Distribution Center
Replenishment
Collaboration
Business Process Guide
February 2, 2005
Abstract
Distribution Center Replenishment Collaboration has been the most common starting
point for trading partners working together to improve the replenishment and
forecasting processes between their organizations. Executed within the framework of
Collaborative Planning, Forecasting and Replenishment (CPFR®), suppliers and buyers
work together to optimize the flow of inventory into the retail distribution center and
out to the store network. Trading partners collaborate to improve the accuracy of DC
to Store and Supplier to Retail DC forecasts, calculate optimal inventory levels, and
maximize transportation and operational efficiencies. The objective of these initiatives
is to attain targeted service levels to the store network in a way that maximizes
profitability.
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Copyright © 2004
Uniform Code Council, Inc. And Voluntary Interindustry Commerce Standards (VICS) Association
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
2
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Revision History.............................................................................................................................. 4
Acknowledgements ......................................................................................................................... 4
Introduction ..................................................................................................................................... 5
Business Case.............................................................................................................................. 6
Implementation Scenarios........................................................................................................... 8
Process Overview........................................................................................................................ 9
Collaboration Roles and Responsibilities ................................................................................. 11
Information Sharing Requirements ........................................................................................... 11
Collaborative Strategy and Planning Process................................................................................ 12
Collaboration Arrangement....................................................................................................... 12
Joint Business Planning ............................................................................................................ 14
Collaborative DC Forecasting Process .......................................................................................... 15
Data Granularity........................................................................................................................ 15
Collaborative Forecast Elements .............................................................................................. 15
Single Node Planning versus Multi-Echelon Planning ............................................................. 16
RosettaNet Order Planning Approach ........................................................................................... 21
Collaborative DC Ordering and Fulfillment Process .................................................................... 22
Order Release............................................................................................................................ 22
Sales and Operations Planning (S&OP).................................................................................... 23
S&OP Linkage to CPFR ........................................................................................................... 24
Collaborative Analysis Process ..................................................................................................... 25
Exception Management............................................................................................................. 26
Performance Assessment .......................................................................................................... 29
Data Interchange Requirements ................................................................................................ 30
Example Process ....................................................................................................................... 31
Appendix A: Collaboration Arrangement w/ Commitment Processing ........................................ 34
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
3
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Revision History
Revision
Date
Changes
0.1
30-Sept-2004
- Initial draft
0.2
03-Oct-2004
- Removed Collaborative Arrangement sample that is found in store
replenishment guide. Edits made to improve readability.
0.3
13-Oct-2004
-
-
Incorporated miscellaneous suggestions from October CPFR
Subcommittee meeting. Retailer/Manufacturing terminology changes
to Buyer/Supplier.
RMR changed to BMR. VMR changed to SMR.
Additional sales to order translation variables added.
Additional forecast collaboration elements added.
Additional replenishment collaboration elements added.
.4
10-Oct-2004
- Incorporated the order commitment processes of RosettaNet
Public
Review
23-Nov-2004
- Enhanced the collaborative arrangement
- Inserted acknowledgements
- Moved high-level discussion of information sharing requirements to the front
of the document
- Incorporated additional committee member comments
Acknowledgements
This document is the result of the combined efforts of the VICS CPFR Committee DC
Replenishment Collaboration Task Team and the EAN.UCC Plan BRG. Authors, editors and
reviewers include the following:
o
o
o
o
o
o
o
o
o
Bill Connell, Federated Department
Stores
Chuck Rehlin, JCPenney
Darlene Goren, HBC
David Ferrell, Wal-Mart
Dennis Embree, Nike
Fred Baumann, JDA Software (Editor)
Gale Weisenfeld, Federated Department
Stores
Hank Steerman, Collaborative Retail
Solutions
Jack Harwell, Radio Shack
o
o
o
o
o
o
o
o
o
o
o
Jean Schenck, Microsoft
Jim Lovejoy, TC2
Jim McLaughlin, Gillette
John Dredge, JDA Software
Larry Roth, Kimberly-Clark
Matt Johnson, Retek
Murray Pratt, Kraft Foods
Pam Sweeney, Federated Department
Stores
Patty Jackson, SC Johnson
Rich Richardson, Uniform Code Council
Ron Ireland, Oliver-Wight Associates
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
4
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Introduction
The Collaborative Planning, Forecasting and Replenishment Process (CPFR) has moved from
being a conceptual idea to a business process that is now integrated into the core building blocks of
the buyer and supplier business operations. Over the last several years, case study after case study
has shown that trading partners engaged in CPFR will derive distinct and measurable value in topline sales, administrative and operating efficiencies, and working capital improvements. Many of the
early implementations of CPFR focused on the demand-based steps of the CPFR business model
(Collaborative Arrangement, Joint Business Plan, and Sales Forecasting) and delivered significant
results. Other trading partners are building on this foundation to collaborate on the replenishment
steps of the business model resulting in significant incremental improvements to their businesses.
Traditional replenishment focuses on just two nodes in the supply chain. The most common focus is
the node between the buyer’s distribution center and the suppliers finished goods warehouse. CPFR
seeks to tightly couple the replenishment activities from store take-away to raw materials
procurement. In addition, traditional replenishment typically provides orders that are one lead-time
away. There is not an extended planning transition period over a planning horizon where order
forecasts can be viewed with a time fence philosophy where order forecasts become orders. The
outcome of these traditional trading practices has been the creation of pools of “extra” inventory
over the supply chain that “hopefully” will be consumed by future orders. Moving to CPFR based
replenishment requires a fundamental change in the ways trading partners interact over the order.
Trading partners are looking for direction and insights to drive benefits to their respective businesses.
To facilitate some of these benefits, buyers and distributors are now asking suppliers to share
responsibility for the distribution center (DC)-level availability of products via DC replenishment
collaboration initiatives. Within these initiatives, trading partners leverage their collective insights to
ensure that the forecast for Retail DC demand and the replenishment parameters associated with the
creation of orders are as accurate as possible so that service levels are maximized for DC–level
availability with the lowest cost investment possible.
The theory of DC replenishment collaboration is sound. Leveraging the insights of both the buyer
and supplier to drive optimal promotional and replenishment plans will result in higher sales with
lower supply chain investments. Suppliers often have insights on seasonality and regionality on their
products that their retail trading partners may lack. Buyers and distributors have unique insights on
planned merchandising activities and supply network changes that will impact forecasts and future
orders. The supplier and buyer then consider other collaboration points that influence replenishment,
such as:
•
•
•
•
•
•
•
•
•
DC to Store and Supplier to Retail DC Forecasts
Supplier truckload brackets
Order cycles
On-hand inventories
In-transit inventories
Order multiples (Pallet, Truckload, Container, etc.)
Lead times
Seasonal and promotional pre-builds to maximize store availability
Targeted service levels/safety stock
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
5
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
The result of DC replenishment collaboration is an order or series of orders that are committed over
a time horizon. The buyer and seller embrace order generation with their replenishment
planning/buying/re-buying and production and supply planning organizations respectively.
DC replenishment collaboration offers many benefits, but it also requires changes in supplier/buyer
roles, responsibilities, skills requirements, information interchange and technology. The level of
complexity and sku/loc volume for DC collaborative replenishment is not as multifaceted as
collaborative store replenishment and may enable trading partners to begin the process with a lower
investment in resource. This business process guide is intended to assist buyers and suppliers who are
planning or executing DC-level initiatives. The objective is to create a common vocabulary and
industry guidelines that will accelerate implementation and enhance benefits.
Business Case
Current Process State
The majority of consumer products carried in large retail chains are first delivered to the buyer’s
distribution centers, and then distributed from there to individual stores. Exceptions are direct store
delivery (DSD) products, such as baked goods, beverages and many snack foods in grocery stores, or
high-end products in consumer electronics stores. These are often shipped straight to stores from the
supplier, or the supplier’s distributor, bypassing the retailers stores. The figure below highlights the
blind spots in the traditional DC replenishment approach.
Limited Collaboration
Order
1.
2.
Buyer
Baseline plus
“Just – In-Case” Inventory
Baseline plus
“Just – In-Case” Inventory
Supplier
In the traditional replenishment model, buyers utilize independent systems and processes to create
purchase orders for their upstream supplier partners. In many cases, these purchase orders are
submitted via EDI, Internet or fax one-lead time into the future. In build to stock environments, the
supplier fills the order with available inventory and delivers the order through the established
transportation methodology.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
6
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
There are several characteristics of this type of relationship that drive inefficiencies:
The supplier has a limited view of future demand requirements
The buyer may lack category/market insights that would lead to better forecasts and orders
Both trading partners forecast their needs independently
Past supply chain outages drive both suppliers and buyers to build buffer stock to
accommodate surprises. In addition, many systems automatically build additional safety
stock based on historical supply and demand variability in to order preserve specified service
levels.
When demand and supply outages occur the relationships become adversarial
The future process state defined below offers contrast to this approach.
Future Process State
Figure 1 presents a high-level overview of DC replenishment collaboration, based upon the VICS
CPFR reference model. Trading partners develop a collaboration strategy and a joint business plan,
typically on an annual or quarterly basis. They then work together to determine the impact of
planned events, base forecast trends and product availability on retail DC demand and supplier to
retail DC distribution. As sales occur, future DC-level demand is forecast, DC replenishment orders
are placed, and delivery takes place. The cycle continues on an ongoing basis.
Along the way, exceptions related to demand planning or delivery execution are identified and
resolved. The process includes an evaluation of collaboration performance.
