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					CPFR® Technology


Henry C. Co
Technology and Operations Management,
California Polytechnic and State University
      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
                                                                                      Scalability through collaborative
                                                                                      processes that are flexible, fast to
                                                             Joint                    implement and easy to integrate.

                                                           processes
Technology for secure, reliable
and cost-effective information                                                                Internal processes that produce
sharing and communication.                                                                    and use collaborative
                                                                                              information.
   Open System                                                                                      Working to a Single
   Internet                                                                                           Forecast
   Application                                                                                      Common Measures
    Development Methods                                                                              Planning
   Secure Communication                                                                             Information Sharing
                                       Technology                           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
Internal Processes


Willing to share information
Able to share information
   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)     5
Joint Processes


Scalability
Interoperability
   Scalability
       Support for many trading partners,
        involving large numbers of products


   Interoperability
       Common standards




             Collaborative Forecasting (Henry C. Co)   7
   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)    8
Technology


Control and Security
Scalability
Standardization
Technological Infrastructure Requirements
1.   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.
2.   Scalability – must support collaboration
     with many large or small trading partners,
     and many products; should offer easy
     integration with different types of existing
     systems.
3.   Standardization – should use open
     standards in order to allow the network to
     expand rapidly.

            Collaborative Forecasting (Henry C. Co)   10
Centralized vs. Decentralized
Solutions


Centralized – Electronic Marketplace
Decentralized – Peer-to-peer information systems




             http://www.cs.hut.fi/~framling/Publications/LRN2001.pdf
Electronic Marketplace, a.k.a.
Exchanges

  1.   Order matching
  2.   Requisition and routing approvals
  3.   Financial settlement of orders
  4.   Content management
  5.   Logistics fulfillment services
  6.   CPFR activities.
Exchanges’ Services
1.   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.
2.   Requisition and routing approvals –
     requests are routed to the right manager
     for approval.
3.   Financial settlement of orders


              Collaborative Forecasting (Henry C. Co)   13
4.   Content management – e.g., converting
     and maintaining catalogue information.
5.   Logistics fulfillment services.


    CPFR capabilities – forthcoming.




     Morgan Stanley Dean Witter (2000), The B2B Internet Report. Collaborative Commerce.


                  Collaborative Forecasting (Henry C. Co)                              14
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)   15
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)       16
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)   17
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)   18
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.
              Shared Process and Data Model

    RETAILER                                                                                              MANUFACTURER



                 Item                                                                                         Item
                                                               Internet




                                                                                                                         APPLICATION
APPLICATION




                 Table                                                                                        Table




                                    Inter-                     Shared                      Inter-
                Forecast                                                                                     Forecast
                                    face                        Data                       face
                 Table                                                                                        Table




              Promotions                                                                                   Promotions
                 Table                                                                                        Table
                                     ITEM          RTLR’S      MFR..      DELTA   TOLERANCE         OK?
                                    NUMBER        FORECAST   FORECAST

                                  1234567890001     1200       1150        50        100            
                                  1234567890002     14000      9000       5000      2000             
                                  1234567890003     330        350         20        50             
                                        …



              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
          Peer to Peer Scenario Architecture


     Workstation                                                                                          Retailer
     Manufacturer                                                                                         Workstation


    CPFR Server                                         SMTP                                             CPFR Server
www.supplier.cpfr.com                                S/MIME, SIL                                       www.retailer.cpfr.com




Backend Server Apps                                                                                Backend Server Apps
                                             Data                          Data

          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
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)                    22
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)                    23
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)     24
CPFR Interoperability


In Peer-to-Peer Collaboration, trading partners use CPFR
applications
A Client-Server Architecture



                         Sun Ultra
    Netscape
                                             Enterprise                                 Web
    LiveWire
                                             Server 3.0                                Browser
    Informix 7.2

                                                                        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
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
   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.
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
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
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
SAP APO Collaborative
Planning (CP) and CPFR


APO is the acronym for Advanced Planner and Optimizer
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)     33
   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)   34
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)   35
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)   36
Internet-Based Functionalities
1.   Consensus-based forecasting
2.   CPFR compliant collaborative
     forecasting
3.   Vendor managed inventory
4.   Supplier collaboration.




