A WINERY DYNAMIC MODEL FOR
“PRODUCT PORTFOLIO” MANAGEMENT
Habib Sedehi Carmine Bianchi
HELP Auditing Informatico Assistant Professor
Via Antonio D’Achiardi, 31 Universita degli Studi di Palermo Facolta di Economia
00158 Rome (ITALY ) Istituto di Scienze Economico Aziendali
Viale delle Scienze 90128 Palermo (ITALY)
E-mail Sedehi@help.it
E-mail Bianchi@cuc.unipa.it
Abstract
On behalf of the “product portfolio” analysis through Boston Consulting Group (B.C.G.)
approach and System Dynamics methodology analysis of a wine production firm, a dynamic
model of a company has been developed.
The winery model is designed for different functions of the firm, taking in to account Resource
& Production , Economic & Financial and Market subsystems.
Even though the model has been focused to evaluate different market strategies in new product
launching, it can be used also to support simulating policies concerning different management
functions of the firm.
The model will be described schematically and a series of simulation results will be presented,
particularly in evaluating company policies in new product launching , so to put in evidence
how system dynamics could be useful in strategic analysis.
Background
In a previous paper (Bianchi C. - Sedehi H., 1995) it has been sketched a dynamic modeling
approach to support decisions concerning resource allocation in order to better manage
"product portfolio" and new product launching in an industrial firm. The paper demonstrated
how strategic control management, for new products launching and monitoring of those which
already exist, is possible not only through accounting models, but also through System
Dynamics methodology. Both approaches are indeed useful in “product portfolio"
management; however, each of them may better satisfy different information requirements.
Nevertheless, still today, also in the Italian context, only B.C.G. matrix (Hax A.C., 1984),
(Morton P, 1987) and other "product portfolio" accounting-derived models are mainly used.
The paper underlined the characteristics and limits of the two approaches. What was concluded
is as following:
“traditional approaches may be useful in identifying key-variables relating to the relevant
processes. However, these variables should be connected one another, usually according
to non-linear relations, and possibly with other "input" variables, that could identify
management system levers and/or environmental external constraints.”
System Dynamics & B.C.G.
System Dynamics may allow to point out different policy levers on which it is possible to act in
order to affect product performance and to understand feedback loops underlying financial and
economic processes. Figure 1 depicts a general framework concerning product-mix dynamics
according to the B.C.G view. u 7 1
It is possible to distinguish at least four groups of policy levers, corresponding to the 4 P's
concerning Marketing mix (Kotler P, 1986); each of them will be differently used according to
the particular growth stage of the product. For example, a mature (cash cow) product will
require a strategy based on large volumes (an adequate promotion) sold at a low price, a high
standardization in production and distribution(place) process; on the contrary, a new product
(question mark) may require a strategy based on strong promotion efforts and on flexible and
selective distribution policies.
ae
STARS PRICE MARKS
PRODUCT
PROMOTION
is
4 PRODUCT
Fig. 1 A general frame work of product-mix dynamics according to B.C.G. prospective
Moreover, Figure 1 emphasizes how cash flows coming from mature products may give rise
(after a delay) to new activities in product renewing and/or new product launching which
cause, after another delay, an increase of the Jevel of investments in question marks. Launching
of question marks may give rise, after another delay, to an increase of product cash flows, i.e.:
to an increase of the level stars, that will become - after a given delay - cash cows.
Consequently, the main problem, in "product portfolio" management, becomes to assure a
proper balance between several classes of products. This objective may be pursued through
financial flows allocation generated by mature products to development and support activities.
The first ones mainly concern question marks, the latter ones mainly relate to cash cows and
stars.
In synthesis it can be asserted that it is of a critical importance for decision makers to
understand trade-offs between the two kind of investment (supporting existing products and
new product launching) and to figure out different possible scenarios that may follow to the
pursuing of several policies according to different sets of external input variables. In this
context the understanding of delays relating to the path of each product (or group of products)
during different stages of its life-cycle, become of crucial importance.
The Winery Firm : “Corvo”
The above problem has been faced in a winery firm, Casa Vinicola Duca di Salaparuta S.p.A.
(hereinafter “Corvo”), a multi-product company located in Sicily and operating on a world-
wide market.
Today Corvo "product portfolio" market strategy is mainly supported through B.C.G.
methodology having a rough and static approach. Moreover the B.C.G matrix does not allow
Corvo decision makers to define when to launch a new product and how many resources to
invest.
The need of a more flexible tool as a support in "product portfolio" management is also
increased by the difficulty in assessing some key policy parameters (such as product "recipe" or
even the introduction time of new products) which are particularly relevant in product
418
launching policy as well as in product mix management. Dynamic modeling may particularly
help decision makers to understand possible different outcomes relating to different hypotheses
concerning a given set of external parameters. It may also allow decision makers to make more
explicit product capacity and external (i.e.: grape availability) constraints and their possible
effects on "product portfolio" management.
“Corvo” Dynamic Model
A dynamic model has been sketched in order to make more explicit, different possible policies
that could be pursued in "product portfolio" management in Corvo.
‘Second_new“FDT_investments
iest_new PD¥investment_allocation
Perc_NCF_to_new_PDT_investments
a
Introd_yehe_of_new_POT
Tot_revenues_PDT_1
Monthly_revenues_PDT_1
Tot_revenues_PDT_2
Fig. 2 New product launching sub-system
The model consists of three main sub-systems:
1) resources & production; 2) economic & financial; 3) new product launching(market).
The first one embodies production and all physical resources quantities (grape, unfinished
wine, workers. ...). The second one concerns three main different points:
a) cash flow policy;
b) cost management (purchasing, production, manpower, etc.), concerning resource
acquisition and development;
47a
c) product revenue management (product mix setting, etc.).
The third sub-system implies a distinction between two different new product cycles (Figure2).
The flow "New product monthly investments" depends on cash flows from existing products
and the percentage of allocation to development activities. The input parameter "Introduction
time of new products" controls the flow of investments to the first or to the second cycle: this
means that after he introduction time for the first cycle has been finished, the flow of new
investments is devoted to the second cycle.
Current revenues (and cash flows) of launched products depend on the level of development
investments accumulated during the introduction time (ie.: "First_new_PDT_investments")
and on the stage of the product during its life-cycle in the period of simulation (i.e.: auxiliary
"PLC_1_stage_weight").
Results
Figure 3 and 4 give an example of graph reports that is possible to obtain from “Corvo”
model.
More particularly, Figure 3 illustrates the detailed monthly costs (a) and monthly net company
profit (b) while Figure 4 illustrates monthly cash flows and total investments in new products
development (a) and the two product life-cycles together with the dynamics of revenues from
the set of products existing from the beginning through the simulation time (100 months) (b).
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Fig. 3 Detailed costs and net company profit Fig. 4 Cash flow and new products monthly revenues
References
Bianchi C, Sedehi H, 1995; Dynamic modeling for “product portfolio” management and new
product launching, System Dynamics Conference Proceedings, Tokyo.
Hax, AC.; and N.S. Majluf 1984, Strategic Management: An Integrative Prospective
Englewood Cliffs, N.J.: Prentice-Hall.
Kotler, P. 1986. Marketing Management, Isedi, Torino
Morton, P. And R. Léffler, and K.P. Wiedmann System Dynamics Review 3 (n°. 2 Summer
1987).
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