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While firms use automated machine learning algorithms in their demand planning processes, human judgment continues to feature in these processes. This research examines two methods of integrating m...

BACKGROUND The 'demand planning guidelines' issued by the Federal Joint Committee are meant to ensure nationwide delivery of healthcare in Germany. The calculatory variable used to reflect the actual care situation in relation to a given geographical entity is referred to as 'adjusted supply rate'. Against the backdrop of demographic change and already existing problems in replacing retiring physicians, the question arises as to how future dermatological care will evolve at the regional level. METHODS Using current 'demand planning guidelines' as well as nationwide data on the location of dermatologists and current and projected population figures at the county level, the adjusted supply rate - in terms of dermatological care - was calculated for the year 2035 based on three possible scenarios (scenario 1: 100 % replacement of retiring dermatologists; scenario 2: non-replacement of one dermatologist per planning area; and scenario 3: non-replacement of two dermatologists in rural areas). RESULTS While scenario 1 shows an actual improvement in regional dermatological care in certain areas between 2014 and 2035 (n = 3 no longer undersupplied), the more likely scenarios 2 and 3 are potentially associated with considerable regional undersupply. CONCLUSIONS Taking demographic change into account, it is safe to assume that the geographical heterogeneity of dermatological care will increase. This requires greater effort not only in terms of demand planning but also with regard to offering alternative methods of delivering healthcare and intercommunal cooperation. In this context, the objective will be to adapt healthcare delivery to changes both in demography as well as in the plans young physicians have for their own lives.

This paper attempts to explore a new insight to both industrialized and growing economies by demonstrating a digital-driven creative disruption in the forest-based bioeconomy which is beginning to replace its conventional and narrow concept of a forest-blinded economy. Notwithstanding the potential broad cross-sectoral benefits to both industrialized and growing economies, natural environments and locality constraints and the incessant challenge of distance have impeded balanced development of this economy. However, driven by digital solutions the economy has taken big steps forward in recent years. Digitalization has enabled real-time end-to-end supply chain visibility, improved delivery accuracy, stock level optimization and alignment with demand planning. These have led to digital ecosystem collaboration and a transparency crossover industrialized and growing economies worldwide. Thus, creative disruptive platform has emerged by embracing digital solutions. By means of an empirical analysis focusing on the noteworthy business activities at the forefront of both upstream and downstream of the chain, this paper demonstrates a transforming stream observed in the forefront of a forest-based bioeconomy chain. This research thus explores a new insight common to both industrialized and growing economies in constructing a creative disruption platform by embracing digital solutions.

Explosive demand for wireless internet services has posed critical challenges for wireless network due to its limited capacity. To tackle this hurdle, wireless Internet service providers (WISPs) take the smart data pricing to manage data traffic loads. Meanwhile, from the users' perspective, it is also reasonable and desired to employ mobile data traffic management under the pricing policies of WISPs to improve the economic efficiency of data consumption. In this paper we introduce a concept of cost efficiency for user's mobile data management, defined as the ratio of user's mobile data consumption benefits and its expense. We propose an integrated cost-efficiency-based data traffic management scheme including long-term data demand planning, short-term data traffic pre-scheduling and real-time data traffic management. The real-time data traffic management algorithm is proposed to coordinate user's data consumption to tailor to the pre-scheduled data traffic profile. Numerical results demonstrate the effectiveness of cost efficiency framework in indicating and motivating mobile user's data consumption behavior. The proposed management scheme can effectively motivate the user to adjust its data consumption profile to obtain the optimal data consumption cost efficiency., 23 pages, 13 figures

This deliverable addresses a methodological approach to developand assess intermodal potentials within supply chains under real market conditions. For thatintermodal planning tools are developed and tested using real data. The approach is basedon the real intermodal services that are established within the CLUSTERS2.0 clusters andshipment orders as provided by shippers. A matching algorithm was developed in order toidentify possible matches to use existing intermodal services. “For the potential analysis “virtual” intermodal services were introduced on lanes with major volumes. The intermodalplanning tool is part of the massification concept and supports shippers collaboration toexploit intermodal potentials with their supply chain through collaboration and coordination. Clusters 2.0developed and applied an intermodal planning environment that is capableof assessing the potentials of collaborative demand planning of shippers as addressed in themassification concept. Making use of large-scale realistic demand data covering the area ofthe Clusters 2.0clusters, a significant potential of existing and newly “massification”services could be identified. Our study provided a potential of up to 60% ofall transportorders with distances higher than 250 km that can be operated by intermodal transport.The approach developed is supporting the activities as addressed in the massificationworkshops together with collaborating shippers.

