The CPFR ® Reference Model by iqm86975

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									The CPFR® Reference Model


Henry C. Co
Technology and Operations Management,
California Polytechnic and State University
The Need for a Standard Process Model
   CPFR is being implemented at thousands of
    companies across the globe.
   Many companies, such as GSK, are
    implementing CPFR with multiple retailers
   A standard vision is needed to provide a
    common understanding of:
        Terminology and definitions
        The steps needed to implement CPFR
        Data and information system requirements
   Best practices


    http://scm.ncsu.edu/public/cpfr/ last accessed 23 April 2007.

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The VICS CPFR® Guidelines


http://www.gmabrands.com/industryaffairs/docs/cpfr.pdf
http://www.cpfr.org/Guidelines.html
The VICS CPFR® Guidelines
   Voluntary guidelines aimed at structuring
    and guiding supply chain partners in setting
    up their relationship and processes.
       Shared plans
       Exception identification
       Resolution


   Allows visibility to trading partners’
       Critical demand
       Order forecasts
       Promotional forecasts.



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   In 2004, VICS revised the 9-step
    CPFR® reference model (see
    diagram). At the center of the model
    is the consumer. The circling arrows
    between the retailer ring and the
    manufacturing ring show the eight
    CPFR® collaboration tasks.
    Collaboration tasks are not
    numbered. No predetermined
    sequence is implied.


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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.




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CPFR® Is Consumer-Centric
   Consumer
       At the center of the model.
       Retailers, manufacturers and
        suppliers work together to satisfy the
        demand of the end consumer.
   The circling arrows between the
    retailer ring and the manufacturing
    ring show the eight CPFR®
    collaboration tasks.
       Collaboration tasks are NOT numbered;
        NO predetermined sequence is implied.

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CPFR: Key Tenets
   The consumer is the ultimate focus of all
    efforts
   Buyers‖ (retailers) and ―sellers‖
    (manufacturers) collaborate at every level
   Joint forecasting and order planning reduces
    surprises in the supply chain
   The timing and quantity of physical flows is
    synchronized across all parties
   Promotions no longer serve as disturbances
    in the supply chain
   Exception management is systemized
    http://scm.ncsu.edu/public/cpfr/ last accessed 23 April 2007.

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Collaboration Tasks Under CPFR®




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1. Strategy & Planning


         Establish the ground rules for the
         collaborative relationship.
         Determine product mix and
         placement, and develop event plans
         for the period.
1.1 Collaboration Arrangement
   Setting the business goals and
    defining the scope for the relationship
   Assigning roles, responsibilities,
    checkpoints and escalation procedures
       Participating companies identify executive
        sponsors, agree to confidentiality and
        dispute resolution processes.
       Develop a scorecard to track key supply
        chain metrics relative to success criteria,
        and establish any financial incentives or
        penalties.


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   Outcome – Memorandum of
    understanding
       Defines the process in practical terms.
       Identifies the roles of each trading
        partner and how the performance of each
        will be measured.
       Spells out the readiness of each
        organization and the opportunities
        available to maximize the benefits from
        their relationship.
       Formalizes each party’s commitment and
        willingness to exchange knowledge and
        share in the risk.

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1.2 Joint Business Plan
   Trading partners exchange information
    on corporate strategies and business
    plans to develop a joint business plan.
   Identifies the significant events that
    affect supply and demand, such as
    promotions, inventory policy changes,
    store openings / closings, and product
    introductions.




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   Outcome –A mutually agreed upon
    joint business plan
       Joint calendar for promotions, inventory
        policy changes, store openings/closings,
        and product changes for each product
        category, etc.
       Clearly identifies the roles, strategies, and
        tactics for the SKUs that are to be brought
        under the umbrella of CPFR.
       Cornerstone of the forecasting process.



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2. Demand & Supply
   Management

        Sales forecasting:
        Projects demand at the point of sale

        Order planning/forecasting:
        (a) Determines future product order & delivery
            requirements based upon the sales forecast.
        (b) Takes into account inventory positions, transit
            lead times, shipment quantities, and other factors.
2-1 Sales Forecasting Overview
   Consumption data is used to create a
    sales forecast.
   This consumption data differs
    depending on the product, industry,
    and trading partners:
        Retailer POS data
        Distribution center withdrawals
        Manufacturer consumption data
   Important to incorporate information
    on any planned events (ex. –
    Promotions, plant shut downs, etc.)
    http://scm.ncsu.edu/public/cpfr/ last accessed 23 April 2007.

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Sales Forecasting Steps
1.   Analyze current joint business plan
        Analyze the potential effects of the
         current joint business plan on future
         retail sales
2.   Analyze causal information
        Analyze the potential effect of causal
         factors on future retail sales based on
         historical events and the resulting sales
         impact
3.   Collect and analyze consumption data
        Point-of-Sale (PoS) data, warehouse
         withdrawals, manufacturing consumption


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4.   Identify planned events
        Store openings or closings, promotions,
         or new product introductions
        This comprehensive list of events will be
         used to populate a shared-event
         calendar
5.   Update shared event calendar
        Align events from each trading partner,
         resulting in a common plan
        Agree upon this short-term event plan



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6.     Gather exception resolution data
          Gather sales forecast exception
           resolution data from previous iterations
7.     Generate sales forecast
          Generate the forecast for a given period
           with forecasting tools that use all
           relevant information and guidelines.
           Either partner or both partners may
           generate the sales forecast, depending
           upon the scenario


     http://scm.ncsu.edu/public/cpfr/ last accessed 23 April 2007.

