Nowadays, one of the most challenges faced by companies, especially the large retail chains, is to manage the growth of their organization, in a structured and sustainable way.
One of the many ways to deliver this growth is to improve the performance of the current operation and explore opportunities to expand the business.
Unfortunately, the quest for operational improvement does not work as a panacea dosed equally, curing all problems and achieving the same results for everyone. Quite the opposite, operational improvement performance is consisted to plans, goals and isonomic actions, which must take into account the characteristics and needs of each individual.
In this case, a tool commonly applied to manage strategically this portfolio is the BCG matrix.
In certain organizations, knowledge can get lost over time. In addition, changes and evolutions in the market can de-characterize the initial conditions, assumptions, and classification.
Thus, the present work aims to present a proposal that evaluates the relevant factors that explain the current classification, considering current variables, applying the induction of decision tree by classification rules.
The model will provide criteria to understand the relevant factors used in this classification so that the groups and their elements can be evaluated, allowing more effective actions to be taken on the stores in order to improve their performance or to decide to close the operation .
In this treadmill, it is expected to apply the same methodology to extract rules from the desired target groups (star and cash generators) in order to obtain a market model, with only environmental variables, that can mitigate the risk of failure to choose new store locations.