El presente artículo expone el estado crítico de los inventarios de papelería y su repercusión negativa en los costos de las oficinas en una entidad bancaria en Colombia. En el presente documento se investigó y analizó cómo es el manejo del sistema de inventarios de una entidad bancaria y se encontró que su planeación de la demanda para generar las ordenes de pedido es ineficiente por la manera empírica como la realizan, ya que los encargados de esta gestión en las oficinas solicitan el pedido de papelería al Almacén del Banco de acuerdo con sus propias estimaciones. A través de este documento, se presenta una propuesta para la planeación de la demanda, mediante el uso de modelos de pronóstico cuantitativos, los cuales llevarán a minimizar los excesos o faltantes de papelería que se vienen presentando en las oficinas, con la finalidad de eliminar los sobre costos ya sea por pedidos extemporáneos o por destrucción de sobrantes de papelería. This article exposes the critical state of paperwork inventories and their negative impact on office costs in a Colombian bank. In the present document, the management of the inventory system of a banking entity was investigated and analyzed and it was found that its demand planning to generate the inventory orders is inefficient in the empirical way as they do it, since the managers in the offices request the stationery order to the Bank Warehouse according to their own estimates. Through this document, a proposal for demand planning is presented, through the use of quantitative forecasting models, which will lead to minimize the excesses or missing paperwork in the offices, in order to eliminate the cost overruns either by extemporaneous orders or by destruction of paperwork surpluses.

Las compañías que manejan productos con fecha de vida útil muy cortos generan que los inventarios estén en constante rotación con niveles de stocks muy altos, es ahí donde el pronóstico de la demanda es una herramienta de vital importancia. El objetivo de estudio es analizar y describir el comportamiento de una empresa de alimentos empaquetados conocidos como snacks, comenzando con desarrollar la planificación del pronóstico de demanda, mediante el análisis de los datos históricos de las ventas de los últimos meses, encontrando inicialmente los materiales de mayor rotación con el método de inventarios ABC, para que de tal forma se pueda obtener una mayor asertividad en el plan de ventas, logrando así, una optimización de los recursos a lo largo de la cadena de suministros. Para finalmente dar una visión más clara a las demás áreas que para este caso va principalmente a la de producción. La contribución de este proyecto de estudio va orientada principalmente para la satisfacción del cliente, generando y logrando un mayor impacto en el mercado, para que final, como herramienta de pronósticos sea tomada para la toma de decisiones en la cadena de suministros, además poder tener tiempos de reacción oportunos a las demandas futuras sin generar un aumento en los costos. The life date generate inventories that are in constant companies that handle products with a very short useful rotation with very high levels of stocks, this is where the demand forecast is a vitally important tool. The objective of the study is to analyze and describe the behavior of a packaged food company known as snacks, beginning with the development of demand forecast planning, by analyzing the historical data of the sales of the last months, initially finding the materials of greater rotation with the ABC inventory method, so that a greater assertiveness can be obtained in the sales plan, thus achieving an optimization of resources along the supply chain. To finally give a clearer vision to the other areas that in this case goes mainly to the production. The contribution of this study project is mainly aimed at customer satisfaction generating and achieving a greater impact on the market, so that as a forecasting tool it is taken to make decisions in the supply chain, in addition to having time of timely reaction to future demands without generating an increase in costs

El presente caso trata sobre una mediana empresa manufacturera del sector farmacéutico con 80 años de presencia en el mercado de los medicamentos veterinarios en Colombia. A lo largo de su trayectoria, la empresa ha tenido un crecimiento sostenido que le ha dado reconocimiento en el sector; hace 10 años, como lineamento estratégico, las directivas programan un incremento en las ventas con el fin de tener mayor participación en el mercado y orientan sus esfuerzos a la combinación de estrategias comerciales, promocionales y a la ampliación del portafolio de productos. Sumado a lo anterior, la forma de operar de la compañía es de carácter reactivo, lo que conlleva a que su proceso de manufactura no se planifica, generando un riesgo de faltantes muy costoso. Estos dos aspectos conllevan a un problema en manejo de inventarios, incumplimiento en la entrega de pedidos, afectación en la imagen de la compañía y al impacto negativo en las finanzas. Ante este panorama se decide revisar las operaciones al interior de la empresa, el diagnóstico de esta actividad propone la planificación de la producción dentro de la cadena de suministros, lo que permite la optimización de las operaciones de producción, distribución, y satisfacción de pedidos. Para lograrlo se abordan modelos matemáticos que permiten analizar la demanda y determinar la cantidad de recursos requeridos para ejecutar la producción lo que garantiza la disminución de los niveles de inventarios, la eficiencia en el proceso y la reducción de costos. The present case concerns a medium-sized pharmaceutical manufacturing company with 80 years of presence in the veterinary pharmaceutic market in Colombia. Throughout its trajectory, the company has had a sustained growth that has given it recognition in the sector; 10 years ago, as a strategic guideline, the directives programmed an increase in sales in order to have greater participation in the market and directed their efforts to the combination of commercial and promotional strategies and the expansion of the product portfolio. Added to the above, the way the company operates is reactive, which means that its manufacturing process is not planned, generating a risk of costly shortages. These two aspects lead to a problem in inventory management, failure in the delivery of orders, affect on the image of the company and the negative impact on finances. The diagnosis of this activity proposes the planning of production within the supply chain, which allows the optimization of production operations, distribution, and order satisfaction. To achieve this, mathematical models are used to analyze demand and determine the amount of resources required to execute production, which guarantees lower inventory levels, process efficiency and cost reduction. La présente affaire concerne une entreprise de fabrication pharmaceutique de taille moyenne comptant 80 années de présence sur le marché des produits pharmaceutiques vétérinaires en Colombie. Au cours de sa trajectoire, la société a connu une croissance qui lui a valu une reconnaissance dans le secteur. Il y a 10 ans, les directives étaient programmées pour augmenter les ventes afin de participer davantage au marché et orienter leurs efforts vers la combinaison de stratégies commerciales et promotionnelles et l'expansion du portefeuille de produits. Outre ce qui précède, le mode de fonctionnement de la société est réactif, ce qui signifie que son processus de fabrication n’est pas planifié, ce qui crée un risque de pénuries coûteuses. Ces deux aspects entraînent un problème de gestion des stocks, un échec dans la livraison des commandes, une incidence sur l’image de la société et un impact négatif sur les finances. Le diagnostic de cette activité propose la planification de la production au sein de la chaîne d'approvisionnement, ce qui permet d'optimiser les opérations de production, la distribution et la satisfaction des commandes. Pour ce faire, des modèles mathématiques sont utilisés pour analyser la demande et déterminer la quantité de ressources requise pour exécuter la production, ce qui garantit des niveaux de stock inférieurs, une efficacité des processus et une réduction des coûts.