Figure 1 – DC Replenishment Collaboration Process Overview (VICS CPFR Model)
DC replenishment collaboration is one of four standard scenarios in the VICS Collaborative
Planning, Forecasting and Replenishment (CPFR) process. The others are retail event collaboration,
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
7
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
store replenishment collaboration and collaborative assortment planning. Guidelines are available or
in development for each of these scenarios.
Implementation Scenarios
The two major alternatives for DC replenishment collaboration are buyer-managed release (BMR) and
supplier-managed release (SMR).
o
In the BMR model, the buyer shares DC-to store forecasts and event and order plans with the
supplier, who uses these to prepare DC-specific quantities for shipment. If the supplier has an
availability constraint, wants to propose different DC-specific quantities (for example, for
displays during a promotion) or suggest alternative delivery dates, the company submits a
revised forecast or plan recommendation. Exceptions identify where differences in the buyer’s
and supplier’s plans exceed predetermined tolerances. The buyer and supplier negotiate a
replenishment approach that meets the trading partnership’s needs. The buyer adjusts their DC
reordering system to incorporate the insights of collaboration, and places orders.
This approach corresponds to collaboration role option A (conventional order management) in
the CPFR reference model.
o
In the SMR model, the buyer shares DC-level shipment history, DC inventory, event plans and a
DC -level forecast for each item. The supplier then adjusts reordering parameters to refine DC
inventory levels to match the expected demand. The buyer and supplier collaborate on event
estimates and proposed changes to DC reordering parameters. Finally, the supplier releases order
quantities within a commit window established by the buyer. Either the buyer or the supplier
may manage the replenishment planning solution that calculates DC orders.
This approach corresponds to collaboration role option B (supplier-managed inventory) or D
(retail VMI) in the CPFR reference model, depending upon whether the buyer provides a DC
level forecast.
Table 1 summarizes the roles of the buyer and supplier in each variant of the DC replenishment
collaboration process. Note that there is some flexibility in these roles, as one or both parties may be
involved in each step. Also note that a single retailer/manufacturer relationship might use both of
these models, depending on the product category or the distribution method.
Table 1 – Summary of Buyer/Supplier Roles in DC Replenishment Collaboration
Buyer- Managed
Release (BMR)
Task
Promotion Plan Joint
Supplier
- - Managed
Release (SMR)
Joint
Sales Forecast
Buyer/Supplier
Order Plan
Buyer (w/supplier input) Supplier
Order Release
Buyer
CPFR Role
Option A
Retailer and/or
Supplier
Supplier
CPFR Role
Option B or D
The SMR model requires that suppliers have deeper access into the buyer’s replenishment processes
than the BMR model. However, it provides greater assurance that the results of collaboration will
actually be incorporated into future ordering cycles. The SMR model also allows the buyer to
delegate more of the replenishment responsibility to suppliers, reducing the burden on its own
resources.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
8
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Figures 2 contrasts the replenishment ordering steps of the process for the RMR and SMR.
Replenishment: BMR Model
Lead Time
Order Multiples/Rules
Item Multiples/Rules
Shipping Constraints
Replenishment: SMR Model
Replenishment
Parameters
Lead Time
Order Multiples/Rules
Item Multiples/Rules
Shipping Constraints
Service Level Rqts
Receipt Constraints
Release
Shipments
Replenishment
Calculation
Calculation
Demand
Forecast
Shipments
Inventory
Replenishment
Parameters
Service Level Rqts
Receipt Constraints
Replenishment
Replenishment
Calculation
Calculation
Inventory
Release
Demand Forecast Inputs
Demand
Forecast
Demand Forecast Inputs
Orders & Order Forecasts
Orders & Order Forecasts
Supplier
Buyer Managed Release
Buyer
Supplier
Vendor Managed Release
Buyer
Figure 2 – Replenishment Ordering: BMR vs. SMR
Process Overview
Table 2 provides a more detailed outline of the process. Differences between the RMR and SMR
alternatives are highlighted in the below table.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
9
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Table 2 – DC Replenishment Collaboration Process Overview
Task
Buyer Managed Release (RMR)
Supplier Managed Release (SMR)
The buyer and supplier agree on which products and locations fall within the scope of
collaboration, as well as the kinds of data that will be shared, and at what interval.
Collaboration
Arrangement
The buyer determines which replenishment
parameters are available to suppliers for
visibility and proposals for adjustment.
The buyer and supplier negotiate the
process of order planning and release,
including which parameters the supplier can
adjust, and over what horizon.
Individual roles and responsibilities are assigned for process steps, along with escalation
procedures. Participants are trained in the collaboration process. The organizations align
their terminology and metrics calculation approaches.
Overall supply chain and financial goals for the planning period are established.
Joint
Business
Plan
The buyer develops its assortment, space and distribution plans, working with suppliers to
incorporate new items and adjust the mix of products to match consumer buying trends.
The collaboration environment is updated to provide visibility to the latest product
distribution matrix.
The buyer negotiates trade promotions with suppliers, and develops in-store promotion
plans.
DC
Forecasting
The buyer shares historical sales data, inventory positions and other supply chain data, as
available.
The buyer and/or supplier develops the DC-level to Store forecast and the Supplier to
Retail DC forecast that incorporates both base and promotional sales expectations. The
impact of lost sales is factored into the forecast creation.
The buyer develops order plans with the
supplier, who uses these to prepare DCspecific quantities for shipment to the retail
DC or direct to store in DSD environments.
The supplier develops order plans with the
buyer, who uses these to prepare DCspecific quantities for shipment to the retail
DC. The buyer typically continues to control
shipment to the store network in non- DSD
environments.
If the supplier has an availability constraint,
wants to propose different DC-specific
quantities (for example, for displays during
a promotion) or suggest alternative delivery
dates, it submits a revised forecast or plan
recommendation.
The supplier typically has latitude to address
availability constraints, propose different DCspecific quantities (for example, for displays
during a promotion) or suggest alternative
delivery dates within planning horizon
boundaries specified in the collaboration
arrangement.
The buyer and supplier negotiate a
replenishment approach that meets the
trading partnership’s needs. The buyer
adjusts their DC reordering system to
incorporate the insights of collaboration.
The buyer reviews the supplier’s order plans,
and highlights any changes required (due to
receiving constraints, for example).
Order
Generation
The buyer’s replenishment system
generates orders according to the
parameters in the collaborated order plan.
The buyer may provide a level of
commitment to order plans that have not
passed into a total commitment zone.
The supplier releases order quantities from
the collaborated order plan that are within
the buyer’s commit window.
Order
Fulfillment
The supplier ships the order, notifying the buyer of the inbound shipment.
Order
Planning/
Forecasting
The buyer receives the order and generates a receipt transaction.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
10
DC Replenishment Collaboration – Business Process Guide
Task
Exception
Management
Performance
Assessment
Buyer Managed Release (RMR)
FINAL DRAFT
Supplier Managed Release (SMR)
The buyer and supplier monitor sales, inventory, orders, shipments and receipts using
exception thresholds. Appropriate parties discuss and respond to the exceptions, as
outlined in the collaboration arrangement.
The buyer and supplier monitor changes to sales forecasts and order plans, as well as
major deviations between the buyer’s and supplier’s values. Participants discuss and
respond to any exceptions, as outlined in the collaboration arrangement.
The buyer and supplier calculate the key performance indicators specified in the
collaboration arrangement.
Periodic discussions confirm progress towards goals, as well as any corrective action
required.
Collaboration Roles and Responsibilities
Organizational Implications for Suppliers
DC-level collaboration places new demands on the supplier organization. Instead of relying on the
buyer or distributor to independently create the retail DC forecasts and orders, they take a more
active role in the process. The investment in human and technology resource to support DC
Collaborative Replenishment is not as great as Store Level Collaborative Replenishment where there
may be hundreds or thousands of store locations. Some suppliers prefer to start with DC level
collaboration because it is less sku intensive and provides experience that can be leveraged in store
collaborative initiatives at a later date. Suppliers frequently hire former retail buyers, merchandise
planners or inventory analysts with insight into DC and Store replenishment practices to lead
collaboration efforts.
The coordination of corporate account teams and corporate demand planning can also be a challenge.
Account teams historically have had little input into production and distribution plans. The
increasing market share of the largest global retailers makes it important to incorporate customerspecific promotions and buying trends into corporate planning. Meeting consumer demand can no
longer be a “sales issue” or a “customer service issue.” It must become a company-wide passion.
Organizational Implications for Buyers
Retail buyers and replenishment personnel have to contend with the “opening up” of their previously
private business practices to suppliers. They must evaluate supplier proposals to change ordering
parameters, and closely monitor execution to ensure that inventory hasn’t been pushed into the
channel, or allocated to less desirable assortments. It is common for buyers and distributors to grant
varying levels of visibility and access rights associated with supplier relationships. In some cases
there can be varying levels of visibility and access rights across a single suppliers categories. Some
partners may be given visibility and/or execution rights to specified menus and data while others
have to earn the trust of the buyer to be given expanded visibility. Organizations need to define the
scope of visibility and execution privileges of their initiatives before documenting specified partner
parameters in the collaboration arrangement.
Information Sharing Requirements
Buyers and suppliers must share a variety of data to collaborate at the DC level. Sales history, sales
forecasts and order plans, performance metrics and the details of promotional events all need to be
available to both trading partners. Companies may exchange this data through EDI and/or XML
messages, or use a shared implementation of a collaboration solution to make the data visible to both
parties.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
11
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Both approaches have advantages and disadvantages. A shared solution can accelerate
implementation and guarantee consistency between buyer and seller views. Peer-to-peer data
exchange implementations can incorporate data from many trading partners, and integrate more
readily with enterprise systems if shared systems do not have standard data and message exchange
capability. Trading partners will weigh the integration and execution advantages of each of these
deployments and move to the approach that delivers the greatest benefits at the lowest cost.
