PepsiCo & Safeway A “Big Data” Collaboration To Reduce Out-Of-Stocks Using Visualization Techniques

1. PepsiCo & SafewayA “Big Data” Collaboration To Reduce Out-Of-Stocks Using Visualization Techniques Carl Graziani SVP Supply Chain, Safeway Inc. John Phillips SVP, Customer Supply Chain & Global GTM, PepsiCo

2. There Is A Lot Of Data For Collaboration S

3. Safeway Data Sharing Programs Data Sharing Programs In Place With CPG Vendors In Marketing & Supply Chain • Shopper Insight / Loyalty Data Sharing • Supply Chain Data Sharing Share POS And Inventory Data Marketing Data At Household And Segment Level Aimed At Reducing OOS And Inventory, Decisions On Assortment, Increasing Sales Pricing, And Promotion Used By Customer Supply Chain Teams Customer Marketing Teams Typically Cost Nothing To Participate A Fee To Participate S

4. Safeway Data Visibility Program 20 Vendors Are Now Receiving Data From Safeway • Collaborative Process With Safeway Supply Chain To Request Firm Orders To Reduce OOS’s, Distribution Voids & Pre-Event Allocations • Working With PepsiCo & Deloitte On A Data Visualization Program • Collaborative Process With Safeway Marketing Groups For Specific Competitive Responses • Vendors Are Beginning To Report Fourth Quarter Benefits Back To Safeway S

5. Data Visibility Core Competencies S

6. PepsiCo & Safeway Are Collaborating Further P

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8. 360° Retail Execution™ Delivers “Big Data” For Driving Performance • Every Item / Every Store / Every Day • 31+ Retailers Sharing Daily Data • 53,234+ Retail Stores • 130 Million Saleable Units Every Week • Enterprise Program Driven From Center • Annotated With Attributes & Hierarchies • Activated With Account Teams, Supply Chain Field Execution P

9. PepsiCo Believes In The Power Of Data & Analytics To Drive Supply Chain • Near Real-time Data & Dashboards • Identifies Actual & Predictive OOS & Overstock Issues At SKU/ Store Level • Enables Root Cause Analysis • Actionable Tasks Prioritized By Profitability • Drive Sales & Execution • New Product Introductions • Closing Distribution Voids • Promotion Execution & Effectiveness • Store Merchandising & Replenishment • Order & Shipment Forecasts • Retail Pricing Compliance P

10. Demand Signal Repository (DSR) Overview Retailer Shares POS Data Joint Value Creation Account Team Improved Shopper Experience Shared Scorecards DSR Cleanses & Stores Data Dashboards BI Tools Advanced Analytics OOS Alerts In-Store Execution Phantom Inventory NPI Promo Execution Supply Chain P

11. Examples Of Driving Value Through Shared Data Filling Distribution Voids Through Scripted Replenishments Field Teams Are Leveraging Gap Scans Increasing Forecast Accuracy & Driving Supply Chain Efficiencies Through True CPFR & VMI Improved Forecasting Approaches Are Resulting From The Safeway / PepsiCo Partnership P

12. Filling Distribution Voids Through Scripted Replenishments • PepsiCo 360° Analytics Reveal D-Voids • Item-Store-Day Analysis • Planogram Compared To Sell-thru • Missing Items Identified • Potential Lost Sales Calculated • PepsiCo & Safeway Resolve D-Voids • Jointly Develop DC Force-Shipments • Determine Which Products • Agree On Quantities Needed P

13. Filling Distribution Voids Through Scripted Replenishments • Opportunities Identified • 12 Brands Analyzed • Weekly Store Lost Sales Amounted To Several Thousand Dollars Per Item • Actions Taken • Safeway Pushed 2,339 Store/SKUs Across 49 Items • PepsiCo VMI Replenished DC Inventory • Results • Recaptured Sales = $500K -$1.5M P

14. Collaboration Has Led To A Change In Safeway’s Internal Processes, Resulting In Benefits Along The Entire Supply Chain • Higher Forecast Accuracy • MAPE Reduced 20% • Bias Reduced 15% • Improved Store In-stocks • Less Days Of Supply • DOS Reduced 15% YOY • Shorter Order Lead Time • Improved Service Levels • +1.1% Service Level Improvement S

15. We Have Data But Need Analytics & Visualizations Companies That Excel In Advanced Analytics Also Excel In Financial Performance With Profit Margins In The Range Of 19 To 73% Higher Than Those Of Other Companies Data To Enable Decision Making Increasing Employee Expectations Shortage Of Analytical Talent Analytical IQ For Competitive Differentiation Increasing Customer Expectations Personalization And Hyper Targeting The Data Tsunami Availability Of Data S Source: Jim Duffy and Scott Rosenberger, The Future of Consumer Products Companies: Technology – Gaining an Advantage with Advanced Analytics, 2007

16. Why Visualization? Market Forces Highlight The Growth Of Data, A Need For Talent, Changing Expectations & Improving Decision Making 70% Of Our Sensing Receptors Are Dedicated To Vision Certain Visuals Are More Impactful Than Others Such As Relative Position, Groupings, Shading, Etc. fonts, weights, sizes and colors S

17. It’s All About The User Experience We Need To Move From Rows And Columns To Something More Natural And Impactful Yesterday Today These consumers are employees and need to be trained the same way Just as consumers are being preconditioned to learn visually fonts, weights, sizes and colors S

18. Companies Are Investing Significantly In Visualization Capabilities Deloitte Has Made Significant Investment In Our Visualization Capabilities Because We See Visualization As A Critical Step To Understanding Data And Developing Deeper Insights And Other Leading Consumer Products Companies Such As P&G Are Also Making Similar Bets With “Business Spheres” (~50 Locations). S