Background: An established South African fast-moving consumer goods (FMCG) manufacturer, Company A, sought to address an underperforming supply chain through an attempt to improve demand planning accuracy. A need arose within the organisation for an assessment of the impact of this intervention. A literature gap was also identified, taking into account the limited number of relevant case studies that exist in academic literature. Objectives: The primary objective of this study was to establish whether or not the demand planning interventions of Company A had a positive impact on the performance of the supply chain under investigation. In support of this primary objective, the secondary objectives were to determine and compare the pre- and post-intervention demand planning activities and performance of Company A. Method: A case study research design was used focusing on Company A. The researcher sourced evidence through a secondary quantitative data analysis and primary data collection through interviews with personnel directly involved in the demand planning process at Company A. Results: From mean absolute percentage error calculations, it was found that the focal company’s demand planning process intervention had reduced the errors in demand forecasting for all classifications of stock keeping units analysed. Conclusion: The demand planning interventions applied by Company A had a positive impact on the overall supply chain performance. A positive relationship was found between a well-informed, team-based and technology-assisted approach to demand planning and improved forecasting accuracy within an FMCG company.

The trend of digitalization has led to disruptive changes in production and supply chain planning, where autonomous machines and artificial intelligence gain competitive advantages. Besides, the satisfaction of customers’ wishes has reached top priority for demand-driven companies. Consequently, companies implement digital applications, for instance neural networks for accurate demand forecasting and optimized decision-making tools, to cope with nervous operational planning activities. Since planning tasks require human-machine interaction to increase performance and efficiency of planning decisions, this analysis focuses on forms of interaction to determine the right level of collaboration. The paper outlines various levels of interaction and analyses the impact of human reactions in the context of an industrial demand planning algorithm use case at Infineon Technologies AG conducting a behavioral experiment. The results show that a variance in the levels of human-machine interaction has influence on human acceptance of algorithms, but further experiments need to be conducted to outline an overall framework.

In densely populated and rapidly ageing countries like Singapore, the demographic pressures on urban environments will increasingly demand planning and design responses. The inclusive neighbourhood that integrates active ageing strategies is proposed as a pragmatic model that serves the needs of current generations of older adults and generations in the future. While the inclusive neighbourhood promotes the ideals of diversity and social equity as shared values for the maintenance of social cohesion, the strategies and programmes associated with active ageing attend to physical, mental, and emotional well-being. Together, the concepts integrate qualities that address life satisfaction. Secondary research was undertaken to include the current literature on inclusive neighbourhoods, active ageing programmes, health and ageing, neighbourhood design, planning guidelines and standards, and case studies. The purpose of the research was to propose design strategies from a transdisciplinary perspective.

In the machining process of modern digital workshops, the tool life is an important parameter index that influences the development of tool demand planning, cost accounting, and cutting parameter setting. In view of the highly nonlinear relationship between tool life factors and tool life, particle swarm optimization BP neural network technology was used to predict tool life. Firstly, the relationship between tool life and tool wear, the influence factors of tool life and the significance of tool life prediction are analyzed. Then, a tool life prediction algorithm based on particle swarm optimization BP neural network was established. Finally, the proposed algorithm is simulated and tested. Experimental results show that compared with the original BP neural network prediction algorithm, the proposed algorithm has fast convergence rate and high prediction accuracy.

