Insight from industry Procurement of agricultural products using the
CPFR approach
Xiao Fang Du
Wuhan University of Technology,Wuhan,China
Stephen C.H.Leung
Department of Management Sciences,City University of Hong Kong,Hong Kong
Jin Long Zhang
School of Management,Huazhong University of Science and Technology,Wuhan,China,and
K.K.Lai
Department of Management Sciences,City University of Hong Kong,Hong Kong
Abstract
Purpose–This paper seeks to apply a framework of collaborative planning,forecasting and replenishment(CPFR)to develop a procurement model for agricultural products.
Design/methodology/approach–Considering the biological nature,seasonality and perishable characteristics of agricultural raw materials and products,the paper revises the CPFR reference model.Then,the paper constructs a n-tier CPFR procurement model by extending a two-echelon supply chain to a multi-echelon supply chain and incorporating upstream suppliers in the supply chain.Moreover,the concept of collaborative transportation management(CTM)is integrated into the n-tier CPFR procurement model.Finally,a case study is analysed and the efficacy of the proposed model is also validated.
Findings–Thefinding suggests that CPFR approach is applied in the procurement of agricultural products.The case results show that the service level is increased and inventory variance is reduced.The proposed model can thus improve the accuracy of forecasting and reduce inventory losses. Originality/value–The paper offers a useful insight into procurement of agricultural products.The proposed model is a useful development for the agricultural industry in implementing CPFR in the future.
Keywords Supply chain management,Business planning,Forecasting,Procurement,Agricultural products
Paper type Research paper
1.Introduction
Industries manufacturing products from agricultural resources are developing rapidly but complexities in supply chains of products often result in economically unviable cost structures.It seems that many companies in the agriculture related industries have started worrying about their current competitive positioning since profits of agricultural products are among the lowest.One reason could be that agricultural products,such as eggs,milk,meat,cake,vegetables,fruits, seafood,etc.deteriorate easily and their shelf life is often very short.Prices of agricultural products are time-sensitive,which means that the price decreases dramatically as the shelf life of the product comes to an end.On the other hand,a shortage of saleable agricultural products at any given point of time may result in significant loss of revenue because the demand is not carried forward.Therefore,it is crucial that inventories of agricultural products be properly managed.However,absence of an efficient mechanism to respond quickly to market conditions and an equally efficient procurement mode are bottlenecks in profitable m
arketing of agricultural products. Conventional procurement systems have generally encountered problems,such as difficulties in sharing information as part of procurement management, empiricism in procurement decision-making,unstable relationships between purchasers and suppliers,the impossibility of tracking procurement and over-purchasing resulting in waste arising from decay of agricultural products. These factors have led to slow reactions to changes in demand,poor adjustments to demandfluctuations,probable
The current issue and full text archive of this journal is available aldinsight/1359-8546.htm
Supply Chain Management:An International Journal
14/4(2009)253–258
q Emerald Group Publishing Limited[ISSN1359-8546] [DOI10.1108/13598540910970081]
The work described in this paper was fully supported by a Strategic Research Grant from City University of Hong Kong(Project No.7001909).
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overstocking or product shortages,and so on,which in turn have seriously influenced the profits from the sale of agricultural products(Hansen,2001).
The challenging issues are how to make sure that perishable products produced by farmers or food manufacturers can be bought by consumers in perfect condition,and how to deal with shortages and problems of overstocking.T o deal with these problems,we apply collaborative planning,forecasting and replenishment(CPFR)as a framework to develop an agricultural product procurement system.The objective of this study is to develop a model for agricultural products procurement management so that the precision of agricultural products demand forecasts can be improved by making collaborative forecasts based on information sharing.The benefits are that purchasers can reduce inventory losses and save management costs.
CPFR is proving to be one of the most successful mechanisms in transforming relationships between partners into a win-win situation where customer satisfaction,costs and revenues can all improve simultaneously(Sheffi,2002). One of the main differences between CPFR and other collaborative arrangements is that under CPFR,both parties are informed of exceptions,and this generates collaboration mechanisms aimed at resolving these exceptions.A second difference is the ability of the exception engine to point out discrepancies when operating at a large scale–i.e.with a large number of
stores and many stock keeping units.In early 1998,through initial voluntary interindustry commerce standards(VICS)association initiatives,the cross industry team presented the standard process model and technology standards for collaborative planning,forecasting,and replenishment(CPFR,n.d.).
However,owing to many characters of agricultural products,the CPFR process needs to be improved to incorporate these characteristics when it is applied to agricultural products procurement management.
The paper is organised as follows.After this introductory section,a procurement model for agricultural products using CPFR is proposed,and a n-tier CPFR model by extending a two-echelon supply chain to a multiple-echelon supply chain is constructed.The concept of collaborative transportation management(CTM)is integrated into the model.In section 3,a case study is discussed.Section4concludes the advantages of the proposed agricultural products procurement system.
