Generación de escenarios de demanda para productos de innovación

Objetivo: Generar escenarios de demandas simulando el ciclo de vida del producto, cuando este no tiene información histórica o registro de ventas. Métodos: Se utilizan los modelos de difusión de la Curva Logística, Gompertz y Bass, junto con simulación de Montecarlo. Resultados: Se obtienen diferentes escenarios de demanda dado el comportamiento de los parámetros según su distribución de probabilidad. Conclusiones: Se utilizan los modelos de difusión para la generación de escenarios de demanda, como aproximación del potencial de realización de la demanda. Implicaciones prácticas: Los escenarios obtenidos se tomarán como entradas a modelos de programación matemática para la planificación de cadenas de suministro rápidas para productos de innovación.&nbsp

Life cycle prediction for agile supply chains: a comparison of methods

The aim of this paper is to compare the performance of several product life cycle models on an empirical dataset from a lighting products retailer to inform inventory decisions for products that are in different life cycle stages: introduction, growth, maturity, or decline. Bass diffusion curves, piece-wise linear curves, and polynomial curves, fourth order polynomial curves are used to predict the life cycles of 2,618 products. We identify which products need an efficient and which require an agile supply chain design. We provide recommendations for how much inventory to keep, especially for products that are in the decline stage

Hacia la mejora del manejo de inventarios caso de estudio en una organización sin fines de lucro : proyecto de investigación

Nowadays, companies around the world, even non-profit ones should keep control of their operations and make improvement efforts in order to remain competitive in a highly demanding market. One of the relevant operations within an organization is the supply chain management, where a significant portion of total costs is associated, specifically the ones relating to inventory management. This paper presents a case of study focused on the inventory management of a nonprofit organization, particularly in one of the bookstores that belong to this organization located throughout Latin America. The actual system and policies for inventory management are analyzed along with the purchasing decisions. A root cause analysis of the principal problems in inventory management is presented, followed by an improvement plan. This plan is compounded by two stages: first, a centralized system for the control of inventories is implemented using available technology combined with Statistic Control Charts; second, a technical forecasting method is employed to help in the decision making process of purchasing. And an inventory management policy is proposed, with a particular focus on the key items sold by the bookstore. Results were validated through interviews with the actors of the process

Analogous Forecasting of Products with a Short Life Cycle

Managing a supply chain for products with a short life cycle, like fashion apparel, high-tech, personal computers, toys, CD’s etc., is challenging for many companies (Fisher and Raman, 1999). Because the life cycles of these products are too short for standard time- series forecasting methods (not longer than one – two years), an important way of overcoming the challenges of managing supply chains for such products is to find appropriate forecasting methodologies. The standard forecasting methods require some historical data, which are often unavailable at the time when the forecasts are being performed for products with a short life cycle (Lin, 2005). The method described in this article allows forecasters to use life cycles of similar, analogous products to arrive at the initial forecasts for the product(s) at hand

On the stochastic inventory problem under order capacity constraints

We consider the single-item single-stocking location stochastic inventory system under a fixed ordering cost component. A long-standing problem is that of determining the structure of the optimal control policy when this system is subject to order quantity capacity constraints; to date, only partial characterisations of the optimal policy have been discussed. An open question is whether a policy with a single continuous interval over which ordering is prescribed is optimal for this problem. Under the so-called "continuous order property" conjecture, we show that the optimal policy takes the modified multi-$(s,S)$ form. Moreover, we provide a numerical counterexample in which the continuous order property is violated, and hence show that a modified multi-$(s,S)$ policy is not optimal in general. However, in an extensive computational study, we show that instances violating the continuous order property are extremely rare in practice, and that the plans generated by a modified multi-$(s,S)$ policy can therefore be considered, for all practical purposes, optimal. Finally, we show that a modified $(s,S)$ policy also performs well in practice.Comment: 30 pages, submitted manuscrip

A Nonlinear Growth Analysis of Integrated Device Manufacturers' Evolution to the Nanotechnology Manufacturing Outsourcing

With the increasing cost of setting up a semiconductor fabrication facility, coupled with significant costs of developing a leading nanotechnology process, aggressive outsourcing (asset-light business models) via working more closely with foundry companies is how semiconductor manufacturing firms are looking to strengthen their sustainable competitive advantages. This study aims to construct a market intelligence framework for developing a wafer demand forecasting model based on long-term trend detection to facilitate decision makers in capacity planning. The proposed framework modifies market variables by employing inventory factors and uses a top-down forecasting approach with nonlinear least square method to estimate the forecast parameters. The nonlinear mathematical approaches could not only be used to examine forecasting performance, but also to anticipate future growth of the semiconductor industry. The results demonstrated the practical viability of this long-term demand forecast framework