В статье рассматривается и приводится классификация цифровых решений, технологий и инструментов, которые могут быть применены в различных процессах и функциях цепочки поставок и основных сферах движения материального потока в рамках цепочки поставок. Анализируются перспективы цифровой трансформации в управлении цепочками поставок, а также обосновывается целесообразность перехода к сетевому подходу в управлении цепочками поставок, позволяющему выстроить более гибкую, прозрачную и надежную цепочку поставок. Выявляются и структурируются возможные цифровые технологии, такие как машинное обучение, облачные технологии, интернет вещей, блокчейн, продвинутая аналитика, в каждой из областей цепочки поставок, и на этой основе разрабатывается и предлагается модель на основе балльнорейтингового метода оценки, позволяющая компании на начальном этапе выявить приоритетное цифровое решение для внедрения. Предложенная модель апробирована автором для одной из сфер управления цепочкой поставок складирования, для этого были выделены ключевые процессы и рассмотрены возможные цифровые альтернативы в каждом из выделенных процессов. В заключении автор подчеркнул преимущества и недостатки предложенной модели и перспективы дальнейших научных исследований по данной теме., The article is dedicated to provide and classify digital solutions, technologies and tools that can be applied in various processes and functions of the supply chain management and the main areas of the material flow within the supply chain. Also, the possibilities of digital transformation in supply chain management are analyzed, and the feasibility of a transition to a network approach in supply chain management that makes it possible to obtain a more flexible, transparent and reliable supply chain is substantiated. Possible digital technologies such as machine learning, cloud technologies, Internet of Things, blockchain, advanced analytics are identified and structured. On this basis, a model is developed and proposed on the basis of a scorerating evaluation method, which allows the company to identify at an early stage a priority digital solution for implementation. The proposed model was tested by the author for one of the supply chain management areas warehousing. Key processes were identified and possible digital alternatives were considered in each of the selected processes. In conclusion, the author emphasized the advantages and disadvantages of the proposed model and the prospects for further research on this topic., №2 (2019)

Despite the improvements in statistical forecasting, human judgment remains essential in business forecasting and demand planning. Typically, forecasters do not rely solely on statistical forecasts; they also adjust forecasts according to their knowledge, experience, and information that is not available to the statistical models. However, we have limited understanding of the adjustment mechanisms employed, particularly how people use additional information (e.g. special events and promotions, weather, holidays etc.) and under which conditions this is beneficial. Based on a UK-retailer case study, we first establish how event-driven software is used. We build on this by laboratory experiments that simulate a typical supply chain forecasting process. We provide past sales, statistical forecasts (simple baseline forecasts or statistical forecasts that include promotional effects) and qualitative information about past and future promotional periods. We find that when adjusting, forecasters tend to focus on model-based anchors, such as the last promotional uplift and the current statistical forecast, ignoring past baseline promotional values and additional information about previous promotions. The impact of contextual statements for the forecasting period depends on the type of statistical predictions provided: when statistical forecasts with promotional effects are presented, people tend to misinterpret the provided information and over-adjust, harming accuracy.

As is the case for the core business, the demands for Facility Management have risen massively over the last years, especially given the fact that statutory requirements and increasing user demands with regards to comfort, security, and efficiency have changed. Facility Management is subject to an increased professionalisation, raising questions about necessary financial and human resources in order to ensure interruption-free and legal operation. Owners und operators of bigger real estate urgently need tools and aids for workload planning. These are only available at a limited capacity in Facility Management (FM).Given these developments, the authors were commissioned to work out a guideline on behalf of GEFMA (German Facility Management Association e.V.), creating the task force “Personalbemessung im FM”. This task force was accompanied by a research project which was financially supported by the Arbeitsgemeinschaft Technischer Abteilungen deutschsprachiger Hochschulen (ATA). The aim of this guideline is to show approaches for resource planning and to give a short overview over existing proceedings. The focus is set on maintenance and operation of buildings and technical equipment. The aim is to provide a scientifically established procedure, based on existing approaches by owners and operators, which will enable them to calculate the necessary resources.

Applied Sciences 9(24), 5567 - (2019). doi:10.3390/app9245567, Published by MDPI, Basel

In today’s fast-moving world, a company´s ability to align with changes in the market is becoming a major competitive factor. Demand forecasting form the basis of all supply chain planning and is a process that companies often fail to recognize as a key contributor to corporate success. Different contexts and market dynamics creates different challenges for companies to overcome in order to have an efficient forecasting process, matching demand with supply. This master thesis looks at the whole forecasting process, also called forecasting management, at a decentralized global company to identify the main challenges within the process and propose recommendations on how to overcome them. The research is based on a single case study where the forecasting process is investigated using four different dimensions: Functional Integration, Approach, Systems and Performance Measurements. The study identified twelve challenges in the forecasting process where a majority can be connected to issues within information sharing and lack of support in the process. Based on the identified challenges, eight improvement suggestions where developed to target the challenges and improving the process for a decentralized global company. I dagens snabbt utvecklande och växande landskap så är ett företags förmåga att anpassa sig till marknadens behov en betydande konkurrensfaktor. Säljprognoser utgör grunden för all planering inom försörjningskedjan och är en process som företag ofta inte erkänner som en viktig bidragsgivare till företagets framgång. Olika marknadslandskap och förutsättningar skapar olika utmaningar för företag att bemästra för att kunna bedriva ett effektivt prognosarbete och matcha efterfrågan med utbud. Detta examensarbete tittar på hela prognosprocessen, även kallad prognoshantering, hos ett decentraliserat globalt företag för att identifiera de viktigaste utmaningarna i processen och föreslå rekommendationer om hur man kan övervinna dem. Forskningen bygger på en enda fallstudie där prognosprocessen undersöks utifrån fyra olika dimensioner: Funktionell integration, strategi, system och prestandamätningar. Studien identifierade tolv utmaningar i prognosprocessen där en majoritet kan kopplas till utmaningar inom informationsdelning och brist på stöd i processen. Baserat på de identifierade utmaningarna utvecklades åtta förbättringsåtgärder för att övervinna utmaningarna och förbättra processen för ett decentraliserat globalt företag.