19. Familiar Visualization Examples Source: SourceMap (http://sourcemap.com) Source: Lumino.so (http://www.luminoso.com/) S

20. PepsiCo, Safeway & Deloitte Visualization Design Session On August 28th, 2012 PepsiCo And Safeway Came To The HIVE (Deloitte’s Highly Immersive Visual Environment) To Design And Rapidly Prototype New Ways To Visualize Key Challenges S

21. Reduce Out Of Stocks & Improve Days Of Supply Challenges And Questions To Address • What Locations Are Causing The Most Significant Challenges & What Are Those Challenges? • What Causal Variables Are Impacting My Days Of Supply & Out Of Stock Performance? • What Brands Are Most Impacted By Out Of Stock & Days Of Supply Performance? • What Are My Total Lost Dollar Sales For A Particular Set Of Events? P

22. Reduce Out Of Stocks & Improve Days Of Supply Streamgraph Force-directed graphs Tree Maps Sunburst 1. Consider A Technique To Visualize The Data Word Tag Cloud Bubble Chart Many Eye Bubble Chart Time Series Analysis Geo Spatial Parallel chord Calendar View Heat Maps Often Used For Highly Dimensionalized Data Sets P

23. Reduce Out Of Stocks & Improve Days Of Supply Rapid Prototype 2. Identify Casual Variables That Impact Out Of Stocks And Days Of Supply 3. Showcases Trends Between Those Factors P

24. Store does not meet in-stock target What stores are key drivers? Itemdoes not meet target NE SA WA Warehouse Adjustment What items are key drivers? Not Enough Sold After NO SI Stocking Issue WS Warehouse Short Not Ordered Review store orders, forecast assumptions, POS Review display inventory Validate available inventory Force-out Product Adjust Store Inventory Review Store Ops Ensure VMI Reorders Determine Recovery P

25. Reduce Out Of Stocks & Improve Days Of Supply How This Visualization Works Effect Cause Day of Week OOS Percentage Brand Lost Dollars Item Velocity DOS OOS Reason Stocking Issues Brand N High Sun High High High Brand 2 Med Wed Med Med Med WH Short Groupings Show Trends, Even If Just One Color Whereas Here There Is No Obvious Trend…maybe You Have To Dig Deeper Not Ordered Brand 1 Mon Low Low Low Low P

26. Reduce Out Of Stocks & Improve Days Of Supply Diving Down Into A Specific Product Root Cause Identification: What are the key reason codes for out-of-stocks in select districts? Corrective Action: If root causes can be identified, can corrective actions be put in place to reduce or remedy the out-of-stocks? Please select the DISTRICT: We are going to begin by filtering our dataset. We can hide in stock data Please select the TRADEMARK: Product 1 Product 2 Product 3 Product 4 Product 5 Product 6 Product 7 Product 8 Product 9 Product 10 Product 11 Product 12 Product 13 Product 6 District 1 District 2 District 3 District 4 District 5 District 6 District 7 District 8 3.39% OOS rate. Let’s dig in further Select Dataset to Visualize District 6 XX District: District 6 YY Trademark: Product 6 P

27. Reduce Out Of Stocks & Improve Days Of Supply Change Thread Coloring To Develop Insights • So far we: • Filtered to show only OOS products • Changed color to reflect OOS Reason Code More “stocking issues” than expected…if we highlight these threads we can see them more clearly P

28. Reduce Out Of Stocks & Improve Days Of Supply Following A Thread To Develop An Insight Interesting, almost all of the stocking issues are from store 2272. Need to get a macro view across all products Highlighted stocking issues P

29. Reduce Out Of Stocks & Improve Days Of Supply Zoom Out And See Bigger Picture • Let’s back up and look at the big picture: • All products • All OOS • Entire district Let’s dig into store 2272 Over $4000 in lost sales for this district over this period XX District 6 Product 1, Product 2 YY Product 3, Product 4, Product 5, Product 6, Product 7, Product 8, Product 9, Product 10 P

30. Reduce Out Of Stocks & Improve Days Of Supply One Location Is Causing A Significant Number Of Lost Sales Highlighted threads related to store #2272 About 1/5 of the lost sales dollars for this region come from one store! That’s 3X higher than the average XX District 6 Product 1, Product 2 YY Product 3, Product 4, Product 5, Product 6, Product 7, Product 8, Product 9, Product 10 P

31. Reduce Out Of Stocks & Improve Days Of Supply Develop Actionable Insight Removed all other stores to focus analysis on store #2272 1/4 of the issues for this store occur on Saturday. We are exploring solutions with PepsiCo for alternate delivery or incremental storage Highlighted threads related to store #2272 XX District 6 Product 1, Product 2 YY Product 3, Product 4, Product 5, Product 6, Product 7, Product 8, Product 9, Product 10 P

32. What We Learned: Collaboration Is Essential • Retailers / Supplies Share The Shelf • The Magic Comes From Sharing • Data: Must Be Free & Open • Insights: Joint Interest In Analysis • Actions: Aligned On Plans / KPIs • Data Visibility & 360 Retail Execution Building “Big Data” Muscle • More Data Streams Are Coming With Digital Couponing, Etc. • Data Has Value Through Collaboration S

33. Safeway & PepsiCo Will Build On Successes Using “Big Data” & Visualization Techniques • Supply Chain Remains An Opportunity For Improved Productivity Within CPG • Data Sharing Provides A Foundation For Retailer/Supplier Collaboration • New Data Visualization Techniques Will Make Use Of Data More Intuitive • CPG Industry Needs To Develop Analytical Competencies in Their Supply Chains P

34. Any Questions? P

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