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Inventories represent stocks of goods necessary for operations of sales or manufacturing in a company. These allow to the companies meet their sales levels, while representing an opportunity to the cost control and the decision-making. This paper presents an optimization approach to minimize the inventory costs in probabilistic inventory models of independent demand. The approach has been validated for set the policy optimal of inventories with probabilistic demand within a company that markets disposable products. The established policy aims to minimize the inventory costs by using the standard deviation of the historical data, the mean deviation of forecast errors and the mean deviation of the historical data. For the determination of the economic order quantities, three types of products were selected, taking historical sales data. Likewise, different forecasting methods were used, selecting the one that minimizes the mean squared error for the forecasted demand. The proposed methodology is practical and easy to use in companies where inventories have probabilistic and independent demand. Also, the proposed approach allowed optimize the costs related to holding costs, ordering costs and safety stock costs. [ABSTRACT FROM AUTHOR]

This paper aims to present a Business Intelligence dashboard with a goal-oriented approach. A case study was developed taking as context of analysis a Cuban college. The requirements of the dashboard were modeled by using aspects of social modeling and the language i*. The models obtained allowed analyzing the goals, tasks and resources necessary to accomplish the requirements of the dashboard, as well as to align the metrics of the dashboard with the goals of the decision-maker. The resulting dashboard allowed visualizing and monitoring the performance of students to support decision-making at a tactical level. The contribution of this paper is a goal-oriented approach for modeling the requirements of dashboards and for extracting the metrics of dashboards aligned with the goals of decision-makers. [ABSTRACT FROM AUTHOR]

Investors need reliable information for decision-making, so it is important to measure the quality of public information disclosed by quoted companies. This paper advances in the measurement of disclosed information using the multiple correspondence analysis methodology to reduce the number of traditionally used variables, resulting in three variables: i) disclosure of accounting policies and criteria, ii) disclosure of financial information and iii) disclosure of the board assessment. Using three these dimensions, we characterize and classify the analyzed companies according to their information disclosure. [ABSTRACT FROM AUTHOR]