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The impact of Big Data and applied analytics along the value chain by Guy Peri at Big Data Spain 2017

The impact of Big Data and applied analytics along the value chain by Guy Peri at Big Data Spain 2017

Guy Peri, Chief Data Officer at The Procter & Gamble Company, will share how big data and applied analytics can have a real impact on how you optimize supply chain and connect with customers.

https://www.bigdataspain.org/2017/talk/impact-big-data-applied-analytics-along-value-chain

Big Data Spain 2017
November 16th - 17th Kinépolis Madrid

Big Data Spain

November 30, 2017
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Transcript

  1. Touching and Improving Lives Through Technology, Data & Analytics Big

    Data Spain 2017 Guy Peri Chief Data Officer
  2. • Application to Supply Chain • Application with Customers •

    Skills Needed for Success • Learnings to Date AGENDA Big Data Analytics
  3. P&G’s World Class Supply Chain led to being in the

    first class of Supply Chain Masters based on Gartner’s rankings. Data and analytics play a significant role in achieving this milestone. • Supply Chain Network Design • Inventory Analytics and Tools. • Transportation Analytics and Solutions • Big Data / AI Applied to Concurrent Optimization Building the Supply Chain of the Future SUPPLY CHAIN ANALYTICS
  4. How AI & Commercial Data Drove Sales Results in India

    HISTORICALLY • Served 1.7 million high frequency stores in India the same. TODAY • Advanced algorithm recommends specific SKUs based on consumer behavior. • Sales reps receive targeted selling list for every sales call. IMPACT • Meaningful increase in Sales. • Launched to 40 distributors, 800 branches, 5,600 sellers.
  5. Procter & Gamble’s Olay launched a Skin Advisor platform that

    uses AI to analyze skin using selfies and recommend products
  6. What is Required to Bring Data Science to Life •

    High Value Business Problems Solvable via Algorithm • Big Data Environment with Supporting Data Flows, Engineering, and Data Wrangling • Data Scientists (Blend of Math, Statistics and Computer Science)
  7. Discussion to gather business questions, hypothesis, decision making processes and

    value to the business Clarity on data needed. Extract data, transform the structure and load it into modeling system Select appropriate analytic method/algorith m to answer question with available data. Test results Explain the Result. Help the business to “get it”. Guidance to Action Typical Data Science Work Flow
  8.  1.5X growth year on year  Expertise in Machine

    Learning, Artificial Intelligence, Statistics, and Operations Research  100s of years of combined
  9. Learnings To Date • Business Problem Focused • Shiny Objects

    • Data as Strategic Asset • Work Process Change Technology, Data & Analytics Business Domain Communication
  10. Transforming P&G with Algorithms Which is More Challenging: Creating Self

    Driving Truck or Designing a Promotion Plan? Notes: 1. Otto Tripled Productivity of Driver 2. Attacked Easiest Part of Problem: Highway Driving 3. Idea to Road Test <12 Months