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El Dr. Eduardo López Soriano y el Dr. Federico Trigos Salazar desarrollaron los modelos para optimizar la toma de decisiones en la aceptación de pedidos.

Dr. Eduardo López Soriano and Dr. Federico Trigos Salazar developed models to optimize decision making in order acceptance.

El Dr. Eduardo López Soriano y el Dr. Federico Trigos Salazar desarrollaron los modelos para optimizar la toma de decisiones en la aceptación de pedidos.

La investigación de la coautoría del profesor de EGADE Business School fue incluida en este libro sobre aplicaciones de la analítica en América Latina y economías emergentes.

The co-authorship research of the EGADE Business School professor was included in this book on data analytics applications in Latin America and emerging economies.

La investigación de la coautoría del profesor de EGADE Business School fue incluida en este libro sobre aplicaciones de la analítica en América Latina y economías emergentes.

Dr. Federico Trigos Salazar, research professor at EGADE Business School, and Dr. Eduardo López Soriano, CEO of the consulting firm NCA Europa, developed mathematical models to help manufacturing companies make strategic decisions with the objective of profit maximization in order acceptance.

Research by coauthor EGADE Business School professor presents the latest contribution to the theory of order acceptance. Findings have been published in a compilation on analytics applications in Latin America and emerging economies, published by CRC Press, a globally renowned publisher specializing in technical books.

Their findings were published in a coauthored article, “Prescriptive Analytics in Manufacturing: An Order Acceptance Illustration”, which was included as one of the chapters of the book Data Analytics Applications in Latin America and Emerging Economies, a compilation of cases edited by Dr. Eduardo Rodríguez, a professor at the University of Wisconsin-Stevens Point, and published by CRC Press of the Taylor & Francis group.

In their collaboration, the authors returned to the make-to-order manufacturing models they had presented in a research paper published in the International Journal of Production Research in 2015, and offered a new contribution to the order acceptance theory by extending them to make-to-stock manufacturing scenarios.

Dr. Trigos Salazar stressed that the book in which they participated seeks to expose that analytics are not only for major corporations and markets, but also for organizations of any size and developing markets.

“The important point is that we not only address the Business Analytics approach, but also facilitate its application to solve issues that are very specific to our region. SMEs comprise the majority of companies in Latin America. Our chapter mentions that the models we are proposing can be resolved with tools that are accessible to large companies, but we also point out that there are guides available to small and medium-sized firms that enable them to achieve a competitive advantage as well,” added the member of the EGADE Business School’s Strategic Research Group on Business Analytics.

Regarding the scope of their work, Dr. López Soriano commented that it applies to companies that have just one highly specialized machine, where demand normally exceeds capacity, forcing them to decide which orders to accept and which orders to reject or defer for the future.

“Very often, those in charge of production scheduling base their planning on intuition, common sense and prior experience, ignoring real data, which leads to suboptimal decisions being made. The application of our mathematical models guarantees that an optimal solution will always be found for order-acceptance dilemmas,” he explained.

In order to reach a decision on which orders will be accepted, and whether they will be produced partially or in full, Dr. López Soriano explained that the first step is to define the sort of manufacturing required - order or stock - since there is a different model for each type.

“The lot size of each product ordered also needs to be taken into consideration, since this might imply not just configuring the machine, but also periodical readjustments such as calibration, addition of refrigerants and lubricants, etc. This is common when tools and similar products are being manufactured. They all take time and cost money, and should therefore be incorporated into the decision-making process Finally, the total time available for manufacturing orders becomes the limiting factor. In order to evaluate, compare and distinguish alternatives systematically and consistently, the total benefit, understood as the expected revenue minus the total costs involved, will be the target to be maximized in the decision model in order to reach a final order-acceptance strategy,” he specified.

If you are interested in finding out more about Dr. Trigos Salazar and Dr. López Soriano’s work, you can order the book Data Analytics Applications in Latin America and Emerging Economies online from CRC Press.


Keywords: Research, Manufacture, Decision Making, Business Analytics, Prescriptive Analytics, Order Acceptance, Make To Order, Make To Stock, CRC Press
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