1. © Copyright 2013 Wellesley Information Services, Inc. All rights reserved. Case Study: Lessons from Animal Health International's SAP NetWeaver BW to SAP HANA Migration Project Tim Hays Dr. Berg Animal Health International, Inc. Comerit Inc.

2. 1 What We’ll Cover …  Introduction to Animal Health International  Animal Health International goes to HANA  Animal Health International’s vision for Customer and Inventory Stratification on HANA  Defining KPIs  Identifying Data  Designing the Solution  Wrap-Up

3. 2 Animal Health International  Animal Health International, headquartered in Greeley, Colorado, is the premier animal health company and a leading distributor of production and companion animal health products  85 locations; Over 500 sales representatives

4. 3 Animal Health International 80,000 Customers  Large and Small Animal Veterinarians, Producers and Retailers  Companion Animal, Equine, Beef, Dairy, Poultry and Swine 85,000 SKUs sourced from over 2,000 Manufacturers  Pharmaceuticals, vaccines, diagnostics, equipment, software, pet foods, devices and other animal health supplies Call Centers, Distribution Centers, Retail Stores, Mobile Stores (Trucks), B2B E-Commerce

5. 4 What We’ll Cover …  Introduction to Animal Health International  Animal Health International goes to HANA  Animal Health International’s vision for Customer and Inventory Stratification on HANA  Defining KPIs  Identifying Data  Designing the Solution  Wrap-Up

6. 5 2013 Infrastructure before HANA  2013 Landscape before SAP HANA SAP ERP 6.0 EhP6 SAP BW 7.3 Virtualized on HP-UX, DB2 v9.7

7. 6 Next generation SAP Real-time Data Platform

8. 7 Installation of SAP Hana  June 2013 – Go-Life with BW 7.30 on Hana  Actual migration of environment took 5 weeks  Prepping the BW on DB2 system took 3 month  Rolled out SAP HANA Studio and Data services

9. 8 BW 7.3 on HANA Landscape

10. 9 Reducing the layers and complexity SAP HANA Row/Column store OLAP OLTP Structured Unstructured Real-time Replication Batch ETL/ELT PlanningPredictive/Statistical Application ServicesUI Development tools

11. 10 What We’ll Cover …  Introduction to Animal Health International  Animal Health International goes to HANA  Animal Health International’s vision for Customer and Inventory Stratification on HANA  Defining KPIs  Identifying Data  Designing the Solution  Wrap-Up

12. 11 AHI’s Stratification Vision Customer Stratification: Method of stratifying customers into key groups to improve process and relationships. Example: Silver, Gold, Platinum customer status (hotel, airline industry)

13. 12 AHI’s Stratification Vision Common Practice 1.No defined customer stratification 2.Customer groups based on market type or product line 3.Top customers based on revenue or gross profit

14. 13 AHI’s Stratification Vision (cont.) Good Practice Based on more than one factor 1.Volume [sales $] based 2.Gross margin 3.Business potential 4.Includes lagging and leading indicators

15. 14 AHI’s Stratification Vision (cont.) Best Practice Based on many factors 1.Business potential 2.Profitability 3.Customer loyalty 4.Cost to serve

16. 15 AHI’s Stratification Vision (cont.) The vision is defined by the questions being asked CEO How can I increase Profit Company wide ? Sales rep. Which Customer should I pursue? Sales manager Which Customers are most profitable? Plant manager How much should I purchase? When? Marketing manager How can I increase brand loyalty?

17. 16 AHI’s Stratification Vision on HANA Why Hana ? 1.The first time we are able to analyze the necessary data volume needed for stratification (e.g. 700.000 records daily for stock data married up with Copa data) 2.Gives us the flexibility to have near real-time reporting if necessary 3.Reduced reporting response time by over 30 % allowing us to include larger user community

18. 17 What We’ll Cover …  Introduction to Animal Health International  Animal Health International goes to HANA  Animal Health International’s vision for Customer and Inventory Stratification on HANA  Defining KPIs  Identifying Data  Designing the Solution  Wrap-Up

19. 18 Lagging and Leading Indicators Important indicators You decide which ones are most important to you and concentrate on those Customer Loyalty Buying Power Cost to Serve Customer Rebates Profitability

