CPFR ® Technology

1. CPFR® Technology Henry C. Co Technology and Operations Management, California Polytechnic and State University

2. Cornerstones of CPFR® Internal Processes Joint processes Technology Småros J., and Kary Främling, “Peer-to-Peer Information Systems - An Enabler of Collaborative Planning, Forecasting and Replenishment,” available online from http://www.cs.hut.fi/~framling/Publications/LRN2001.pdf

3. Technology Scalability through collaborative processes that are flexible, fast to implement and easy to integrate. Joint processes Technology for secure, reliable and cost-effective information sharing and communication. Internal processes that produce and use collaborative information. • Open System • Internet • Application Development Methods • Secure Communication • Working to a Single Forecast • Common Measures • Planning • Information Sharing Internal processes Viswanathan, R., “Systematic Collaboration in the Supply Chain Planning, Forecasting, and Replenishment,” available online from http://www.ise.ufl.edu/Supplychain/done/Day1/Viswanathan/Viswanathan.ppt

4. Internal Processes Willing to share information Able to share information

5. Willing to share information • Trust – Fear that information (e.g., end-customer demand, upcoming promotions, and sales forecasts) may leak, or be used against them. • Power – Knowledge is power. Access information (e.g., end-customer demand), gives one power in the supply chain – making this information available to others could lessen this power. • Able to share information • Trading partners may have difficulties sharing information because their internal processes do not correspond and, in some cases, cannot produce the necessary data. For example, several grocery retailers find it impossible to produce item level forecasts for all of their tens of thousands of products, which obviously forms a significant obstacle for CPFR type collaboration. Collaborative Forecasting (Henry C. Co)

6. Joint Processes Scalability Interoperability

7. Scalability • Support for many trading partners, involving large numbers of products • Interoperability • Common standards Collaborative Forecasting (Henry C. Co)

8. Scalability • Small-scale pilots may not work be scalable. Nabisco, for example, admits that it still does not have a scalable enough solution despite being one of the early companies to start CPFR piloting (Frantz, 2000). • Scalability, i.e. support for several users, rapid implementation and easy integration with different types of existing systems, need to be required of collaborative processes and supporting tools. • Common standards • Lack of common standards for sharing the type of information needed for CPFR is today slowing the development down (Angeles, 2000). Collaborative Forecasting (Henry C. Co)

9. Technology Control and Security Scalability Standardization

10. Technological Infrastructure Requirements • Control and security – should be able to control what information is shared, with whom and be able to rely on the security of the information sharing. • Scalability – must support collaboration with many large or small trading partners, and many products; should offer easy integration with different types of existing systems. • Standardization – should use open standards in order to allow the network to expand rapidly. Collaborative Forecasting (Henry C. Co)

11. Centralized vs. Decentralized Solutions Centralized – Electronic Marketplace Decentralized – Peer-to-peer information systems http://www.cs.hut.fi/~framling/Publications/LRN2001.pdf

12. Electronic Marketplace, a.k.a. Exchanges Order matching Requisition and routing approvals Financial settlement of orders Content management Logistics fulfillment services CPFR activities.

13. Exchanges’ Services • Order matching • Catalogue orders –Fix-priced catalogue items • Dynamic pricing – the marketplace matches orders real-time based on bids and quotes that come into the marketplace • Auctioning • Request for proposals – detailed specifications are put online and bids are consolidated and compared. • Requisition and routing approvals – requests are routed to the right manager for approval. • Financial settlement of orders Collaborative Forecasting (Henry C. Co)

14. Content management – e.g., converting and maintaining catalogue information. • Logistics fulfillment services. • CPFR capabilities – forthcoming. Morgan Stanley Dean Witter (2000), The B2B Internet Report. Collaborative Commerce. Collaborative Forecasting (Henry C. Co)

15. CPG Industry Exchanges • New in CPG (2000). • Founded by supplier • Transora (www.transora.com) • CPGmarket.com (www.CPGmarket.com) • Founded by retailers • WorldWide Retail Exchange (www.worldwideretailexchange.org) • GeneralNetXchange (www.gnx.com) Collaborative Forecasting (Henry C. Co)

16. Advantages • Efficient matching of demand and supply – Easier to involve many (even anonymous) players in the trading process. • Expands customers base; lowers barriers for sellers to participate in bidding. • Expands supplier base; allows buyers to get better price. • Only investment is the communication link to the exchanges – Low entry barrier (allows small players to participate in CPFR). • ONE link (to the exchange), rather than several links to several trading partners. • Standardization – Exchanges impose communication standards (open or proprietary). • Value-added services – translation services when trading partners use different message formats. Collaborative Forecasting (Henry C. Co)