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Output
   Single sales forecast generated by one
    or both parties
   Used as a baseline for the creation of
    an order forecast, as well as other
    supply chain activities.




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2-2 Order Planning/Forecasting Overview
   Sales forecast, causal information,
    inventory policies, etc. are used to
    generate a specific order forecast.
   Actual volume numbers are time-
    phased and reflect inventory
    objectives by product and receiving
    location.
   The short-term portion of the forecast
    is used for order generation.
   The longer-term portion is used for
    planning.

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How Sales Forecasts Drive Order Forecasts
   Using POS forecast and inventory policy information, we
    can calculate when each store needs to release an order to
    the Retailer DC …
    Example:




   ...and this information is then used to generate a
    replenishment forecast for the DC.
    http://scm.ncsu.edu/public/cpfr/ last accessed 23 April 2007.

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   The same process can be used to develop an order
    forecast for the manufacturer.




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Output: Time-phased, netted order forecast
   The order forecast allows the seller to
    allocate production capacity against demand
    while minimizing safety stock.
   The real-time collaboration reduces
    uncertainty between trading partners and
    leads to consolidated supply chain
    inventories.
   Inventory levels are decreased, and
    customer service responsiveness is
    increased. A platform for continual
    improvement among trading partners is
    established.

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Execution

            Place orders, prepare and deliver shipments, receive
            and stock product on retail shelves, record sales
            transactions and make payments.
            Order generation— Transitions order forecasts into
            firm demand
            Order fulfillment — Producing, shipping, delivering,
            and stocking the products
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Order Generation Output
   Committed orders by the buying
    organization (the retailer) and delivery
    shipments from the vendor.
       The buyer receives and stocks products,
        records sales transactions, sends order
        acknowledgment and makes payments.
   Buyer and seller agree on a ―time
    fence‖ where forecasts are frozen.
       Near-term orders are fixed; Long-term
        ones are used for planning.



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4. Analysis


         Monitor planning and execution activities for
         exception conditions.
         Aggregate results, and calculate key
         performance metrics.
         Share insights and adjust plans for
         continuously improved results.
Performance assessment
   Trading partners calculate key performance
    metrics (e.g., in-stock level, forecast
    accuracy targets, etc.)
       To evaluate achievement of business goals,
        uncover trends, or develop alternative strategies;
       To share insights and adjust plans for continuous
        improvement.
   Generate and agree to a list of exception
    items for your CPFR initiative.
       Develop a process to resolve sales forecast
        exceptions.




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Exception management
   Monitor plan vs. execution to identify
    deviations and exceptions.
       Trading partners resolve exceptions by
        determining causal factors, adjusting
        plans where necessary.
       Forecast accuracy problems,
        overstock/stock-out conditions, and
        execution issues must be identified and
        resolved in a timely manner.




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4-1 Performance Assessment Overview
   Performance assessment is essential to any
    understanding of collaboration benefits.
   The specific measures can vary from one
    situation to the next, but generally fall into
    two categories:
       Operational measures: fill rates, service levels,
        forecast accuracy, lead times, inventory turns,
        etc.
       Financial measures: Costs, item and category
        profitability, etc.
   In reality, partners are often reluctant to
    share financial measures and estimates of
    ―profitability‖ can vary widely, depending on
    how one defines and assigns costs.

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4-2 Exception Management Overview
   Exceptions need to be handled in both
    sales forecasts and order forecasts.
   The exception criteria are agreed to in
    the collaboration arrangement.
   Sales and order forecast exceptions
    are resolved by querying shared data,
    email, telephone conversations,
    meetings, and so on, and submitting
    any resulting changes to the
    appropriate forecast.

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Identify forecast exceptions




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1.   Retrieve exception criteria – Retrieve the sales/order
     forecast exception criteria (e.g., retail in stock
     percent or measures such as forecast accuracy)
2.   Identify changes/updates – Identify seller or buyer
     changes or updates to the joint business plan (e.g.,
     a change in the number of stores)
3.   Compare item values against exception criteria –
     Compare each item’s value for the selected criteria
     to the constraint value (e.g., store in-stock for item
     X is 83% versus the criteria value of 90%
4.   Identify exception items – Identify items as
     exception items if their values fall outside the
     constraints




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Resolve the exceptions




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1.   Retrieve exception items and decision support data
     (e.g., historical sales, in-stock percent).
2.   Select desired exception criteria/values (e.g., ―all
     items with a store in-stock percent less than 90
     percent‖)
3.   Research exceptions – Use the shared-event
     calendar and supporting information to look for
     cause
4.   Heighten collaboration – If research does not yield
     satisfactory forecast changes or resolve the
     exception, then either partner can heighten the
     collaboration
5.   Submit changes to sales/order forecast – If research
     changes the forecast and/or resolves the exception,
     submit the change to the sales/order forecast


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Exception Management Output
   List of exceptions in the sales and
    order forecasts.
   Resolution of identified exceptions.
   Adjusted forecast.




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