Collaborative Strategy and Planning Process
Collaboration Arrangement
The Collaboration Arrangement is the preparatory step that defines the scope of the project, assigns
roles and establishes procedures for data interchange, issues identification and resolution. The
process can be divided into the following steps.
A. Initial Collaboration Scope Definition
1) Receive and review background information from the sales organization or buyers (depending
upon the company role) and replenishment personnel regarding the following:
a)
b)
c)
d)
e)
f)
g)
h)
i)
Service level and inventory turn performance/objectives
Number of DCs
Map supplier DC locations to retail receipt DC’s
Receiving/shipping pattern
Promotional lead times
Average promotional quantities
Execution/visibility rights
Default item/order rules (Volume Order Brackets/Item order multiples)
Issues and opportunities of the trading relationship
2) Identify the product/location categories that should be included in the initial scope (usually
categories with large volume):
a) Document product code list, including package GTIN/UPC/EAN code, description, buyer
item code, supplier item code, package-to-case conversion factors.
b) Document the distribution center locations and timing of the rollout.
3) Prepare the collaboration team for the initiative:
a)
b)
c)
d)
Assign individual roles and responsibilities for process steps
Define escalation procedures
Train participants in the collaboration process
Align terminology and metrics calculation approaches among participants
B. Define Collaboration Objectives
1) Collaboration objectives can include:
a)
b)
c)
d)
e)
f)
Increase sales
Increase DC to Store and Supplier DC to Retail DC order forecast accuracy
Increase DC-to-store service level
Reduce product returns
Reduce activity based costs associated with pick, load, unload and put-away
Reduce excess inventory throughout the supply chain
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
12
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
2) Define specific metrics that reflect the above objectives.
C. Define Collaboration Process
1) Replenishment collaboration cycle:
a) Event calendar and attributes collaboration (typically 12 - 10 weeks prior to promotion)
b) DC to Store forecast collaboration (typically 8-16 weeks in the future for promo; 52 weeks
for turn)
c) Order planning (typically 6 - 4 weeks in the future); Order Forecast visibility can be extended
many months into the future.
d) Definition of lead times, collaboration windows and commitment time fences.
e) Collaboration assessment (typically for the prior 2-3 weeks)
2) Monthly process/results review meetings to discuss results, challenges, and process
modifications, if necessary.
3) Annual joint business planning and strategies discussion.
D. Document Data Requirements
1) Document the data sources, level of detail and timing of delivery needed for a successful
collaboration process, including:
a)
b)
c)
d)
e)
f)
g)
Event calendar (event dates and items)
Event attributes/tactics (price point, display activity, etc.)
DC to Store Forecast
Supplier DC to Retail DC Forecast
Order/shipment plan
Actual POS data
DC replenishment parameter settings
2) Document additional information that can be used for analysis, including:
a)
b)
c)
d)
Actual shipments (including any product cuts or shipping delays that affected execution)
Actual DC withdrawals or store receipts
Store and DC inventory
Store replenishment parameter settings
E. Set up Technical Infrastructure
1)
2)
3)
4)
5)
Establish data transmission process
Develop any required interfaces to enterprise systems
Load data into collaboration solution.
Set up security parameters
Administer user ID’s and passwords
F. Prepare for Collaboration Kick-off Meeting
1) Prepare Collaborative Arrangement document and other materials. (See Appendix A and B for
examples.)
2) Develop the agenda for the kick-off meeting, covering the following:
a) Collaboration objectives
b) Collaboration scope
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
13
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
c)
d)
e)
f)
Weekly/monthly/quarterly/annual process
Roles and responsibilities
Official start date
Educational Materials (Buyer prepares for supplier recruitment, Supplier prepares for buyer
recruitment)
g) Define the organizational leads for collaborative execution
h) Other milestones
i) Next steps
G. Conduct the Collaboration Kick-off Meeting
Note that a working session for CPFR team members follows the general kick-off meeting and may
include discussion of technical details (e.g. exception tolerance limits, etc.), as well as collaboration
tool training.
The following team leads are defined and are present during some portion of the kick off meeting.
a)
b)
c)
d)
e)
j)
k)
l)
Executive sponsor
Collaborative program manager
Information systems
Category Management/Merchandising
Replenishment
Logistics/transportation
Demand management
Implementation/education
Joint Business Planning
In the VICS Collaborative Planning, Forecasting, and Replenishment (CPFR) process, the supplier
and buyer exchange information about their corporate strategies and business plans in order to
develop a joint business plan. Changes in the supplier and buyer distribution networks (such as store
to retail DC alignments) are also planned and communicated to ensure forecasts are as accurate as
possible. In the DC replenishment collaboration variant of CPFR, the focus of joint business
planning is on upcoming promotions and other planned retail events (such as holidays, major sports
events and other consumer-related activities) that will drive demand from the retail DC. At this stage,
the supplier and buyer may collaborate on developing optimal plans for these events - prior to
developing detailed sales forecasts during the next stage of the process.
Either the buyer, the seller or both parties develop an event calendar that includes (in rough order of
priority):
•
•
•
•
•
•
•
•
•
What events will take place during a given time period (typically the next 6 – 12 months)
When the events will take place (start and end dates)
What brands and SKUs will be included in each event
What type of event each will be (e.g. supplier promotion, holiday, etc.)
What tactics will be used for the event (e.g. store display details, feature, display, ad, etc.)
Which Store locations (And the corresponding DC’s) will participate in the event
Consumer price points (by product/location)
Buying price/cost sharing arrangements between buyer and seller (i.e. for price reduction
promotions), and what periods these arrangements are valid for
Other external factors, such as advertising and likely competitive pressure
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
14
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
The collaborative process helps the buyer and seller agree to the event calendar and event details that
will affect retail DC shipments and specific order quantities. The objective of the event calendar is to
ensure events are planned to achieve optimal results, and to enable both parties to plan the execution
of the event more accurately, from the preparation of advertising and displays, to the production and
delivery of promotional stock. As a result, the details of an event that affect timing and impact the
forecast for demand are the most important to include.
Either the buyer or the seller documents the details that have been previously negotiated in an event
calendar. The trading partner confirms the plans for the event or proposes changes. Each party
continues to notify the other of any changes.
The completeness of event detail will vary based on the time in the planning horizon. Annual or
seasonal plans, in negotiation 6-12 months prior to individual events, may only capture product
category, volume target and a performance date range. The additional event details should be
negotiated and captured as the event approaches. At the point of forecast commitment, any
variations in event tactics or expected demand by DC must have been identified.
Collaborative DC Forecasting Process
Data Granularity
For retail buyers, POS forecasting begins with POS data. For buyers that have a multi-echelon
replenishment model, the POS is aggregated and enhanced with a lost sales calculation and leveraged
upstream for the retail DC supplying these stores. Many buyers have single-node replenishment
models that rely on shipment history as the primary data stream to calculate future forecasts. For
retailers, POS data collection includes each cash register scan of a consumer purchase. This
individual scan level POS data, while sometimes useful for market research, is too detailed for
replenishment purposes. Before reporting POS, retailers first consolidate the data along several
dimensions:
o
o
o
Time dimension – consolidated to day or retailer week
Location dimension – variously consolidated to store, DC, retailer region or chain
Product dimension – preferably reported at the GTIN/UPC/EAN code level
Suppliers are sometimes given the option to retrieve POS data at multiple levels. The most common
alternatives are DC or chain level data summarized by week.
Collaborative Forecast Elements
In DC Replenishment Collaboration, one of the primary drivers of the order is the sales forecast.
Trading partners work together in this model to ensure the forecast is as accurate as possible and
collaborate on multiple inputs to the total sales forecast number. The following forecast elements are
the ones most commonly reviewed collaboration process:
-
Base forecast- The base element is sometimes called out as the “turn” component of the
forecast and represents the movement of product that is driven by regular demand without
the influence of causal events.
-
Seasonal Profiles- Many products are seasonal in nature and can have dramatic differences in
movement throughout the year. To distinguish this “forecastable” variability from random
demand fluctuation, some replenishment systems allow for the application of seasonal
indices or profiles to properly build replenishment orders into the season and reduce the
forecast and corresponding orders appropriately at the end of the season. Seasonal indices
are typically applied to the base forecast and trading partners can leverage their unique
product and category insights to ensure these indices are applied properly.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
15
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
-
Promotional Forecast- The promotional element of the forecast represents the expected
demand above the baseline component that is driven by causal events. Trading partners can
leverage their experiences with similar causal events and collaborate on these experiences to
ensure that in-stocks are maximized with the optimal inventory investment. Buyers and
suppliers often keep a historical record of lift factors from historical events and subscribe to
syndicated market data as inputs to forecast models for this effort.
-
Calculations/filters for lost sales- Filters and calculations for lost sales are often incorporated
into the forecast collaboration in the DC and Store Replenishment models. Historical
movement, which is often one of the primary inputs for the baseline forecast, can be
dramatically understated if historical lost sales are not accounted for in the process. Trading
partners collaborate on the approach for calculating/filtering lost sales and incorporate this
element into their collaborative discussions.
Single Node Planning versus Multi-Echelon Planning
The data that is leveraged in a DC or Store Replenishment Collaboration environment will vary
depending upon the planning methodology that is adopted by the trading partner. When multiple
nodes in the supply chain are considered in the creation of inventory policy and forecast plans, a
multi-echelon approach is adopted. When inventory policies and forecast plans are built on a single
node and the inventory positions and forecasts of other nodes are not taken into account, the model
is referred to as “single node” because other nodes are not directly driving the replenishment
parameters of the planning node.
Multi-Echelon – the DC sales forecast is determined by using the downstream consumer sales
forecast as the primary input.
