The CPFR Reference Model

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The CPFR Reference Model

• Henry C. Co
• Technology and Operations Management,
• California Polytechnic and State University

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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

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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
• Strategy Planning
• Demand Supply Management
• Execution
• 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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Strategy Planning

• Establish the ground rules for the collaborative
  relationship.
• Determine product mix and placement, and develop
  event plans for the period.

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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 partys 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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Demand Supply Management

• Sales forecasting
• Projects demand at the point of sale
• Order planning/forecasting
• Determines future product order delivery
  requirements based upon the sales forecast.
• Takes into account inventory positions, transit
  lead times, shipment quantities, and other
  factors.

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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

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

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• 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
• 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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• Gather exception resolution data
• Gather sales forecast exception resolution data
  from previous iterations
• 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
• ...and this information is then used to generate
  a replenishment forecast for the DC.

Example
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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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.

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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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• Retrieve exception criteria Retrieve the
  sales/order forecast exception criteria (e.g.,
  retail in stock percent or measures such as
  forecast accuracy)
• Identify changes/updates Identify seller or
  buyer changes or updates to the joint business
  plan (e.g., a change in the number of stores)
• Compare item values against exception criteria
  Compare each items 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
• 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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• Retrieve exception items and decision support
  data (e.g., historical sales, in-stock percent).
• Select desired exception criteria/values (e.g.,
  all items with a store in-stock percent less
  than 90 percent)
• Research exceptions Use the shared-event
  calendar and supporting information to look for
  cause
• Heighten collaboration If research does not
  yield satisfactory forecast changes or resolve
  the exception, then either partner can heighten
  the collaboration
• 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.