20. 19 Customer Ranking define your ranking criteria

21. 20 What We’ll Cover …  Introduction to Animal Health International  Animal Health International goes to HANA  Animal Health International’s vision for Customer and Inventory Stratification on HANA  Defining KPIs  Identifying Data  Designing the Solution  Wrap-Up

22. 21 SAP Data Sources MM ERP Data SD 3 rd Party Government, Social CRM COPA Financial BPC Initiate a data reconnaissance effort Data you have in ERP but not yet available in Data Warehouse Data ready to report on in Data warehouse (might need some remodeling) Data coming from entirely external data sources (in our case governmental websites containing Agriculture statistics)

23. 22 Opportunity Data find data relevant to you

24. 23 Data Challenges Multiple sources of Internal data  More than one ERP system  More than one CRM platform Data is not collected congruently  Rebates, chargebacks, net-downs impact sales revenue and profitability calculations 3 rd party data is hard to correlate  No common key between internal and external data Dataset is too large to process with available tools  85,000 products * 80,000 customers * 400 plants

25. 24 It Starts with the Data Data Analytics Stratification Views

26. 25 Stratification Views Data Inventory COPA External Statistics Customer ranking view Inventory Ranking view Profitability View Sales Penetration view  Inventory, Copa and external statistics data are the building blocks of AHI’s Stratification solution  Based on this data we have Customer ranking reports, Inventory ranking reports, Sales Penetration reports and Profitability reports

27. 26 What We’ll Cover …  Introduction to Animal Health International  Animal Health International goes to HANA  Animal Health International’s vision for Customer and Inventory Stratification on HANA  Defining KPIs  Identifying Data  Designing the Solution  Wrap-Up

28. 27 Example: AHI’s Inventory Stratification Inventory Stratification: Method of stratifying inventory (items/SKUs) into high and low performing groups. Example: A B C D

29. 28 Inventory Stratification Sales Revenue Hits GMRIO Average Inventory ____________________________________ Gross Margin Count of Order Lines Sales as % of Total Sales

30. 29 Inventory Ranking define your ranking criteria Rank% of Total A60% B20% C10% D

31. 30 Inventory Stratification Stage Inventory snapshot data for amount and value on hand per plant

32. 31 Inventory Stratification (cont.) COPA data staged

33. 32 Inventory Stratification (cont.) Combine Inventory Snap Shot with COPA data Inventory Snapshot COPA Invoice level Inventory Stratification Reporting Level

34. 33 Customer Stratification Apply algorithms to basic data and populate Stratification staging DSO

35. 34 Inventory Stratification Inventory Stratification Demo Using HANA

36. 35 Business Adoption Education  Sessions for Business and IT Executive sponsorship  This cannot be an IT or Marketing project, it must have high- level support Create a cross-functional project team  Marketing  IT  Sales Tie to incentive programs Make it a game

37. 36 Customer Stratification Predictive Analytics HANA R – K Means HANA R – Decision Trees

38. 37 What We’ll Cover …  Introduction to Animal Health International  Animal Health International goes to HANA  Animal Health International’s vision for Customer and Inventory Stratification on HANA  Defining KPIs  Identifying Data  Designing the Solution  Wrap-Up

39. 38 7 Key Points to Take Home Stratification is critical to understanding customer and inventory performance over time Customer and inventory stratification methodology will require business adoption to be useful Available data will determine starting point for ranking criteria Acquiring quality data can be a challenge Ranking customers and inventory with limited data set is better than no ranking at all Stratification can be a big data problem requiring tools like HANA Business adoption will require education and an implementation plan

40. 39 Where to Find More Information www.naw.org/publications/pubs_item_view.php?pubs_itemid=145  Customer Stratification Overview http://id.tamu.edu/intensive-customer-stratification-program  Texas A&M University Education http://events.sap.com/sapphirenow/en/session/2371  Gray Bar utilizing HANA for Customer Stratification www.sap.com/asset/index.epx?id=aaff7f67-7400-490e-a800- ad08f4f1eb09  SAP Customer Value Intelligence Overview

41. 40 Your Turn! How to contact us: Tim Hays Tim.Hays@AnimalHealthInternational.com Dr. Berg bberg@comerit.com

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