In a fully connected environment, the calculation of a DC sales forecast is an inventory planning
exercise, which is fully dependent on the previously formulated consumer sales forecast. Inventory is
accounted for within different nodes in the supply chain in a multi-echelon model. When DC
forecasts are driven from POS sales and POS projected lost sales, it is important that the inventories
in the stores are considered so the demand on the DC is adjusted to account for understocks (The
DC needs to order earlier and potentially more) and overstocks (the DC can order later or potentially
less).
Additional inputs to the DC plan are facilitated through buyer seller collaboration and include:
Returns to the DC,
Changes in the DC to store network,
Changes in the DC or store inventory policy, and
Historical DC inventory shrinkage.
Store category shelf sets
Store display plans
Seasonal store reordering policies
Seasonal warehouse safety stock levels
The consumer sales forecast may be modified with the above inputs to determine the DC sales
forecast. The high-level process steps in a connected environment are:
1. Review and adjust planning inputs,
2. Add additional inventory planning variables (shrinkage, store model quantities, lead times),
3. Review and gain agreement with all internal departments,
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
16
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
4. Generate DC level forecast using planning engine
5. Review and gain agreement with all internal departments, and
6. Review forecast with trading partner.
Note that the DC level forecasting does not occur independently of the store forecast in a connected
environment.
Single Node Model- the DC sales forecast is determined without benefit of the downstream
consumer sales forecast. In this case, shipment history from the DC to the stores is used as the
primary input. A statistical forecast model is used to predict the DC to store network sales forecast.
Order Planning/Forecasting
In best practice DC forecasting, store-level sales forecasting process yields a detailed picture of
consumer demand is leveraged as a starting point. The order planning and forecasting step
determines what the buyer and supplier must do to satisfy that demand, through a time-phased
sequence of orders, shipments and receipts that maintain store inventories at the desired service level.
Order calculation to DC’s considers two tiers of distribution. Even though no inventory may be held
at the DC level (Cross Dock/Flow Through), the additional components of lead time and handling
time must be included. If inventory is held at the DC, then the replenishment calculation must be
made for the DC-to-store level, followed by supplier-to-DC to Buyer DC.
From the buyer’s perspective, the sales forecast represents projected sales from the store shelf to the
consumer or in some environments the forecast of demand from the customer distribution centers
to the purchaser (Co-operative Distributors). From a buyer’s perspective, the order forecast
represents what they are going to order from the supplier to meet the needs established in the sales
forecast. Unfortunately, some trading partners have created separate disconnected processes for
developing the sales and order forecast. It is important to understand that the sales forecast and
order forecast are inextricably linked. Thus, when a change occurs in the sales forecast, there should
be a dynamic synchronization process that automatically adjusts the order forecast. The two
forecasting processes should not be approached independently.
To address this issue it is important to understand the complexity involved with accurately providing
an order forecast beyond one lead-time with a required level of accuracy. Suppliers are typically very
interested in the order forecast because it answers the question, “What is my customer going to order
and when?” Having input and insight into the demand stream is very valuable but in isolation does
not provide enough information to assist in the commitment processing of production capacity and
finished goods inventory planning.
Variables that must be considered for accurate sales forecast to order forecast translation include:
On-hand and on-order inventory positions of the buyer
Order cycle / Order frequency policies
Changes to inventory policy (Safety Stock Requirements - service level, weeks of supply)
Shipping requirements (Item Min & Max, Order Min & Max)
Lead time
Unit translation (Order/pack multiples)
DC to DC inventory transfers
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
17
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Safety Stock Calculation
The classic replenishment calculation generates the minimum order quantities needed to maintain
inventory at safety stock over the planning horizon. The safety stock requirement increases with the
volatility of demand and supply. There are several statistical methods for calculating safety stock to
meet a desired service level; alternatively, companies may choose a simpler “rule of thumb” method,
such as days or weeks of supply. While less accurate, the advantage of rule-of-thumb methods is that
they can be readily negotiated between trading partners, independently calculated, and referenced in
supplier agreements. Some trading partners leverage advanced planning systems that enable them to
collaborate on the inventory trade-offs of differing service levels. This approach can enable trading
partners to agree on specified service levels in their agreements and carry inventory positions tailored
to their strategic parameters.
Distribution center inventory calculations have many overriding inventory constraints, which may
result in less than “optimal” quantities being maintained. For example, suppliers may have minimum
unit case quantities and truckload order brackets that cause a DC to carry excess supply. Slowmoving items may end up with a year’s worth of inventory on-hand simply to meet specified
minimum case and order multiples; fast-moving promotional items may go out-of-stock in the DC
slot because there is not enough capacity allocated to the item on a regular basis.
Demand and Supply Data
The estimated rate of inventory consumption may be based on historical or forecasted demand. In
CPFR, sales forecasts are most often used as the input to order planning. Assuming that forecasting
practices are sound, DC forecasts capture trends, seasonality and planned events that shipmenthistory-driven planning would miss. The minimum required horizon of the forecast is the next
ordering window, though longer horizons can support mid- and long-range planning of promotional
orders, manufacturing production and logistics/production capacity.
Information about inbound products is equally important. Order calculations should exclude
inventory that is committed to be delivered, in-transit or arrived but not available due to ad dates,
quality hold, or additional handling requirements.
Projected Inventory, Shipments and Receipts
Once all the data has been gathered, the actual replenishment calculation is fairly simple. Projected
consumption is netted from the current inventory, and any expected receipts are added back in. If
the resulting projected inventory quantity is less than safety stock, a new order is proposed to
increase the inventory to safety stock levels. The calculation is repeated over the reordering horizon.
Additional replenishment constraints can complicate this process. The orders have to take into
account the lead time of order processing, delivery and receipt, the dates/times that both the
shipping and receiving locations are open, minimum order sizes as well as (potentially) transportation
load building and routing rules. In its fully-developed form, replenishment calculation is a complex
statistical optimization problem that seeks to flow inventory in a way that maximizes profitability for
the trading partners. The output of the process is an order plan, with projected inventory, receipts
and shipment quantities by item over the planning horizon.
Collaborating on Order Plans
Collaboration is intended to uncover the issues and opportunities in the order planning process.
When out-of-stocks, overstocks, or excessive logistics costs are identified, the trading partners work
together to enhance future plans. Certainly, ad hoc orders can be entered, and planned orders can be
deferred or canceled to deal with tactical issues. But more lasting improvements depend upon
adjusting the parameters that drive future order planning.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
18
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
The parameters that can be adjusted vary with the collaboration program, and the underlying
replenishment technology being used. They may include one or more of the following:
o
Safety stock: The safety stock method or the threshold value may be altered, reflecting expected
changes in the volatility of demand or supply.
o
Lead time: The number of periods for order processing, transportation and/or receipt may be
revised, reflecting different transportation modes, sourcing points, order processing cycle time or
receiving practices.
o
Order sizing: The rules for rounding order quantities up (or down) can be adjusted to reflect
changes in minimum order requirements, transportation constraints or capacity.
The frequency of collaboration on orders depends on the volatility and importance of the product,
seasonal variation, assortment complexity, transportation mode, and distribution cost. Collaboration
on some products is intra-day, while others can be weekly – or even monthly.
Establishing Commitment Parameters
According to the third CPFR guiding principle used to create the initial guidelines, partners commit
to a shared forecast through mutual risk taking and the removal of supply process constraints.
Committing to a customer focused demand strategy based on real knowledge of each step in the
trading process greatly reduces the uncertainty associated with sales and order forecasting. Adopting
a single shared forecast of demand, suppliers can shift from a “build to stock,” to “build to order”
methodology which can greatly reduce the dependency on buffer inventory. Restraints such as fixed
retail order cycles or inconsistent delivery and fill rates from suppliers can be greatly reduced.
After trading partners agree on the single shared order forecast, there has to be a level of
commitment that is given by both trading partners to achieve the vision of the third guiding principle
of CPFR. If suppliers are going to move to “build to order” processing or significantly reduce safety
stocks, there has to be a confidence level that the buyer is going to provide purchasing commitments
beyond a typical lead-time. The commitments should have a stated level of tolerance that can be
decreased as the orders approach delivery. By contrast, in order for buyers to lower safety stocks and
attain higher fill rates, they need commitments of supply from their respective suppliers and visibility
to manufacturing constraints to meet consumer requirements efficiently. The ability to overcome
this hurdle hinges on a level of confidence embedded in the order forecast. A trading partner’s
willingness to commit to an order forecast is directly correlated to the accuracy the order forecast has
delivered over time.
A strong possibility exists that there are cultural barriers that have inhibited the adoption of
commitment processing. Both trading partners have to take on a certain degree of risk to get to this
level of a CPFR relationship. Customers that provide a level of commitment to order beyond
historical lead-time parameters should receive a level of commitment to supply beyond historical
levels from suppliers. In order to reap the full rewards of collaboration this step must be taken.