17. Disadvantages • Reduced control – once information is uploaded to the exchanges, must rely on the exchange to deliver it to the right recipient (and only the right recipient); • Power – Exchanges are likely develop features and capabilities to cater to the needs of large customers; • Exchanges offer standardized solutions, companies have different needs in collaboration. • Transaction and service fees. Collaborative Forecasting (Henry C. Co)

18. Disadvantages • Information has to be explicitly communicated to the administrator of the marketplace, thus making it more difficult to keep catalog information (product info, prices) up to date. Collaborative Forecasting (Henry C. Co)

19. Peer-to-Peer System Instead of passing through centralized databases and servers, data is exchanged directly between systems. No need for a 3rd party for setting-up and governing the network.

20. RETAILER MANUFACTURER Item Table Item Table Internet Inter- face Inter- face APPLICATION APPLICATION Shared Data Forecast Table Forecast Table Promotions Table Promotions Table ITEMNUMBER 1234567890001 1234567890002 1234567890003… RTLR’SFORECAST 1200 14000 330 MFR..FORECAST 1150 9000 350 DELTA 50 5000 20 TOLERANCE 100 2000 50 OK? ü û ü Shared Process and Data Model Viswanathan, R., “Systematic Collaboration in the Supply Chain Planning, Forecasting, and Replenishment,” available online from http://www.ise.ufl.edu/Supplychain/done/Day1/Viswanathan/Viswanathan.ppt

21. Backend Server Apps Backend Server Apps Data Data Peer to Peer Scenario Architecture Workstation Manufacturer Retailer Workstation SMTP S/MIME, SIL CPFR Server www.supplier.cpfr.com CPFR Server www.retailer.cpfr.com Viswanathan, R., “Systematic Collaboration in the Supply Chain Planning, Forecasting, and Replenishment,” available online from http://www.ise.ufl.edu/Supplychain/done/Day1/Viswanathan/Viswanathan.ppt

22. Example of Retailer-Supplier Setup • Supplier configures three connections to access forecast data from three retailers • Each retailer configures the connection to the supplier, permitting the supplier access to their forecasting information. http://www.cs.hut.fi/~framling/Publications/LRN2001.pdf Collaborative Forecasting (Henry C. Co)

23. Information Sharing Connections • Connections set up by mutual agreement; configure what database to use, setup the database tables, and eventually add new database users with appropriate access rights. • Three pieces of information • Identifier of the partner • Internet address of the partner computer to connect to/receive connections from • Public RSA encryption key that uniquely identifies and authenticates the partner. See PowerPoint on Cryptography http://www.cs.hut.fi/~framling/Publications/LRN2001.pdf Collaborative Forecasting (Henry C. Co)

24. Advantages and Disadvantages • Advantages • Control and power • No need for a 3rd party for setting-up and governing the network. • All parties have equal status regardless of their size and can independently choose how to collaborate with other network parties. • Scalability • Network setup as needed; no limit on number of parties, products or product groups. • Up-to-date information • No participation fees • Disadvantage: Slow standardization Collaborative Forecasting (Henry C. Co)

25. CPFR Interoperability In Peer-to-Peer Collaboration, trading partners use CPFR applications

26. A Client-Server Architecture Sun Ultra Netscape LiveWire Informix 7.2 EnterpriseServer 3.0 Web Browser HTTP Server Client Viswanathan, R., “Systematic Collaboration in the Supply Chain Planning, Forecasting, and Replenishment,” available online from http://www.ise.ufl.edu/Supplychain/done/Day1/Viswanathan/Viswanathan.ppt

27. Prototype Process/Functionality • Authenticates users • Stores exceptions data • Allows selective retrieval of data • Displays time-variant data such as supplier forecast, retailer forecast, POS for 52 weeks • Displays detail time-invariant data such as On-hand, Fill-rate, store information etc for a specific forecast • Displays information in both tabular and graphical form • Displays calendar of events for both sides, for each item

28. Shows how a level 1 (corporate) forecast can be drilled down to DC and store levels • Shows how a forecast update can take place interactively • Shows how messages associated with an exception can be created, stored and sent.