The services provided by driving schools, on the market of all other services in the traffic domain, have very specific features. They are an interactive process that takes place between the participants of the driving school on the one hand and the technological process on the other. This process should ultimately lead to the training of candidates, and it takes place in the interaction of users (ie candidates) of services and service providers. The success of such a traffic-technological process is reflected in the speed of service delivery and ultimate user satisfaction with the overall effects of service, ie training. For longer-term demand planning, the factors affecting the market of driving school services in the Republic of Croatia are researched, such as regulatory measures, the impact of demographic trends, and the methodological and statistical forecasts analyze the collected or processed data.

The decline in the number of clothing manufacturers and the effect of globalisation have contributed to complexities in estimations and the scheduling of demand, as well as lead time management in the South African clothing industry. This article explores demand planning factors affecting the South African clothing industry, with specific reference to Gauteng. The study was necessitated due to demand planning challenges facing the South African clothing industry as well as economic factors which contribute to inaccuracies in clothing demand planning. The study makes an impact in the garment production factories of Gauteng in South Africa and adds to the philosophy of demand planning practices. It uncovers key factors affecting demand planning practices in the Gauteng clothing industry, South Africa. The study is explorative and descriptive in nature and it uses SPSS to analyse data. The findings revealed that there were factors affecting how demand planning practices were conducted in the clothing industry. The factors that have a significant influence on clothing demand planning include the scheduling of the manufacturing of customers’ orders, planning for fashion clothes, the use of the POS system, clothing imports, estimating future clothing requirements, recession and the effect of the late arrival of clothes. Therefore, clothing industry stakeholders should take these factors into consideration when planning for their demand to ensure customer needs can be fully met, thus improving the performance of the clothing industry.

Peak load rate(i.e., maximum daily flow/average daily flow) has not been considered for industrial water demand planning in Korea to date, while area unit method based on average daily flow has been applied to decide capacity of industrial water treatment plants(WTPs). Designers of industrial WTPs has assumed that peak load would not exist if operation rate of factories in industrial sites were close to 100%. However, peak load rates were calculated as 1.10~2.53 based on daily water flow from 2009 to 2014 for 9 industrial WTPs which have been operated more than 9 years(9-38 years). Furthermore, average operation rates of 9 industrial WTPs was less than 70% which means current area unit method has tendency to overestimate water demand. Therefore, it is not reasonable to consider peak load for the calculation of water demand under current area unit method application to prevent overestimation. However, for the precise future industrial water demand calculation more precise data gathering for average daily flow and consideration of peak load rate are recommended.

Transportation logistics of wood is one of the important links of wood processing industry, and its high efficiency and low cost directly affect the survival of enterprises. Timber transportation and inventory are the two most important parts of its logistics cost. Based on the field investigation of Jingnan Town Processing Park and the analysis of its geographical location and existing industrial scale, this paper puts forward three constructive suggestions: use the combination of multimodal transportation and land and water transportation to reduce transportation costs, integrate transportation resources through third-party logistics outsourcing, and use material demand planning to optimize inventory.

Digitalization is accelerating and changing much in our lifestyles and ways of working. In the construction and building sector, this phenomenon is currently gaining acceptance through the Building Information Modeling (BIM) method. As an integral planning method for improving the quality of planning, construction and operating processes, BIM requires a starting point that is defined by demand planning. This paper focuses on recording demand planning digitally and generating it autonomously for basic planning. The aim is to provide planners with a BIM model that is generated early from user-oriented needs with in-depth information and enables considering sustainable and health planning aspects in the future. As a result, BIM and the open BIM data exchange format Industry Foundation Classes (IFC) are used to create a BIM-Model (3D Model) based on user needs, which are recorded by a web application. Thereby planners will be provided with a valuable starting and orientation basis that considers important user requirements. In doing so, maximum user satisfaction and quality will be achieved. Furthermore, communication and participation of users in the planning process will be promoted.