Figure 2 below displays a graphical view of how an order forecast might be displayed after the
previously mentioned order adjustments are taken into account. Each column represents an order
forecast that will eventually become an order. As time progresses, the columns will move to the left
until the orders become live and tendered for shipment. It is important to note that if the order
forecasting process is going to automatically translate to order generation, the entire supplier line
must be taken into account. It does not make sense to execute a subset of items for this process
within the supplier line unless that subset is tendered as a separate order.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
19
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Example: Projected Receipt Quantities and Dates
Figure 2
Item Number Item Description
100% Committed
30
70% Committed
60
5-Jan
18-Jan
1-Feb
12-Feb
5-Mar
21-Mar
123456 SKU 1
120
543
345
380
434
6243
123457 SKU 2
2321
345
3333
578
66
444
123458 SKU 3
234
753
154
524
643
434
123459 SKU 4
212
345
245
623
453
434
123460 SKU 5
465
2345
667
35
4534
45
123461 SKU 6
453
454
436
44
345
6443
123462 SKU 7
753
345
643
234
543
455
123463 SKU 8
545
754
345
553
453
643
Figure 2 – Time phased order forecasts with commitment percentages
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
20
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
RosettaNet Order Planning Approach
RosettaNet is a self-funded, non-profit organization, RosettaNet is a consortium of major
Information Technology, Electronic Components, Semiconductor Manufacturing,
Telecommunications and Logistics companies working to create and implement industry-wide, open
e-business process standards. These standards form a common e-business language, aligning
processes between supply chain partners on a global basis. RosettaNet is a subsidiary of the Uniform
Code Council, Inc. (UCC).*
RosettaNet Collaborative Forecasting supports three types of release processes:
-
-
Embedded release – The buyer releases order quantities by indicating which demand in the
forecast message is firm. This is done directly in the forecast via one of two methods:
o Frozen period: Quantities that are within the specified frozen period are authorized for
shipment
o Ship indicator – Individual line items in the forecast are tagged with a ship authorization
indicator
Material release – The buyer releases order quantities via a separate material release transaction.
The material release includes only the items and quantities to be released.
Threshold release – The seller releases order quantities based upon parameters gathered from
the buyer, including on-hand inventory, minimum inventory level, maximum inventory level, and
past due demand. The seller has the latitude to release orders as it sees fit as long as inventory
remains between minimum and maximum levels (expressed either as a scalar quantity or as days
of supply).
Any changes to forecast buckets that are within the frozen zone incur liability on the party that made
them. An additional “Trade-off zone” may also be specified, which is a future horizon within which
liability for changes may be shared between the buyer and the seller. Outside of the frozen period
and the trade-off zone, forecast changes may be made without penalty.
The buyer can indicate partial commitment to a forecast by supplying separate downside and/or
upside forecasts, which indicate the potential minimum and maximum volumes that will be requested
over the planning horizon.
*
RosettaNet organizational definition provided from home page: www.rosettanet.org
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
21
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Collaborative DC Ordering and Fulfillment Process
Order Release
In replenishment-based environments, the transition from order planning to order fulfillment is
called order release or order firming or order commitment. Among the available proposed orders in the
replenishment plan, some are selected for processing and delivery. Some orders for future periods
may be released early to create efficient transportation loads; others may be deferred due to
availability problems, or to improve production sequencing. Collaboration focused in these decisions
can lower costs and improve overall product availability for both parties.
Figure 2 introduces the notion of “time-fencing” an order forecast after it has been calculated. A
time fence, represented by the vertical solid blue lines, represents a point in time where the order
forecast changes its degree of commitment by the collaborative trading partners.
From the customer’s perspective, commitment is demonstrated by a willingness to purchase against
the forecast. From a supplier’s perspective, commitment means they will produce, deploy and ship
against the forecast. The example above shows that two time fences have been established as part of
the relationship. The first time fence is 60 days out into the future. When order forecasts pass this
first fence, they are 70% committed or conversely the order quantities can vary by +/- 30% between
30 and 60 days. The second time fence is 30 days out into the future. When the order forecasts pass
the 30-day time fence, they become 100% committed.
In practice, it is likely that trading partners will establish multiple time fences with increasing levels of
commitment as the order delivery date approaches. Suppliers have to make production decisions,
how much, before they have to make distribution decisions, where to send it. Volume commitments
might be made at the early time with inventory deployment decision postponed until later. The result
is that the buyer and the supplier can collaborate about decisions that have specific types of
parameters at different times. These decisions drive specific cost implications that should produce
benefits. Understanding those benefits should be the foundation for risk sharing. Trading partners
can take measured steps to ensure that they feel comfortable and can meet the commitment
parameters established in their collaborative arrangement.
For example, in the beginning of a collaborative relationship, the first time fence can be established
at the traditional order lead-time that was used to generate orders prior to the collaborative
engagement. Order forecasts beyond the first time-fence can be used for planning purposes only
with no implied commitment level. As the collaborative relationship matures and the partners feel
more confident of the order forecasts that are being generated, additional time fences can be added
with varying levels of commitment. This progression will be made easier if order forecasting
accuracy measures are made available. Suppliers will obviously prefer that the commitment levels be
as far in the future as possible with low tolerance for change. Customers will likely prefer shorter
commitment windows and wider tolerance ranges. Suppliers may choose to provide incentives to
their customers to provide longer commitment windows through menu based pricing and terms
options. The consumer will be the ultimate benefactor of commitment processing because the work
of the collaborative forecasting will translate to executable product orders that provide stock
availability when they are ready to buy.
In the SMR model, if a supplier is able to schedule orders for accelerated delivery, the buyer usually
has some control over the reorder window (period of time) or maximum authorized quantity of
advanced deliveries. Alternatively, the buyer may perform the order release, based upon the supplier’s
order plan. This could be called the jointly managed replenishment (JMR) option.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
22
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Unless they are expedited, deferred orders may cause out-of-stocks at the buyer. Collaboration may
focus on generating demand for an alternative item, sourcing inventory from other locations or
developing an allocation strategy to minimize the impact.
Sales and Operations Planning (S&OP)
POS is superior to supplier shipments as a demand signal when planning future sales, manufacturing
and distribution requirements. This is because POS is the best representation of independent
demand available (enhancing POS with a lost sales calculation will avoid under forecasting due to out
of stocks). Shipment history, which typically drives supplier demand planning processes, is “polluted”
by supply constraints, poor fill-rate performance, diversion and forward buying. Relying solely on
this type of data can lead to product shortages or oversupply, resulting in markdowns and a tarnished
brand image.
Large retailers recognize that POS and POS forecasts need to be integrated with their supplier’s sales
and operations planning (S&OP) processes in order to drive the high-level of fill rate performance
needed for efficient DC replenishment. Although 100% fill rates can sometimes be achieved by
“shorting” another buyer, this is a poor business practice that is not sustainable in the long term.
Ensuring adequate supply by aligning production with expected POS is the most effective strategy.
However, POS data is not directly usable by S&OP. Forecasts based on POS need to be translated
into shipments and organized along supplier hierarchies before integration is possible.
Figure 3 illustrates a “bottom-up” S&OP process that uses POS forecasts aggregated from “critical
mass” buyers to generate a more accurate supply plan. The revised process requires not only a
flexible data model to represent the appropriate data hierarchies, but also the replenishment planning
logic to turn consumer demand forecasts into actual order forecasts that match likely future buyer
ordering patterns.
Figure 3 – POS-driven S&OP Process
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
23
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
S&OP Linkage to CPFR
The advent of CPFR and the new customer intelligence that these relationships bring enable the
supplier consensus demand plan to be enhanced by the input of the trading partner closest to the
consumer — retailers and distributors! The key outputs of CPFR engagements include the
collaborative sales forecast, the collaborative order forecast and orders that enable suppliers to hit
forecast accuracy levels that would not have been possible without these new customer insights.
Figure 4 below highlights the key touch points of a merged CPFR/S&OP model.
3.
2.
Supply
Review
Executive
Mgmt Business
Review
Demand
Review
1.
4.
New Product/
Activities
Review
CPFR ® Model Property of VICS
Figure 4 – Linkage of CPFR to S&OP
High level steps:
1. The outputs of the CPFR sales and order forecasts are aggregated in a central information
repository. These forecasts are then summarized with the forecasts of non-collaborative
customers to form a total market demand view. This customer view is compared and
analyzed against the suppliers’ internal functional views of future demand. The demandplanning group within the supplier’s organization analyzes the customer and functional views
and uses a variety of techniques to generate an unconstrained consensus demand plan.
New product/activities planning is a formal step in many supplier S&OP processes that
often occurs prior to or in parallel timing with the demand review. The impact of new item
demand and project activities on existing resources within the organization is measured. In
addition, the halo and cannibalization impacts of existing product sales are analyzed and
incorporated into the demand plan.
2. The supply organization processes the unconstrained demand plan. The supply team
reviews available capacities and develops a recommendation to synchronize supply with
demand. The team then prepares and submits its recommended supply plan and any
outstanding, unresolved issues to the next phase of the S&OP process.
3. During the executive management business review, the general manager reviews the
recommendations from the demand and supply organizations to resolve any supply or
demand imbalances. The executive team selects an alternative plan that most closely aligns
with the company’s overall strategies and objectives.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
24
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
4. In some cases the decisions made during the Executive Management Business Review will
not enable all supply/unconstrained demand imbalances to be resolved. As an example,
there may be a “conscious” decision not to close capacity gaps due to the cost or timing
capability to gain closure. In these cases, a feedback loop is taken back to the customer to
minimize the lost sales impact of a product allocation issue. The supply team adjusts
customer order forecasts downward at the customer level with appropriate alternate plans
such as promotion shifting or product replacement to minimize the impact to the consumer.
Collaborative Analysis Process
During this stage of the process trading partners review their scorecard against objectives set in the
collaborative arrangement. Critical measurements often include forecast accuracy, in-stock percent,
sales, inventory turns and attained service levels. Trading partners perform root cause analysis to
understand why metrics are under or over performing and create action plans to address discovered
gaps. The metrics identified in a Collaborative DC Replenishment exercise do not have to be limited
to the DC node in the supply chain.