2.The framework of the proposed model
2.1The modified CPFR process model
The standard CPFR process model is much complicated and there are some barriers in its implementa
tion.Moreover,the agricultural industry has its own characteristics,such as the internal biological,seasonal,unstable and perishable factors, etc.;it is necessary to make improve the CPFR process according to the characteristics of the agricultural industry and agricultural products when CPFR is applied to agricultural products procurement management.spring framework表达式assign
The main modifications from the standard model are listed in the following and the modified CPFR model is shown in Figure1:
1The proposed model considers distribution forecasting and producers’capacity forecasting,which are carried out by upstream partners;the standard model does not
consider this.Agricultural products are usually planted by
“a single farmer produce mode”while they are ultimately
sold to the consumer by supermarkets or trade-markets.
Agricultural products entering the supermarkets move
from the planting place to produce collectors or food
manufacturers to wholesale markets and then the
supermarkets.Supplies of agricultural products are
usually not steady in terms of price and quantity on
account of changes in climate,fluctuations in markets and
variations in distribution capacity,etc.Therefore,
distribution and production capacity forecasting are very
important to agricultural industry.
Step3of the modified model(Figure1)is the
collaborative sales forecasting,including demand
forecasting,supply forecasting and distribution
forecasting.Given the need for quick response,supply
and demand forecasting are carried simultaneously by
upstream and downstream enterprises,which shorten the
time available for forecasting.The CPFR group sends the
forecast data to the CPFR server where the data is
integrated together to serve as evidence for collaborative
forecasting.In collaborative forecasting,differences in
data inputs provided by different members can be
adjusted by a collaborative forecasting programme(Du,
2005).Some forecasting errors are inevitable.However,if
the error is large,the result could be serious in terms of its
net effect for the supply chain as a whole.So,collaborative
forecasting assorts the diverse inputs from different
members in order to reach commonly acceptablefigures.
The key lies in integrating the complex forecasting
technology and using the diversified information for the
benefit of the partners.When it is brought into effect,
exceptional incidents that influence forecasts are revealed
and resolved in time.
2The modified process model is simplified in steps for exceptions’management because the standard model is
complicated.In the collaborative sales forecasting phase,
exceptions of supply capacity and demand planning can
be adjusted and exceptions identification and solutions
may be managed jointly,after order forecasting.For
maintaining the freshness of the product,purchasing of
agricultural products is frequent and diversiform and yet,
the procurement process must be as simple and prompt as
possible.
3Considering the frequent and uncertain distribution of agricultural products,CTM is applied to the purchasing
process and distribution forecasting is also added,in order
to assign distribution resources effectively.
2.2The proposed n-tier CPFR agricultural products
procurement model
CPFR applied between buyer and seller is the two-tier CPFR, while in business operations,supply-chain relationships are often multi-echelon and comprise upstream and downstream enterprises.It is,therefore,more relevant to study n-tier CPFR among a multi-echelon supply chain in the agriculture sector.
Collaborative transportation management(CTM)plays an important role in enlargement of CPFR.The objective of CTM is to reduce or eliminate inefficiencies in the transportation process(for example,time,inventory,space, errors and distance)through collaboration(Esper and Williams,2003).After agricultural products procurement with CPFR is combined with CTM,the business process will 254
change.Firstly,CTM develops a logistics strategy and plans that involve logistics,merchandising,distribution,retail store operations,information systems and agricultural products suppliers.Secondly,CTM develops the purchasing systems and communications needed to share supply chain information such as point of sale,forecasts,purchase orders,shipment schedules and status,performance reporting and measurement.Thirdly,CTM executes supply chain optimisation focusing on quality and time definite shipments while minimising total logistics costs.
Below we discuss the agricultural product procurement process of CPFR combined with CTM,using the example of n -tier CPFR among supermarket,wholesale markets or food manufacturers and agricultural products collection organisations (Figure 2).
The agricultural products procurement workflow based on the above n -tier CPFR is presented as follows (Figure 3):1Development of collaborative arrangement and preparation of
joint business plan .Participants need training and education to understand CPFR.The overall scope of the pilot is defined to ensure that the process maps are understood and used.This step is extremely important to maintain the integrity of the process.The front-end agreement helps to establish the benchmarks that define the roles,responsibilities and timelines.
The planning phase needs to select the categories and the products that would participate in the pilot.The partners assemble their internal marketing plans during the period,review historical shipments,data,the revised category management strategy and anything else the team thinks can help in the planning process.An aggressive merchandising plan is put together and agreed upon for a given quarter.Subsequent quarterly plans are developed in advance of each shipping period.In addition,the CPFR working group is established by the supermarkets,wholesalers or manufacturers and products collection organisations.