Public participation has become a conditio sine qua non when planning infrastructure projects. However, current research is concerned with one-time experiments and can not elucidate long-term effects of iterated consultations. Our argument is that consultations have learning effects over time. We test our argument using the German procedure for electricity grid demand planning as a case. Using dictionary coding and a quantitative analysis, supplemented by a qualitative text analysis, we show that participants get better in framing their contributions by using the “right” keywords. Hence, consultations evolve over time and improve in terms of the output legitimacy they generate.

A good and interconnected demand and supply planning (D&SP) is essential for firms, as it will give better allocation of resource and enabler to stay competitive. The basic and simple applications of D&SP are forecasting and aggregate planning which mainly used in big corporations, but less in small and medium enterprises. The research was a case study in a small firm in Indonesia, which started as small and family-owned company, but can enjoy the benefit of simple demand and supply planning to enhance its cost and productivity. Despite main application of D&SP in every production environment, no vast research has been done in the last couple of decades. The study and the case are thus, a refreshment on how application of D&SP still relevant. The case study examined seven common forecasting tools for demand planning side and exercised classical chase and level aggregate planning strategy for the supply planning side. It explored three possible scenarios and recommended a better scenario with 3% cost saving for the company.

El presente trabajo se trató de una comercializadora de hidrocarburos de Colombia, que se enfrenta a nuevos retos en la implementación de proyectos para expansión, basado en nuevas plantas de abastecimiento que construyen para dar cobertura a diferentes clientes del país. Estos nuevos proyectos traen consigo los estudios previos de factibilidad para el cálculo de las capacidades de almacenamiento y equipos requeridos para las ventas, que realizan con poca información recolectada. Por medio de esta investigación se determinó la importancia de analizar e implementar diversos métodos cuantitativos de pronóstico, aplicados al tipo de demanda, encontrando que existen variables y conocimientos específicos, que dependen no solo de la ubicación de una nueva planta de abastecimiento sino también de los tipos de clientes, proyecciones de crecimiento y normas establecidas tanto de la compañía como de los entes que las regulan. Con lo investigado se tienen las bases para establecer capacidades operativas, mejorando la atención oportuna de los clientes. Al tener una solución efectiva se está generando nuevas oportunidades que a futuro se ven reflejadas para la compañía, en el aprovechamiento eficientemente de las nuevas plantas desde el inicio de su operación. The present work was about a Colombian hydrocarbons trading company, which faces new challenges in the implementation of expansion projects, based on new supply plants that are built to cover different clients in the country. These new projects bring with them the previous feasibility studies for the calculation of storage capacities and equipment required for sales, which they perform in a very basic way based on cost structure and demand review. Through this research the importance of analyzing and implementing various quantitative methods of forecasting, applied to the type of demand, was determined, finding that there are specific variables and knowledge, which depend not only on the location of a new supply plant but also on the types of clients, growth projections and established norms of both the company and the entities that regulate them. With the investigation, we have the bases to establish operative capacities, improving the timely attention of the clients. Having an effective solution is generating new opportunities that in the future are reflected for the company, in the efficient use of new plants from the start of its operation.

In order to ensure the effective supply of integrated energy system (IES) materials, on the basis of analyzing the current research status of integrated energy system, using physical quantity analysis method, mathematical method and theoretical analysis method, combined with the characteristics of the system engineering materials requirements, the study will explore the IES material demand planning frame and scientific planning methods.

International audience; This chapter analyzes the current structure of the demand planning in Agro Peru SA and the potential of rethinking the demand planning structure and decisions on the whole supply chain performance. Using a methodology that combines the CSAR framework for rethinking supply chain strategies, a multi-criteria Analytic Hierarchy Process method, and a Sales and Operation Planning methodologies. The present work proposes a diagnosis of demand planning operations, strategy and a management plan to improve them. First, the chapter presents the company and the agricultural sector in Peru. Second, the methodological framework is described. Third, the main results are presented and discussed. Results indicate that it is necessary to elaborate two internal projects to improve the forecast of demand and thus reduce inventories without affecting sales.This book reports the best practices that companies established in Latin America are implementing in their manufacturing processes in order to generate high quality products and stay in the market. It lists the technologies, production and administrative philosophies that are being implemented, presenting a collection of successful cases of studies from Latin America. The book describes how the tools and techniques are being integrated, modified and combined to create new technical resources for assisting the decision making process for better economic performance in manufacturing companies. The efforts deployed for assisting the transformation of raw materials into products and services are described. The authors explain the main key success factors or drivers for success of each tool, technique or hybrid combination approach applied to solve manufacturing problems.

Advancements in semiconductor industry have resulted in the need for extracting vital information from vast amount of data. In the operational process of supply chain, understanding customer demand data provides important insights for demand planning. Clustering analysis offers potential to identify latent information from multitudinous customer demand data and supports enhanced decision-making. In this paper, two clustering algorithms to identify customer demand patterns are presented, namely K-means and DBSCAN. The implementation of both algorithms on the prepared data sets is discussed and their performance is compared. The paper outlines the importance of deciphering valuable insights from customer demand data in the betterment of a distributed cognitive process of demand planning.