Representing end-consumer sales as counted by retail cash register scan activity, store-level POS data
can provide suppliers with tremendous insight into independent demand at the final stage of the
supply chain. More conventional sources for supplier demand information – such as historical
shipments or buyer warehouse withdrawals – can obscure true consumer demand patterns due to
forward buying, diversion, overstocks or understocks. When combined with related data, such as
retail on-hand inventory, store replenishment from the warehouse, and quantities on-order, POS data
offers suppliers who are able to manage it a competitive advantage in forecasting and replenishment
accuracy.
Buyer/Supplier Data Mapping
POS data needs to be mapped and translated from the originating format to a common format for
loading. Data mapping between different buyer views and supplier views is then required for
meaningful aggregation by product, brand, or region.
Mapping POS data from different sources presents a number of challenges:
o
Buyer-sourced POS data is structured along each buyer’s hierarchies, which include the buyer’s
product groupings, the buyer’s fiscal calendar and the buyer’s geographies. These may all be
different and need to map to the supplier’s hierarchies.
o
Buyers may pre-aggregate POS data into their time buckets (e.g. day and retail week), their
locations (store, buyer DC, or buyer region), and their product identifiers (e.g. “master” SKUs).
These may require disaggregation to align with a supplier’s data.
o
Buyers often report POS data in number of individual packaged units sold, whereas suppliers
may look at it in terms of the number of cases sold.
o
Suppliers often have one or more GTIN/UPC/EAN codes for case packs of a product that
needs to be mapped to the individual packaged unit’s item number.
Figure 4 illustrates the complexity of this process.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
25
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Demand
Mfr View
Shipments
Shipments vs.
vs. POS
POS
Supplier
Locations
Time Buckets
Customer
Locations
Total
Monthly
Monthly vs.
vs.
Weekly
Weekly or
or Daily
Daily
National
Shipping DC
Plant/Mill
Supplier
Products
Cat
Brand
Locations
Supply
Supply Point
Point vs.
vs.
Retailer
Retailer DC
DC
Quantities
Cases
Cases vs.
vs. Eaches
Eaches
Case UPC
Material
Retailer View
Retailer DC
Store
Retailer
Products
Cat
Brand
Each UPC
Product Identification
Item
Case
Case UPC
UPC vs.
vs.
Each
Each UPCs
UPCs
Figure 4 – POS Data Mapping
Syndicated data, panel data, and competing products’ POS data further complicate data mapping by
introducing competitor brands and products, the concept of demand channels (e.g. mass merchant,
drug, grocery), and market share-related data. Many suppliers find their ERP systems to be quite
inflexible in handling data that doesn’t align to the hierarchies defined to support internal processes.
Armed with insight into actual consumer demand gained from analysis, users can make wellinformed management decisions. There are two types of actions that the data can support:
o
Strategic actions: Changes in product mix, production capacity, distribution channels or
marketing programs in response to better consumer insight. These need to be incorporated in
the supplier’s sales and operations planning (S&OP) process.
o
Tactical actions: Adjustments to production plans, inventory policies, order quantities,
transportation arrangements or other near-term activities to respond to particular exceptions.
Recognizing, for example, that demand during an upcoming promotion is going to be much
higher than anticipated could allow a supplier to resequence production, or arrange additional
transportation to avoid an out of stock situation. Tactical issues such as out-of-stocks, overstocks,
inaccurate DC-level forecasts, and inadequate supply or transportation capacity typically require
near-real-time notification. Intervention often must take place in the buyer’s system. Tools that
provide customers with the right amount of analytical data to understand the issue and for the
supplier to propose a solution are critical to success.
Exception Management
Although the volume of transactions and item/location forecast numbers are not as large as
Collaborative Store Replenishment initiatives, one should plan for an approach to identify issues that
work via exception versus standard reporting. To understand problems and opportunities hidden in
the data, companies may employ data mining techniques. The most effective analysis for DC
Shipments, inventory and the other time series data is threshold, or tolerance based. Users set up
business rules based upon tolerances for key values at a particular level of detail, and then examine
the exception cases where the threshold or tolerance is exceeded.
Table 2 outlines some typical exception rules, along with the kinds of resolution actions that can be
taken in each case.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
26
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Table 2 – Typical Exceptions and Resolution Actions in DC Collaborative Replenishment
Exception
Criterion
Comparison/
Threshold
DC
Understock
o
o
o
DC
Out-of-Stock
o
o
DC
Overstock
o
o
o
Potential Resolution
Actions
Inventory (or projected inventory) <
safety stock
Inventory turns > maximum
threshold
Inventory days/weeks on hand <
minimum threshold
o
o
o
Inventory < 1 (or minimum display
stock)
Days with zero sales, or sales far
below the recent average (useful
for fast-moving items, when DC
inventory values are not reliable)
If out of stocks are prevalent:
o Determine pattern (category, geography)
o Isolate issue to source:
a) Underforecasting (high forecast error
percentages)
b) Starved replenishment (safety stock
threshold too low, unrealistically short
lead times or supplier capacity
constraint)
c) Execution policies (short ordering,
late ordering, late shipments/
deliveries, inaccurate DC inventory
counts).
d) DC execution problems (check-in
issues, delayed unload, delayed putaway)
o Adjust policies within category/geography
that triggered the exception
o
Inventory weeks on hand >
maximum threshold
Inventory turns < minimum
threshold
Inventory count > DC capacity
o
o
o
Promotion
Change
Supplier to DC
& DC to Store
Forecast
Change
o
o
Date, price, display/ad or sales
estimate change from previous
communication
o
(|Current Forecast – Previous
Forecast|) / Current Forecast >
xx% at a medium-/near-term
horizon
o
o
o
Replan orders
Propose replenishment planning changes
Expedite orders if necessary
Determine pattern (category, geography)
Isolate issue to source:
a) Overforecasting (high forecast error
percentages)
b) Optimistic order plans (excessively
high safety stock thresholds,
conservative lead times or overly
large minimum order sizes)
c) Execution policies (forward buying,
early arrivals, inaccurate DC inventory
counts).
Adjust policies within category/geography
scope that triggered the exception
Reforecast sales for the event, and
integrate with baseline forecasts.
Expedite or defer orders, if event is near
and date moves up or back (respectively)
Investigate reason for the change
a) New/changed/canceled promotion
b) Product/location reprofiling
c) Manual override
d) Other
Determine whether local forecasts should
be adjusted
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
27
DC Replenishment Collaboration – Business Process Guide
Exception
Criterion
Comparison/
Threshold
DC
Forecast
Difference
o
(|Buyer Forecast – Supplier
Forecast|) / Buyer Forecast > xx%
at a medium-/near-term horizon
Potential Resolution
Actions
o Replan orders for affected products/
locations, if necessary
o
o
o
DC
Forecast
Error/Accuracy
o
o
o
(|Collaborated Forecast – Actual
Sales|) / Actual Forecast > xx%
The forecast may be lagged to
eliminate the effects of adjustments
after planning window passed
Mean weighted absolute
percentage should be used when
measured at aggregate level.
FINAL DRAFT
o
o
o
Investigate reason for the difference
a) New/changed/canceled promotion
b) Differences in forecasting
methodology
c) Manual override
d) Technical data/process error
Determine whether local forecasts should
be adjusted
Replan orders for affected products/
locations, if necessary
Investigate reason for the error
a) Out-of-stocks
b) Competitive activity
c) Planogram/assortment change
d) Poor statistical modeling
e) Technical data/process errror
Determine whether forecasting
methodology should be changed
Reforecast affected products/ locations, if
necessary
Product
Addition/
Discontinuation
o
o
Product change notification
(Buyer or supplier) data missing,
other data present
o
Reconcile new / discontinued products.
Replenishment
Parameter
Change
o
Lead time, safety stock, minimum
order size or other value change
from previous communication
o
o
o
Validate reasonableness of change
Adjust affected order planning systems
Replan orders
Order Plan
Change
o
(|Current Order Plan – Previous
Order Plan|) / Current Order Plan >
xx or xx% at a near-term horizon
o
Investigate reason for the change
a) Overstock/understock condition
b) Forecast adjustment
c) Replenishment parameter change
d) Manual override
e) Inventory transfer/adjustment
f) Technical process/data error
Determine whether replenishment
parameters should be changed
Replan orders for affected products/
locations, if necessary
Expedite or defer orders for near-term
periods, if necessary
o
o
o
Deviation of
Actual Orders
from Plan
o
(|Order Plan – Actual Orders|) /
Actual Orders > xx% at a near-term
horizon
o
Investigate reason for the deviation
a) Late ordering
b) Short ordering
c) Forward buy
d) Lack of planning/ordering
coordination
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
28
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Exception
Criterion
Comparison/
Threshold
Potential Resolution
Actions
e) Technical process/data error
o Determine whether replenishment
parameters should be changed
o Replan orders for affected products/
locations, if necessary
Order
Execution
o
Receipts vs. Shipments vs. Orders
o
o
Resolve shipping execution problems
Resolve shrinkage during shipping
Inventory
|Flow-Through
o
Sales vs. Orders over a long
horizon (quarter or more)
o
Check beginning and ending inventory
balances.
If mismatch is unaccounted for by
inventory balance changes, review
transfer orders (if store- or DC-level) or
investigate inventory diversion (if accountlevel)
o
Missed
Performance
Target
o
Category sales, inventory turns,
forecast accuracy or other measure
below target for the planning period
established in the Collaboration
Arrangement
o
o
Investigate the reason target was missed
Work with trading partner to develop
remediation plan
While basic rules are simple to set up, there are many subtleties that a user must consider. For
example, a sales deviation from forecast of 25% may be considered a tolerance exception, but a
minimum threshold of a 24 unit difference might be set to filter out slow-moving products from
generating an exception. Some rules need different thresholds at different time horizons; sometimes
rules need to be combined (sales are high while inventory is low).