29. Next Steps for CPFR and the industry • Refinement and publication of process models • Define/establish prerequisite EDI feeds if non-existent • Define/establish other feeds (manual initially) - forecast drivers (promotions, price changes, replenishment strategies etc) • Define/establish business rules for exception generation • Develop exception processes based on forecast comparisons • Define/establish procedures for use of CPFR system • Develop measurements/business cases • Refine technology infrastructure • Introduce security - S/HTTP and/or S/MIME • Investigate use of open data model

30. Challenges • Organizational readiness • Process confirmation • Integration of supply chain collaboration tools with backend applications • data models • architecture (hub-hub, hub-spoke, hub-web) • Change management

31. Capabilities Assessment • Process Readiness • Forecasting and Replenishment • Scorecard Solution • Change Management • Inter & Intra organization communication channel readiness • Technology Readiness • Data availability • Internet Enablement • Electronic Commerce

32. SAP APO Collaborative Planning (CP) and CPFR APO is the acronym for Advanced Planner and Optimizer

33. ERP • ERP breaks functional silos within the 4 walls of an enterprise • Integrates • Streamlines … Intraorganization Processes “One number for business planning across all departments” • Next step • Streamlines • Collaborates … Interorganization Processes “One number for supply planning across the entire supply chain.” Collaborative Forecasting (Henry C. Co)

34. ERP promises concurrent, real time planning, information sharing and value added services for intraorganization processes. • Next step – collaborative commerce to break division barriers separating the distinct links in the supply chain: procurement companies, production companies, … low inventory levels, high inventory turns, improved cash flow … drastic reduction of the dreaded bullwhip effect. Collaborative Forecasting (Henry C. Co)

35. Before Internet • Businesses exchange information by • Meetings • Phone • Mail (slow) • Fax • EDI (costly and rigid) • The Internet enable businesses to establish low cost, secure, scalable, and dynamic collaborative commerce. Collaborative Forecasting (Henry C. Co)

36. SAP APO Collaborative Planning • Exchange planning information • Browse and update data via a browser • Multiple partner access, but restricting access to authorized data and activities • Consensus planning process • Exception-based management • One number for supply planning across the entire supply chain. Collaborative Forecasting (Henry C. Co)

37. Internet-Based Functionalities • Consensus-based forecasting • CPFR compliant collaborative forecasting • Vendor managed inventory • Supplier collaboration. Collaborative Forecasting (Henry C. Co)

38. SAP APO CP Functionality 1 Consensus-Based Forecasting

39. Pyramid Forecasting • SAP APO Demand Planning allows you to create plans for different business goals (strategic business plan, tactical sales plan, operational supply chain plan, etc.) and integrates them into one consensus plan that drives your business. • Joint Business Planning Across Supply Chain using SAP APO CP’s tools • Planning Books (Internet-compatible demand planning/supply network planning books in SAP) • Enhanced Macros Collaborative Forecasting (Henry C. Co)

40. Pyramid Forecasting • Parties Involved • Central planning department which creates a consolidated forecast for ALL products • Key account manager who creates a forecast for a specific retailer or wholesaler • Sales department which forecasts its own demand • Each party bases its forecast on specific information. • GOAL – to consolidate the various forecasts into a common time series to be used for planning. Collaborative Forecasting (Henry C. Co)

41. Pyramid Forecasting Process • Department-specific forecasts • Sales • For a combination of product and customer • Goals are tactical – maximize sales • Focus on promotions, orders, POS data, competitive info, customer info. • Logistics • For a combination of product/item and location • Goals are operational – minimize costs, fulfill orders • Focus on shipments, material and capacity constraints. Collaborative Forecasting (Henry C. Co)

42. Marketing • For a combination of product family/market zone • Goals are strategic – increase demand, reduce stock • Focus on promotions and events, causal relationships, and syndicated POS data. Collaborative Forecasting (Henry C. Co)

43. Team meeting held to reach consensus • Manual adjustments made • Accuracy of forecast checked against sales data. • SAP APO CP allows access to SAP APO Planning books through an Internet browser. • Trading partners can view each other’s forecasts, make changes and agree on a consensus-based forecast. Collaborative Forecasting (Henry C. Co)

44. SAP APO Functionality 2 Collaborative Planning, Forecasting and Replenishment (CPFR®)

45. The CPFR® Reference Model • 8 collaboration tasks form an iterative cycle of 4 activities: • Strategy & Planning • Demand & Supply Management • Execution • Analysis. • Each activity consists of two collaboration tasks. Collaborative Forecasting (Henry C. Co)

46. CPFR in SAP APO Collaborative Planning Collaborative Forecasting (Henry C. Co)

47. Collaborative Forecasting (Henry C. Co)

48. SAP APO Collaborative Demand Planning

49. SAP APO CP Functionality 3 VMI over the Internet

50. Vendor-Managed Inventory • Supplier takes the task of requirements planning for its own products within the retail company. • Supplier monitors the buyer’s inventory levels, physically or via electronic messaging. • Supplier decides on when and how much to replenish inventory. • Supplier sends an advance shipping notice to inform the buyer of materials in transit. Collaborative Forecasting (Henry C. Co)