2
Collaborative sales and order forecast generation .The supermarket makes the demand forecast.The demand forecast has two components –the base forecast and the promotional forecast.The base forecast is primarily generated from historical data captured in their continuous replenishment program (CRP)system,whilst the promotional forecast is developed along with the category and merchandising plan.The products collection organisation makes the production capability forecast and distribution forecast.The wholesaler or manufacturer makes sales forecast and distribution forecast.After the forecasting is developed,it is known to all members through the CPFR server where forecasting algorithms
Figure 1The modified CPFR process
model
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make the collaborative sales forecast and adjust for exceptions arising from any member.The collaborative sales forecast is converted to order forecast when it rolls into the freeze period.The freeze period would allow the manufacturers to incorporate the order forecast into
upstream supply chain processes if enough trading partners adapt the CPFR process.
3Order generation and execution of shipments.Order generation and execution of shipments can be divided into the following steps:
Figure2Agricultural products supply chain
partners
Figure3Agricultural products procurement
workflow
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.Collaboratively schedule production and delivery.
Based on the forecast received,each manufacturer in
the partnership should provide a capacity
commitment to the forecast for that specific
production line.The working group will balance a
final order commitment against initial capacity
commitments.Using that information,in addition
to production capability data,the group will generate
work orders for each manufacturer in the supply
chain.Each manufacturer then processes these work
orders individually.From their internal information,
each manufacturer generates a delivery data.A
complete timeline for production could be
generated.The timeline here assumes no inventory
is available and the delivery data at each stage of the
process has been calculated by evaluating the process
times provided by each of the manufacturers.
.Exceptions management.Manufacturers’delivery datum generated from the process of collaboratively
scheduling production will be compared to delivery
status provided by each manufacturer on a regular
basis.If delivery status for products cannot meet the
specified product delivery datum,an exception will
occur.Exceptions may be handled in a variety of
ways.Most exceptions will befirst made available to
the trading partner who is initially impacted by the
exception.For example,the exception is triggered
when actual demandfluctuates or the business plans
change.The changes have to be considered significant
for adjustments.Collaboration software will
automatically advise the users of significant
variations in forecast or demand.At the same time,
the working group would negotiate with the
appropriate trading partners by phone,e-mail,fax,
etc.
.Execution of shipments.The working group manages the order process.They receive and monitor the
forecast and the product availability data.Shipments
to downstream company are based on order
generation.
3.Case study
In the agricultural industry,CPFR application in the Nabisco and Wegmans Food Markets is a successful case.Nabisco is a major international manufacturer of biscuits,snacks and premium grocery products.Nabisco markets products in the USA,Canada and more than85other countries around the world.Wegmans is a58-store supermarket chain in New Y ork and Pennsylvania.The family-owned co
mpany,founded in 1916,is recognised as an industry leader and innovator. The primary goal of the pilot was to test the CPFR concept and related processes.Both Nabisco and Wegmans wanted to validate the model to see if CPFR was a proposition that could be expanded to other businesses and trading partners. The pilot can be viewed as being split into two phases.The first phase was limited to22Planters nut items,representing all can and jar items stocked by Wegmans;bag and canister snack items were excluded.All58Wegmans retail outlets participated right from the pilot’s inception.The second phase of the pilot was expanded to include the shipping
period.The same22Planters nut items from phase one were included,as well as20Milk-Bone pet snack items.
Performance of the implementation was measured by key measures which are case-fill to Wegmans DC;case-fill from Wegmans DC to retail;inventory turns at Wegmans DC;
forecast accuracy;sales growth for the category,planters brand,and private label;category and planters brand profits.
The data sources for the metrics came mainly from the internal supply-chain and POS systems within Wegmans and Nabisco.There has been dramatic improvement in results against key metrics.Sales inc
rease for the Planters brand was especially dramatic at53per cent.Sales increases were supplemented with lower inventory and an improvement in forecasting.On the operations side,service level to stores increased from93to97per cent(service level to stores¼(12(cuts/(demand-cuts)))£100)(Figure4),and days of inventory declined by2.5days(Days of supply¼(on hand inventory/weekly movement)£7)(Figure5).This resulted in a15per cent increase in overall profit dollars.
These positive results have led both Nabisco and Wegmans to decide to extend the timeline for this pilot and to expand its scope to include Milk-Bone pet snack products.Both companies are also establishing pilots with other trading partners.
In the above case,application of CPFR approach is successful in agricultural industry in terms of sales growth, inventory reduction,forecasting accuracy improvement, reduction in spoilage,and reduction or elimination of other supply chain inefficiencies.However,some products of Nabisco Inc.,such as biscuits and nuts,are long-lifespan commodities and compared with fresh products,are less time-Figure4Service level to
stores
Figure5Days of
supply
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