The complexity of these rule combinations needs to be balanced with the need for non-technical
business analysts to set up and manage the rules. Performance must also be considered. Without a
database design and software applications specifically designed for managing voluminous data, it is
very difficult to develop an efficient, easy to use, scaleable system.
Performance Assessment
Performance assessment is essential to any understanding of collaboration benefits. While retail outof-stock is the main measure of whether the product was available to the end consumer, it is also
important to measure service level and fill rate. These measures are more “diagnostic”. They help
identify the issues that resulted in retail out-of-stocks. For example, the fill rate might indicate that
the supplier was not able to ship the adequate amount of product to buyer DCs. The service level
might indicate that the buyer was not able to effectively distribute the product from its DCs to its
stores.
Another desired metric is some measurement of profitability. It is more difficult to establish
standards for profit measures. Depending on their organizational perspective, buyers and suppliers
may include different costs in their calculations. To complicate matters, companies are often
reluctant to share the cost information that would be required for a comprehensive profitability
analysis.
Category analysis complements the evaluation of individual products and promotions, and prepares
participants for future collaboration arrangement discussions. Category analysis considers the
response of items and categories to promotional activity, competition, consumer trends, and brand
initiatives. As a result of this analysis, trading partners may recommend changes in product
assortment, regular shelf and/or display placement, pricing and promotion strategies.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
29
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Data Interchange Requirements
The following sections describe data interchange requirements for DC replenishment collaboration
in more detail. This is only a high-level guide. Specification references are based upon V1.3.1 of
EAN.UCC Business Message Standards. In the event of any difference between the technical
information contained here and that in the standard, the standard takes precedence.
Point-of-Sale (POS) Data Interchange
Point-of-sale data is available from a variety of sources. Many buyers provide POS via an EDI
transaction, such as the ANSI X.12 Product Activity (852) transaction set in the U.S., or the
EDIFACT Sales Report (SLSRPT) in other countries. EDI provides a common format that is easily
interpreted by commercial EDI translators or simple data mapping software, with no user
intervention required. Since EDI sales transactions are often accompanied by buyer on-hand and onorder quantities, additional insight can be obtained by receiving this EDI data.
EAN.UCC XML transaction sets are also available for transmitting POS data. Even at DC level,
XML-based Product Activity messages can become very large. To reduce the data volume and
processing overhead, a “bulk” version of the Product Activity message can be used, which represents
the data in a simpler format.
Larger buyers often skip standards-based messaging altogether, and supply more granular (DCand/or store-level) POS data to suppliers through extranet portals into their data warehouses.
Suppliers with access to these portals can customize the POS data retrieved and download it on their
own schedule. Although they offer flexible reports, extranets require user intervention to schedule
extracts and receive data on a supplier’s system.
Sometimes buyers distribute POS data via proprietary data file feeds to strategic suppliers (e.g.
category leaders), which may even include competing product data. This data is particularly useful to
marketing organizations by providing insight into market share within an individual retail channel.
Syndicated data services are another source for high-quality POS data. For some buyers, it may be
the only source available. These services map and cleanse the data, manage consumer panels and
provide market share information.
Retail Event (Promotion) Data Interchange
EDI support for retail event communication is weak. Global EDI standards do not include any
transaction in this area; VICS EDI offers the Promotional Annoucement (889) transaction set, but it
is poorly suited for collaboration and not widely used.
The best communication vehicle for promotions is XML based. The EAN.UCC Retail Event
Business Message specification provides a standard for communicating event data. Key attributes
that can be communicated for each event include event timing, event type, pricing, expected volume
and tactics, such as ad, display, special packaging, coupons or other consumer incentives..
Order Planning Parameter Data Interchange
The EAN.UCC Trade Item Location Profile message offers a means of transmitting proposed
changes in order planning parameters such as lead time, safety stock and minimum order quantities.
Exception Message Interchange
Companies can use the EAN.UCC Exception message to communicate threshold or tolerance
violations related to forecasts, actual results or metrics.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
30
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Example Process
Figures 5 and 6 illustrate more complete examples of DC replenishment collaboration message
interchange. Figure 5 shows the buyer-managed release (RMR) variant, while Figure 6 shows the
supplier-managed release (SMR) variant.
Retailer
Manufacturer
Retail Event
Product Activity
Sales Forecast
Forecast Revision
Order Plan
Trade Item Location Profile
Purchase Order
Despatch Advice
Receipt
Figure 5 – Sample Buyer-Managed Release Message Interchange
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
31
DC Replenishment Collaboration – Business Process Guide
Retailer
FINAL DRAFT
Manufacturer
Retail Event
Product Activity
Sales Forecast
Sales Forecast
Forecast Revision
Order Forecast
Forecast Revision
Order Release
Despatch Advice
Receipt
Figure 6 – Sample Supplier-Managed Release Message Interchange
Table 3 maps the logical data interchange between the trading partners to electronic commerce
message standards. EDI messages can be used for several steps in the process, but only the
EAN.UCC XML message standard has messages that correspond to all the communications
requirements. Key gaps included the following:
o
Global EDI does not have a message for communicating promotional events. The VICS
EDI message for promotions (the 889 transaction set) is not widely implemented, and does
not have collaboration capabilities.
o
EDI does not have general messages for communicating metrics. The VICS EDI Product
Activity message can include fill rate information, but little else.
o
Communication of exceptions is not covered in EDI.
In response to the gaps, some companies choose a hybrid approach. They utilize EDI for all the
conventional data interchanges, supplemented by XML for collaboration messages, such as the
Forecast Revision. The challenge of hybrid communications is that typically two sets of B2B
infrastructure technology are required for EDI and XML. Relatively few organizations have XML
transaction processing in production (though the number is growing).
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
32
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Table 3 – Mapping Electronic Commerce Message Standards to Retail Event Collaboration
Message
EAN.UCC XML
Global EDI
VICS EDI
Retail Event
Retail Event
N/A
Promotional Announcement
(889)
Sales Forecast
Forecast / Forecast
Response
SLSFCT
Planning Schedule with Release
Capability (830)
Exception
Exception Notification
N/A
N/A
Order Forecast
Forecast / Forecast
Response
DELFOR
Planning Schedule with Release
Capability (830)
Purchase Order
Purchase Order
ORDERS
Purchase Order (850) or
Grocery Order (875)
Despatch Advice
Despatch Advice
DESADV
Advance Ship Notice (856)
Product Activity
Product Activity
SLSRPT
Product Activity (852)
Performance
History
Performance History
N/A
N/A
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
33
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Appendix A: Collaboration Arrangement w/ Commitment
Processing
2.2 Sample Extended Collaboration Arrangement
The collaborative arrangement that follows is between ABC Stores, Inc., and XYZ Manufacturing
Co. Inc. The Collaborative Planning, Forecasting, and Replenishment (CPFR) arrangement will
be customized for each trading partner relationship.
2.3 CPFR Arrangement
ABC Stores and XYZ Manufacturing agree to collaborate in a key supply chain process
called Collaborative Planning, Forecasting, and Replenishment (CPFR). Their goal is to
increase mutual efficiencies and delight the end consumer through dynamic information
sharing, to focus on common goals and measures, and to remain committed to the CPFR
process. They recognize that there are many business processes as well as technological
and organizational changes that are required by this collaboration, and they commit to
apply resources to make these changes so that collaboration is effective and meets mutual
goals.
All communication between the partners will be governed by anti-trust regulations. Both
trading partners commit to absolute confidentiality in the use of information shared.
2.4 CPFR Goals and Objectives
Through Collaborative Planning, Forecasting, and Replenishment (CPFR), ABC Stores
and XYZ Manufacturing seek to reduce out-of-stocks, increase sales, reduce business
transaction costs, improve the use of capital (especially that involved in inventory), and
facilitate trade partner relationships.
ABC Stores and XYZ Manufacturing agree to focus on key results-oriented measures.
Goals for specific products are listed in the joint business plan, but the overall goals are
listed below. Time fences are established at each of the planning horizons that have
impact to the supply chain. (The following section includes metric values for an example,
and do not represent any particular values that are considered VICS benchmarks). An
eight week time fence will measure items having production impact, and a frozen zone at
two weeks monitors when routine order fulfillment can be accomplished without
expedition. Measures that have specific goals in the time interval between time fences are
shown below:
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
34
DC Replenishment Collaboration – Business Process Guide
Number of time fences
FINAL DRAFT
2
1 =Two Weeks
2= Eight Weeks
Time zone 1
If order forecasts change by
more than XX% within
time zone 1 send an alert.
Variance % greater than XX
will generate an alert.
Time zone 2
If order forecasts change by
more than YY%
Variance % greater than YY
will generate an alert.
14
Order forecasts frozen until
collaboration occurs
Frozen time zone days
Sales Forecast Accuracy
Greater than xx%
Greater than yy%
Order Forecast Accuracy
Greater than xx%
Greater than yy%
First Time Order Fill Rate
Greater than xx%
Greater than yy%
Order forecast fluctuation
between successive
forecasts for the same
period
Less than xx%
Less than yy %
General process measurement goals re-calculated periodically and not necessarily aligned
with the time fences are listed below:
In-Stock
Greater than xx%
Emergency Production Runs
Less than y per quarter
On Time Arrival
Greater than xx%
XYZ Manufacturing Inventory
Less than x weeks
ABC Stores Inventory
Less than y weeks of consumer sales
The performance against all of these measures will be the basis of the quarterly face-toface partner reviews. Details on these measures (e.g., scope, data source, responsibility
for maintaining, frequency of measure, frequency of reporting, construction of the
algorithm, unit of measure) will be attached to this agreement.
