarthy Terry Hemken, ABI Srinivas Reddy, P&G Brian McCarthy Prof. Abel Sanchez, MIT Prof. David Simchi-Levi Brian McCarthy 3

4 Consortium Leadership David Simchi-Levi Professor of Engineering Science MIT Narendra Mulani Senior Managing Director Accenture Analytics Brian McCarthy Analytics Innovation Consortium Sponsor Accenture Analytics 4

5 Global Consortium Participants North America Europe Asia Chris Drunsic Nike, Director NA Analytics Group Oregon, USA Terry Hemken ABI, Senior Director BI St. Louis, USA Bob Palermo Shell, VP Performance Excellence & Enterprise Architecture Houston, USA Harj Chand AGL, Head of Business Analytics Atlanta, USA Julie Trowbridge-Dillman Travelers, EVP Enterprise Business Intelligence & Analytics Minneapolis, USA Murli Buluswar AIG, Chief Science Officer New York, USA Srinivas Reddy Procter & Gamble, Director, Process & Engineering, Global Shave Care & Braun Boston, USA Paul Jansen Sanofi, Global Head of Medical Boston, USA Damien Daly Bank of Ireland, Director, Marketing and Customer Analytics Dublin, Ireland Stan Sthanunathan Unilever, Sr. Vice President - Consumer & Market Insights London, UK Giovanni Pepicelli Enel, Global ICT - Business Relationship Management - Innovation Rome, Italy Vicente Gil Chimeno Gas Natural Fenosa (GNF), Coordinator, Generation Technologies Barcelona, Spain Liz Moore Telstra, Director of Research Insights & Analytics Melbourne, Australia Gautam Bose National Australia Bank, General Manager, Customer Strategy & Analytics Melbourne, Australia 5

6 Agenda Welcome & Brief Introductions Consortium-Led Topic: The Analytics Journey Consortium-Led Topic: An Analytics Problem Statement Input to October Event Agenda Glimpse into Fraud Detection Research Reflections & Closing Prof. David Simchi-Levi Brian McCarthy Terry Hemken, ABI Srinivas Reddy, P&G Brian McCarthy Prof. Abel Sanchez, MIT Prof. David Simchi-Levi Brian McCarthy 6

7 Topic Facilitator Terry Hemken Anheuser-Busch InBev, Senior Director Business Intelligence St. Louis, USA 7

8 ABI June 2014

9 Agenda Welcome & Brief Introductions Consortium-Led Topic: The Analytics Journey Consortium-Led Topic: An Analytics Problem Statement Input to October Event Agenda Glimpse into Fraud Detection Research Reflections & Closing Prof. David Simchi-Levi Brian McCarthy Terry Hemken, ABI Srinivas Reddy, P&G Brian McCarthy Prof. Abel Sanchez, MIT Prof. David Simchi-Levi Brian McCarthy 9

10 Topic Facilitator Srinivas Reddy Procter & Gamble Director, Process & Engineering, Global Shave Care & Braun Boston, USA 10

11 Analytics Innovation Consortium June 10, 2014 Analytics Problem Statement

12 Srinivas Reddy Director of Engineering Global Shave Care & Braun

13 Innovation is our lifeblood

14 2013 New Product Pacesetters List 7 of the top 10 non-food products belong to P&G

15 Problem Statement Demand forecast inaccuracy for new product initiatives leading to higher than desired inventories, supply chain inefficiencies and at times customer service issues

16 Forecast Inaccuracies Use of modeling, consumer testing, discussions with the customers and experience to forecast demand By country, by channel, by sku accuracy needed for efficient capacity planning Once in the market, feedback is too slow We tend to be very conservative to avoid any customer issues higher capital & inventories

17 Opportunity Good application for Analytics improve forecast accuracy & response time (faster feedback)

18 Agenda Welcome & Brief Introductions Consortium-Led Topic: The Analytics Journey Consortium-Led Topic: An Analytics Problem Statement Input to October Event Agenda Glimpse into Fraud Detection Research Reflections & Closing Prof. David Simchi-Levi Brian McCarthy Terry Hemken, ABI Srinivas Reddy, P&G Brian McCarthy Prof. Abel Sanchez, MIT Prof. David Simchi-Levi Brian McCarthy 18

19 Topic Facilitator Brian McCarthy Analytics Innovation Consortium Sponsor Accenture Analytics 19

20 Analytics Driven Performance sets the Foundation for Multiple Themes of Discussion A. Contextual business intelligence and performance management Decision Science B. Advanced cognitive capability tied to visual literacy, collaboration and workflow C. Trigger-based alerts for role based recommendations D. Closed-loop process powered by machine learning E. Cultural adoption of fact-based decision making Analytics Link to Performance Digital Consumer A. Always on interaction model that captures all touch points w/ mobile consumers B. Wiring the organization for relevant and timely recommendations to consumers C. Creating an opt in model for monetizing consumer information D. Balancing the trust and value equation Machine to Machine / Big Data A. Always on streaming data from sensors B. Detecting fraud and cyber attacks when machines lie C. Impact of drones in your industry D. Pace of technology innovation compared to organizations ability to adopt 20

21 Decision Science Decision Science A. Contextual business intelligence and performance management B. Advanced cognitive capability tied to visual literacy, collaboration and workflow Analytics Link to Performance C. Trigger-based alerts for recommended actions for specific roles. D. Closed-loop process powered by machine learning E. Cultural adoption of fact-based decision making 21

