DYNAMIC MODELLING FOR EFFICIENT CONSUMER RESPONSE
Carmine Bianchi
Assistant Professor - University of Palermo - Faculty of Economics
Tel. +39.91.6254313 - 6254532 - E-mail: BIANCHI@UNIPA.IT
ABSTRACT
On February 13" 1996, Barilla S.p.A. - a major Italian food producer (of mainly pasta, biscuits and snacks) - in order
to face emerging competition from anonimous brands which were becoming more and more popular, particularly at
hard-discount stores, suddenly announced its new strategy not to operate anymore gift sales promotions and to
decrease retail prices on average by 10%. Such a strategy was justified by a sales increase as well as a marketing,
warehousing and financial costs decrease forecast. Even though successful results were obtained by Barilla, some
logistic and commercial problems arose downwards in the supply chain.
As the paper will show, with particular reference to pasta business, the above strategy affected policies adopted by
M.A.R., an Italian hyper and supermarkets medium-sized chain, which produced a sales and inventory instability, as
well as a profit decrease in the supply chain. It will be demonstrated how System Dynamics may support a deeper
comprehension of relevant feedback loops underlying management processes along the pipeline and a cooperation
between companies located in different segments of the supply chain. In this perspective, dynamic modelling and
simulation may be seen as a useful framework to implement Efficient Consumer Response (E.C.R.), a worldwide
programme involving both producers and distributors, to increase overall supply chain added-value.
1. Main "rules of the game" of pasta business in Italy and Barilla's low price strategy.
In about 1995, a market survey promoted in Italy by Barilla S.p.A. showed that 80% of its consumers was not
anymore interested in sales promotions based on gifts and that brand loyalty was mainly related to quality and price
. The results of this survey suggested Barilla to abandon gift promotion strategy (whose costs were about 7% of
sales revenues), to decrease retail prices on average by 10% and to keep unchanged quality standards. The
decision to adopt such policy has been called "the big event’ as it gave rise to a daring product repositioning which
is a rare example of how to sharply change the "rules of the game" in a consumer goods market. If we particularly
refer to the business of pasta, where Barilla mainly operates in the medium and top price segments , a price
decrease was expected to cause a higher brand loyalty, leading to a more than proportional increase in sales. In
fact, it was estimated that about 23% of Barilla sales in the medium price segment is made up by consumers who
are used to changing their favourite brand according to different conditions. Barilla's potential market is by far bigger:
if we also consider the lower and upper segments, the share of "non-loyal" Barilla's customers rises up to 60% of its
total sales. Itis not so easy, however, to increase customer loyalty. In fact, about 70% of "non-loyal" customers is
made-up by those who are particularly used to buying low price brands at hard-discount stores. The Italian pasta
market is characterized by a very strong competition: it is not only crucial to meet customers’ quality requirements
and to sell products on a relatively low price/quality ratio, but it is also becoming more and more important to
establish cooperative strategies with distributors. Improving formal and informal relationships with other companies
operating downwards in the supply chain is particularly significant for Barilla, whose area of activity is bounded in
the industrial segment, while a serious threat is coming from trade labels (e.g.: Rinascente, Esselunga, Coop), which
have been strongly growing in the last decade. Consequently, an aggressive price strategy would be likely to
generate positive events if Barilla could improve its contacts with medium-sized distribution companies and
particularly with those which are located in geographic areas where neither big trade companies nor hard-discount
stores hold market leadership. A more fragmented distribution structure in Italy is found in the South and Centre of
the country, where also M.A.R. (a medium hyper and supermaket chain) operates.
In the next pages the paper will show how unexpected Barilla's price reduction affected MAR's policies which
affected, in turn, supply chain added value dynamics.
1. Main feedback loops related to Barilla's low price strategy and to M.A.R.'s reactions.
Through an on-line information system Barilla is able to support its customers’ (distributors) reorder policy with the
aim to reduce inventory, set-up and administration costs along the supply chain, to improve overall added value.
When Barilla, in order to fix diminishing profits due to strong market competition, suddenly decreased its “on-shelf"
retail price and sale price to distributors, it suggested MAR to immediately raise its supply orders as a higher
demand was expected (negative loop 1-fig.1). Nevertheless, in the next weeks after the big event, MAR on the
contrary reduced its supply orders, as Barilla products retail sales decreased. Such unexpected phenomenon was
caused by two main related reasons: 1) a mixture of consumers’ astonishment,
puzzlement and also mistrust (in spite of
massive Barilla's "reassuring" advertising) on
the oppor-tunity to choose a "discounted"
brand whose la-bel has always been a
synonimous of higher pri-ce and quality; 2) a
lower on she/fsales support by MAR, caused
by a drop ofits relative unit margins on
existing inventories (loop2). In other
Fig.1: Main feedback loops
words, MAR was forced to sell at a lower retail price those inventories which had been purchased
= io
—s am "aa" before the big event, i.e at a higher unit cost. The above phenomena
eee mrudeee aus) v4 eventually led to lower Barilla profits, which reinforced the need of low
rer “Earn a prices and, consequently, perpetuated MAR's reactions (loop 3). Such
dynamics may be related to the Accidental Adversaries archetype.
coc . Positive loop dominance lasted
Fig. 2-a: Main causal determinants of
supply chain added value and of Barilla's
and MAR's profits
grow, because of
two main reasons:
1) MAR's unit
margin on Barilla
products restore
(loop4), which im-
plied a stronger
on shelf
promotion; 2)
delayed effects
Fig:2-b: Main sectors of
the model related to materials and orders flows in the supply-chain
4. Tel esting
nngeteny core
oa eating Uarioveney
yoy FSR a
ee)
20:
Fig. 3: Main results of a first simulation run (input values) - Fig. 4: Main results of a second simulation run
for a few weeks, until old inventories were sold. Then, Barilla sales at MAR's shelves started to of massive Barilla's
advertising. After another delay, competitors reduced their prices too. Such reaction produced three sequential
effects: a) a higher relative MAR's unit margin on Barilla products (loop 5-a), which gave rise to a stronger sales
support "on shelf", i.e. higher Barilla sales (loop 3 again); b) a lower average price perceived by consumers, which
led to a small increase in potential market (loop 5-b) that also strengthened loop 3; c) system's reset on anew
equilibrium (after MAR depleted other medium price brand inventories) which switched again relative unit margin
and other master variables to their initial values (left-hand side of fig. 3 and 5). So the big event main outcome, in the
case studied, has been too weak a demand increase, if compared to price reduction. If Barilla increased its profits,
because of a sharp promotion costs cut, both MAR and the whole chain (Barilla + MAR) margins would drop (left-
hand side of fig.3 and 5).
A second simulation
run suggests that (other
con-ditions being
equal) bet-ter results
(right-hand si-de of fig.
3 and 5) could have
been achieved by both
companies, if they
would have concerted a
policy to increase more
final sales and to
reduce interface costs.
The first goal could
have been pursued
through a higher and
faster unit purchase
cost reduction allowed
by Barilla to MAR,
leading to a higher on
shelf support to Barilla
product sales. The
second goal could have
been pursued by a
more concerted
inventory and reorder
policy aimed at
Fig. 5: Comparative results from two model's simulation runs, reducing financial and
based on actual poli- cies (on the left) and on a concerted reorder, administration costs.
price and "on shelf" sale support policy
CONCLUSIONS
In this perspective, System Dynamics offers a useful framework to implement Efficient Consumer Response (E.C.R.)
, aworldwide programme involving both producers and distributors, whose goal is to increase overall supply chain
added-value and customer service.
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