2.5 Discussion of Competencies, Resources, and Systems
Based on their earlier discussion of the competencies, resources, and systems that each
party brings to the partnership, ABC and XYZ agree to follow Collaborative Planning,
Forecasting, and Replenishment (CPFR) Scenario B. where the buyer has the ultimate
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
35
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
responsibility for the sales forecast, the seller has ultimate responsibility for the order
forecast, and the seller has ultimate responsibility for order generation.
2.6 Discussion of Order Forecast Scenario
In an advanced order forecasting relationship further discussion should be centered on
the processes for deriving the order forecast. Trading partners have options that include:
Buyer Order Reference Forecast- Buyer and supplier agree that the buyer will convert
the collaborative demand forecast into an order forecast that is reviewed and constrained
by timing and quantity components by both parties. A single order forecast is created
through this collaboration.
Seller Order Reference Forecast- Buyer and supplier agree that the supplier will
convert the collaborative demand forecast into an order forecast that is reviewed and
constrained by timing and quantity components by both parties. A single order forecast
is created through this collaboration.
Dual Order Forecast Approach- Buyer and supplier independently generate an order
forecast and compare the two for exceptions. A single order forecast is created through
this collaboration. The order forecast is reviewed and constrained by timing and quantity
components by both parties.
2.7 Definition of Collaboration Points and Responsible Business Functions
2.8 Collaboration Points
Collaboration points include the joint business plan, the sales forecast, and the order
forecast. Collaboration on the sales and order forecast will be driven by the following
item-level exception criteria and values:
•
Sales forecast exception criteria; retail in-stock less than xx percent, sales forecast
error greater than yy percent, sales forecast differs from same week prior year greater
than zz percent, change in promotional calendar or number of active stores
•
Order forecast exception criteria: retail in-stock less than xx percent, order forecast
error greater than yy percent, annualized retail turns less than goal (as noted on item
management profile table), entry of new event that impacts inventory/orders,
emergency orders requested more than z percent of weekly forecast.
•
Order forecast change alerts: Order quantity constraints, Order timing constraints,
quantity/timing constraints in the frozen zone.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
36
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
2.9 Responsible Business Functions
The following business functional units are impacted by and responsible for the success
of Collaborative Planning, Forecasting, and Replenishment (CPFR):
•
Buyer: merchandising/buying, forecasting, inventory management, logistics
•
Seller: sales team, planning/forecasting, logistics, production planning
2.9.1 Order Forecast Translation Variables
•
•
Algorithms or rules to be employed:
Example: The sales forecast will be divided by the case and/or ordering multiple and
rounded up to the next full multiple, then offset by the replenishment time as
specified in the Item Management Profile. This will be increased by the amount of
store inventories below the target level or decreased by the amount of store
inventories above the target level.
Components:
Product specific variables are listed on the Item Management profile.
2.9.2 Information Sharing Needs
Information sharing will be open and routine as needed to support Collaborative
Planning, Forecasting, and Replenishment (CPFR) processes. No information on
competitor activity will be shared. It is the partners’ expectation that communication will
be timely, and the collaboration information cycle time will be measured.
The CPFR Agreement Owners must resolve any issues that are deemed to be potentially
ongoing, determine the appropriate resolution and implement. It may be necessary to
adjust the collaborative arrangement to reflect revisions made. Making these adjustments
due to unforeseen facts, maintains the business partnership and viability of the program.
2.9.3 Areas of Information Sharing
•
Data necessary to measure success (common metrics) such as retail in-stock percent,
inventory, and forecast accuracy
•
Data necessary to identify exceptions in the sales and order forecast such as retain instock percent, inventory turns, and levels (retail, in transit, warehouse) sales and order
forecast accuracy, and supplier order fill rate
•
Data necessary to support decisions about exception items such as promotion,
planned inventory actions and other events that impact the forecast, Point-of-Sale
(POS) data, historical shipments, sales and order forecast, current item in-stock
percent retail, current inventory turns, number of valid stores
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
37
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
•
Item management profile, including item identifiers and logistics rules (rounding
rules, order minimum and multiples, and configurations)
•
Define the location hierarchy appropriate for the relationship. Trading partners may
want to consider mapping the ship to receive distribution network (Example – Buyer
DC’s A, B &, C pull from supplier DC A). This exercise will assist trading partners
with how they will want to format and share their order forecasts.
2.9.4 Frequency of Updates
Forecasts will be created and shared on a daily basis. Exceptions, supporting data, and
item management data will be shared daily, and metrics will be calculated and shared
monthly.
2.9.5 Method of Data Sharing
Where possible, data sharing will be accomplished using approved Collaborative Planning,
Forecasting, and Replenishment (CPFR) Extensible Markup Language (XML) messaging
specifications.
2.9.6 Recovery and Response Times
Response time for the Collaborative Planning, Forecasting, and Replenishment (CPFR)
system used by ABC Stores and XYZ Manufacturing should be no more than 30 seconds.
Steps have been taken to limit recovery time following a system fault to 12 hours.
2.9.7 Order Forecast Time Horizon
The order forecast will be XX (Days, Weeks, Months) into the future and will be
displayed in (Daily, Weekly, Monthly) periodicity.
2.9.8 Incorporate and Experiences of Previous CPFR Pilots
Based on their experiences with previous Collaborative Planning, Forecasting, and
Replenishment (CPFR) initiatives, each party will contribute a summary of its findings
and appoint a resource with previous CPFR experience to meet with the project team at
regular intervals.
2.9.9 Service and Ordering Commitments
One of the ways both companies expect to benefit from forecast collaboration is through
commitments to supply the forecast and to consume the forecast through orders (subject
to a range of deviation). The range of deviation will be reevaluated periodically. XYZ
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
38
DC Replenishment Collaboration – Business Process Guide
FINAL DRAFT
Manufacturing agrees to support the agreed-to forecast (at a frozen period of fourteen days)
with timely shipments within x percent of the forecast (measured weekly). In return,
ABC Stores agrees to consume the forecast through orders within y percent (measured
weekly). In the event that these limits are exceeded, the respective party will notify the
other as soon as possible and will determine a resolution plan. In recognition of the spirit
of this arrangement, both parties agree to commit the resources and systems necessary to
maintain the upstream planning processes, which will in turn allow the timely
identification and resolution of potential issues.
2.9.9.1 Resource Involvement and Commitments
The specific resources and activities shown in Figure 4.1.8 – 1 are necessary for successful
collaboration.
Figure 1: Resources/Activities Necessary for Successful Collaboration
Process:
Key participants:
Activities:
ABC Stores
XYZ
Manufacturing
Joint Business Primary: Category
buyer
Planning
And planner
Primary: Sales team
manager
and analyst,
Secondary: category
manager
Sales
Forecasting
Primary: forecasting
analyst. category buyer
and planner.
Primary: Sales team
manager
and analyst
Secondary: new store
planner
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
Category buyer and planner
meet with the sales team
manager, analyst, or category
manager quarterly to develop
the joint business plan as
defined in the process model.
Participants share responsibility
for outputs; the joint business
plan, and the item management
profile.
Based on joint business plan
and other inputs (POS data,
events, causal information), an
ABC forecasting analyst creates
the sales forecast weekly. The
following are responsible for
input that drives the forecast;
ABC category buyer, planner,
and new store planner, and the
39
DC Replenishment Collaboration – Business Process Guide
Process:
Key participants:
FINAL DRAFT
Activities:
ABC Stores
XYZ
Manufacturing
XYZ sales team manager and
analyst (responsible for
maintaining events and
communicating the joint
business plan). The ABC
category planner and the XYZ
sales analyst are responsible for
initiating the resolution of
exception items.
Order
Forecasting
Secondary: Category
buyer and planner,
forecasting analyst,
inventory rebuyer,
Primary: sales team
analyst, forecasting
manager.
Secondary: production
planner
logistics planner
Order
Generation
Secondary: Category
buyer
Primary: Inventory
planner
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
Based on the sales forecast,
order forecast impact events,
production capacity, inventory
strategies, and current
inventory position, the XYZ
sales team analyst and
forecasting manager create the
order forecast weekly. The
following are responsible for
input that drives the forecast;
ABC category buyer and
planner, forecasting analyst,
inventory rebuyer, and logistics
planner, XYZ sales team
manager, analyst, forecasting
manager, and production
planner. The ABC category
planner and XYZ sales analyst
are responsible for initiating
the resolution of exception
items.
Based on the frozen period of
the order forecast, the XYZ
inventory planner generates
orders. The need to generate
orders is evaluated daily.
40
DC Replenishment Collaboration – Business Process Guide
Process:
Key participants:
FINAL DRAFT
Activities:
ABC Stores
XYZ
Manufacturing
2.9.9.2
Resolution of CPFR Business Risk
Several specific situations may arise in extended CPFR Relationships. For example:
•
Supply cannot meet demand.
•
Compromise cannot be met on the timing of order/order forecast.
•
Compromise cannot be met on quantities associated with orders/order forecast.
•
Other.
In the event of a Collaborative Planning, Forecasting, and Replenishment (CPFR )
disagreement, the ultimate process owners will have the final say about the sales forecast,
order forecast, and order generation if intermediate efforts at resolution are not successful.
All other disagreements will be handled by a meeting of the leaders of the affected
functional areas, and ultimately the CPFR agreement owners.
2.9.9.3
CPFR Arrangement Review Cycle
This arrangement will be reviewed each year in January, and both companies will reaffirm
the effectiveness of the process by renewing the arrangements. Based on its success,
consideration should also be given to enhancing the CPFR program through
identifying areas where the new processes can be leveraged to provide additional
benefits not originally cited in the first year collaborative arrangement. In some cases,
success establishes a base for continual improvement.
VICS Collaborative Planning, Forecasting and Replenishment (CPFR®)
41