22 Digital Consumer Analytics Link to Performance Digital Consumer A. Always on interaction model that captures all touch points w/ mobile consumers B. Wiring the organization for relevant and timely recommendations to consumers C. Creating an opt in model for monetizing consumer information D. Balancing the trust and value equation 22

23 Machine to Machine / Big Data A. Always on streaming data from sensors Analytics Link to Performance B. Detecting fraud and cyber attacks when machines lie C. Impact of drones in your industry Machine to Machine / Big Data D. Pace of technology innovation compared to organizations ability to adopt 23

24 Agenda Welcome & Brief Introductions Consortium-Led Topic: The Analytics Journey Consortium-Led Topic: An Analytics Problem Statement Input to October Event Agenda Glimpse into Fraud Detection Research Reflections & Closing Prof. David Simchi-Levi Brian McCarthy Terry Hemken, ABI Srinivas Reddy, P&G Brian McCarthy Prof. Abel Sanchez, MIT Prof. David Simchi-Levi Brian McCarthy 24

25 Topic Facilitator Abel Sanchez Executive Director and Chief Technology Architect MIT 25

26 SAFARI Situational Awareness Framework for Risk Ranking Abel Sanchez, John Williams, Alan O'Loughlin and Sascha Boheme Alberto Garcia-Robledo, Rongsha Li, Sanjay Kumar-Gautam Accenture and MIT Alliance in Business Analytics June 10, 2014 z Accenture MIT Alliance in Business Analytics SAFARI: Situational Awareness Framework for Risk Ranking 26

27 Corporate Computing: Data Explosion & Complexity MIT GDC Situational Awareness Framework for Risk Ranking 27

28 50 Billion Devices by 2020 MIT GDC Situational Awareness Framework for Risk Ranking 28

29 MIT, Accenture, & Commonwealth of Massachusetts Goal: Reducing False Positives MIT GDC Situational Awareness Framework for Risk Ranking 29

30 SAFARI: Open Workflow And Architecture Accenture MIT Alliance in Business Analytics SAFARI: Situational Awareness Framework for Risk Ranking 30

31 Design Principles MIT GDC Situational Awareness Framework for Risk Ranking 31

32 SAFARI: RFs and RFNet Integration RFNets automatically connect disparate but related entities and red flags to build fully contextualized potential fraud cases from data and detected anomalies. Accenture MIT Alliance in Business Analytics SAFARI: Situational Awareness Framework for Risk Ranking 32

33 RFNet Pair-Wise Node Match RFNet node match f_fuzzy_lname_match f_phon_lname_match l i v 0 v 1 f_geo_addr_match f_vcc_match Accenture MIT Alliance in Business Analytics SAFARI: Situational Awareness Framework for Risk Ranking 33

34 Community of Payments MIT GDC Situational Awareness Framework for Risk Ranking 34

35 Communities of Payments MIT GDC Situational Awareness Framework for Risk Ranking 35

36 Radial Network Visualization MIT GDC Situational Awareness Framework for Risk Ranking 36

37 Communities of Payments MIT GDC Situational Awareness Framework for Risk Ranking 37

38 SAFARI: Web-Based Visual Analytics Accenture MIT Alliance in Business Analytics SAFARI: Situational Awareness Framework for Risk Ranking 38

39 SAFARI Visualization Web-GUI Improvements Accenture MIT Alliance in Business Analytics SAFARI: Situational Awareness Framework for Risk Ranking 39

40 Geolocation Matching MIT GDC Situational Awareness Framework for Risk Ranking 40

41 Benefits of the 3-Level SAFARI Platform Innovative fraud detection platform with increasing levels of intelligence and automation of fraud risk management. RF anomaly detection + RFNet integration + Visual Analytics + Prediction Analytics approach that discover and learn from fraud patterns in large volumes of unlabeled financial data. Open platform that can be extended in the future to take advantage of new advances and add more capabilities in data and visual analytics for fraud detection. Accenture MIT Alliance in Business Analytics SAFARI: Situational Awareness Framework for Risk Ranking 41

42 SAFARI Open Architecture Applications Scale risk assessment and prediction Cybersecurity monitoring and attack detection Insurance, bank and other kinds of financial fraud Accenture MIT Alliance in Business Analytics SAFARI: Situational Awareness Framework for Risk Ranking 42

43 Thank You for Your Attention Datasource for this visualization: data.gov.uk Accenture MIT Alliance in Business Analytics SAFARI: Situational Awareness Framework for Risk Ranking 43

44 Agenda Welcome & Brief Introductions Consortium-Led Topic: The Analytics Journey Consortium-Led Topic: An Analytics Problem Statement Input to October Event Agenda Glimpse into Fraud Detection Research Reflections & Closing Prof. David Simchi-Levi Brian McCarthy Terry Hemken, ABI Srinivas Reddy, P&G Brian McCarthy Prof. Abel Sanchez, MIT Prof. David Simchi-Levi Brian McCarthy 44

45 Join Us on the Analytics Innovation Consortium Website 45

46 Other MIT Events of Interest: MIT s Supply Chain Forum Conference Manufacturing & Industrial Internet 46

47 Next Consortium Event Live Event: October 23 & 24 Thursday, 9:00am 5:00pm, dinner to follow Friday 8:30 1:00, including lunch Location: MIT Campus 47