Tactical S&OP process can be visualized like in Fig. 3.18. In this big chapter, we bring to you a lot use cases which can help in your maturity assessment, design, and implementation.

In this chapter we will highlight our key observations about process measurement and exemplify them on demand planning and forecasting processes.

We have seen that operational planning was introduced in the companies when monthly tactical S&OP process was not granular enough to solve demand-supply-finance imbalances driven by product type, brand, channel, and sales area. Operational planning has a short-term horizon focus and an objective to extract the best value from available assets. Let us see how we may understand operational planning.

In this chapter we explain key functional aspects of Cloud SAP IBP on HANA. You will learn about what applications to use for which planning type. We bring examples of how to model in SAP IBP processes, organization to operate in global organizations. We highlight key elements of data modeling which set technical foundation of the planning. We explain functionality which supports “what-if” simulations and collaboration.

Jugendliche in unserer heutigen Gesellschaft werden sehr stark daran gemessen, ob sie bestimmte gesellschaftlich vorgegebene Bildungs- bzw. Ausbildungsziele erreichen oder nicht. Damit stellt die Schulausbildung für Jugendliche eines der wesentlichen Bewährungsfelder dar. Sie ermöglicht einerseits Entwicklungschancen, kann jedoch auch mit vielfältigen Problemlagen verbunden sein. Die vorliegende Studie richtet die Aufmerksamkeit auf die Problemlagen der Jugendlichen in der Sekundarstufe I und untersucht diese mit Blick auf die Bewältigungsstrategien der Jugendlichen sowie den damit verbundenen pädagogisch-psychologischen Beratungsbedarf. Dazu wurden 1155 Jugendliche aus acht Hauptschulen und fünf Gymnasien (jeweils 5. bis 8. Schulstufe) in Österreich befragt. Ergänzend dazu liegen Daten von 798 Eltern der befragten Jugendlichen vor. Die Ergebnisse zeigen, dass sich die Jugendlichen am meisten durch Lern- und Leistungsprobleme belastet fühlen. Absolut gesehen wünschen sich 21% der Jugendlichen zusätzliche Hilfe und Unterstützung. Insbesondere leistungsschwache Jugendliche mit Migrationshintergrund in der Hauptschule sowie leistungsschwache Mädchen mit Migrationshintergrund im Gymnasium bringen überzufällig häufig das Bedürfnis nach mehr Beratung und Unterstützung zum Ausdruck. (DIPF/Orig.), Adolescents in our society are very much judged by whether they achieve certain socially determined educational goals or not. School education is one of the essential 'probation fields', and allows development opportunities, but is also connected with challenges for the youth of today. This study focused on the challenges in dealing with school and investigated the problems of students in lower secondary schools, their coping strategies, and their counseling needs. 1155 Austrian students in eight general secondary schools and five academic secondary schools (5th until 8th grade) were interviewed. In addition, data from 798 parents has been made available. The results showed that most of the students feel stressed by learning problems. Overall, 21% of students would like additional help and support, in particular underachieving students with a migration background in general secondary schools and underachieving girls with a migration background in academic secondary schools. (DIPF/Orig.)

With the notion that the transformation of the forest-based bioeconomy in recent years provides insightful suggestions not only on the bioeconomy, but on business innovation, this paper conducts an empirical analysis of the transformation and attempts to extract suggestions for a digital-solution-driven, disruptive business model in the digital economy. Notwithstanding the potential broad cross-sectoral benefits, the natural environment, locality constraints, and incessant challenge of distance have impeded the balanced development of the bioeconomy. However, driven by digital solutions, the bioeconomy has taken big steps forward in recent years. Digitalization has enabled real-time, end-to-end supply chain visibility, improved delivery accuracy as well as stock level optimization and alignment with demand planning. The advancement of e-commerce has also led to the elimination of distance between both the upstream and the downstream of the chain. This paper demonstrates a transformative stream observed at the forefront of the forest-based bioeconomy chain. An empirical analysis focusing on the core business activities at the forefront, both upstream and downstream of the chain, is conducted. A new insight common to all industries in the digital economy is thus explored for constructing a creative disruption platform by embracing digital solutions. peerReviewed

With the development of space techniques, more and more missions using both satellite resources and ground cloud resources are being conducted in situations such as sea rescue, earthquake relief or some emergencies. However, lacking of an integrated framework makes this kind of missions inefficient and makes it hard for dynamic adjustment. In this paper, we design an integrated framework, involving demand planning, joint task planning, task assignment, resources allocation and dynamic adjustment. This paper aims to integrate all the relevant techniques and provide a complete framework for rapid space-ground joint mission planning and in-time adjustment in space information networks. We also propose a case study of three investigative missions to help you understand this framework.