          Collaborative Forecasting (Henry C. Co)   37
SAP APO CP Functionality 1


Consensus-Based Forecasting
   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)    39
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)   40
Pyramid Forecasting Process
1.   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)   41
   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)   42
2.   Team meeting held to reach consensus
3.   Manual adjustments made
4.   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)   43
SAP APO Functionality 2


Collaborative Planning, Forecasting and Replenishment
(CPFR®)
The CPFR® Reference Model

                                         8 collaboration tasks
                                         form an iterative cycle
                                         of 4 activities:

                                          A. Strategy & Planning
                                          B. Demand & Supply
                                             Management
                                          C. Execution
                                          D. Analysis.

                                         Each activity consists of
                                         two collaboration tasks.




       Collaborative Forecasting (Henry C. Co)                     45
CPFR in SAP APO Collaborative Planning




        Collaborative Forecasting (Henry C. Co)   46
Collaborative Forecasting (Henry C. Co)   47
SAP APO Collaborative Demand Planning
SAP APO CP Functionality 3


VMI over the Internet
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)   50
SAP APO CP Enables VMI over Internet
   VMI requires supplier to be able to track the
    amount of its products stocked at the retailer side,
    and access to the retailer’s sales forecasts.
   SAP APO CP enables VMI over the Internet
       Internet planning book allows users to access the
        Supply Network Planning data
       Business Connector allows users to transmit VMI data
        from SAP APO Collaborative Planning to partners’
        systems that can receive and process XML messages.
   VMI over the Internet
       Affordable – small retailers can participate in supply
        chain planning.
       Allows retailer to maintain control over the data it is
        sending to the supplier and change it if necessary.




                Collaborative Forecasting (Henry C. Co)           51
   SAP APO Business Connector
       The Business Connector translates EDI messages to XML
        messages that can be transmitted over the Internet.
       Retailer can transmit, via the Business Connector, VMI
        data from SAP APO Collaborative Planning to suppliers’
        systems.
       Partners’ systems must have the capability to receive and
        process XML messages
   Making VMI possible via Internet provides small
    retailers with an
   economical alternative to participating in supply chain
    planning. It also allows the retailer to maintain control
    over the data it is sending to the supplier and change it
    if necessary.
   To achieve their goals, participants will be able to
    access the Supply Network Planning data through
    Internet planning books.


               Collaborative Forecasting (Henry C. Co)         52
SAP APO CP Functionality 4


Supplier Collaboration
   EDI in automotive industry
       Suppliers connected to auto
        manufacturers by EDI;
       Exchange dependent requirements (MRP)
       Requires large investments.
   The Web
       Low cost
       Allows smaller companies to participate
       The only requirement is that partners’
        systems must have the capability to
        receive and process XML messages.

             Collaborative Forecasting (Henry C. Co)   54
SAP APO Collaborative Planning
   The dependent requirements in Supply Network
    Planning are displayed in supplier specific planning
    books.
       A supplier can have access to those aspects of the
        planning situation that affect him/her.
       Users can have access to production plans as well as
        dependent requirements.
       Internet enabled planning books allow users to have an
        interactive role; for example, if the delivery of the
        dependent requirements cannot be made in time, an
        alternative date can be suggested.
   Using the Business Connector, SAP APO Collaborative
    Planning can directly communicate with partners’
    system using XML messages over the Internet.
       Allows system-to-system communication enabling users
        to be involved only in exception situations.
       Thus, SAP APO Collaborative Planning enables
        synchronized planning across business partners.


               Collaborative Forecasting (Henry C. Co)      55

				
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