BACKGROUND Knowledge of blood utilization can assist clinicians in directing patient blood management (PBM) initiatives and can facilitate demand planning by blood services. We describe a national study of red blood cell (RBC) utilization in England and North Wales in 2014. STUDY DESIGN AND METHODS All hospitals that are supplied with blood components by NHS Blood and Transplant (NHSBT) were asked to provide data on the age and sex of all recipients of transfusions of RBCs, and the clinical indication for every unit transfused, for two separate weeks in 2014. Clinical indication categories were derived from those used in previous studies in an English region. Completeness of data collection was checked against NHSBT issue and wastage data. RESULTS Data on 46,111 RBC units were collected, representing 73% of all RBCs issued by NHSBT during the weeks surveyed. A total of 67% of RBC units were transfused for a medical indication, with 27 and 6% being transfused for surgical and obstetric/gynecologic indications, respectively. For comparison, figures from a study in the North of England in 2009, on which this national study was based, showed that 64% of RBCs were transfused to medical patients. All but 20 units could be ascribed to a broad clinical heading, for example, “gastrointestinal bleeding.” CONCLUSION Our findings confirm the previous regional finding that the percentage of RBC units that are transfused to surgical patients in England and North Wales is now much lower than for medical patients and suggest that PBM initiatives should now focus on medical patients.

Demand planning for industrial's electricity consumption is an important factor to efficiently plan the generation and distribution of power utilities. However, this can only be possible if the demand is predicted accurately. Recent advancement in adaptive neuro-fuzzy inference system aimed at mapping input to output for highly non-linear processes such as energy management field, provide reliable approach to forecast energy demand. Despite the wide range of applications and flexibility of adaptive neuro-fuzzy inference system, complexity of the rule base is featured with certain limitations associated with combinatorial explosion of rules, parameters and data. This paper proposes a hybrid procedure, subtractive clustering technique coupled with genetic algorithm, to develop adaptive neuro-fuzzy inference system. Genetic algorithm finds the optimum value of cluster radius which guaranteed the minimum number of rules and error. The empirical data regarding the industrial's electricity demand in Iran from 1967 to 2011 are investigated to demonstrate the applicability and merits of the present method. The performance of hybrid approach is found to be better than that of conventional adaptive neuro-fuzzy inference system based on gird partitioning, fuzzy c-means, and subtractive clustering in terms of both accuracy and the number of rules.

International Color Company (ICC), a multinational paint major was an established player in the paint market in India. It had launched its premium 2-pack refinish product range in January 2013. Within first six months of the launch, when the excitement of the new launch had abated, it was found that there were shortage of certain SKU’s. There were incidences of shortage in some specific locations as well as the entire country, which required to be addressed on an immediate basis. The import lead time was 12 weeks by ship and 4 weeks by air which made the solution even more difficult. The situation was becoming more acute every passing day. Jayant, the Product Manager responsible for 2-pack refinish product range had been given two months time by the top management of ICC to get the situation under control. Apart from the mismatches in stock availability and its requirements across the retail outlets and branches, Jayant had inherited problems which were related to the structure and compensation plan of ICC, which made his task even more challenging.

Neste estudo teve-se como objetivo analisar a percepção de mentores e mentorados de uma empresa pública de energia sobre o processo de compartilhamento do conhecimento, em um programa de mentoria implantado. Quanto à abordagem do problema, a pesquisa foi qualitativa com natureza descritiva. Seu modo de investigação foi o estudo de caso. O quadro de análise encontra-se no modelo de compartilhamento de conhecimento de Tonet e Paz (2006). Os resultados evidenciaram que as quatro fases do modelo teórico utilizado (iniciação, implementação, apoio e incorporação) apresentaram valores aceitáveis, sinalizando-se pela existência de planejamento da demanda, interação entre mentores e mentorados, apoio do mentor ao mentorado no uso do conhecimento recebido e assimilação do conhecimento compartilhado e sua incorporação ao dia a dia de trabalho para a tomada de decisões sobre novos serviços, processos, tecnologias e produtos.Palavras-chave: Gestão do Conhecimento. Compartilhamento do conhecimento. Mentoria. Empresa pública. Energia. Abstract This study aimed to analyze the perception of mentors and mentored of a public energy company about the process of knowledge sharing in an implemented mentoring program. Regarding the problem approach, the research was qualitative with a descriptive nature. His mode of investigation was the case study. The framework of analysis is found in the knowledge-sharing model of Tonet and Paz (2006). The results evidenced that the four phases of the theoretical model used (being initiation, implementation, support and incorporation) presented acceptable values, signaled by the existence of demand planning, interaction between mentors and mentored, support of the mentor to the mentored in the use of the knowledge received and the assimilation of shared knowledge and its incorporation into the day to day work for decision making about new services, processes, technologies and products.Keywords: Knowledge management. Sharing knowledge. Mentoring. Public company. Energy.

Background: The decline in the productivity of the South African clothing industry was attributed to changing trends in the number of clothing production organisations, which together with a decline in manufacturing output and a fluctuation in employment had all contributed to complexities in demand planning. Purpose: This article investigates demand planning approaches in the clothing industry in Gauteng. Method: A descriptive study was conducted based on a structured questionnaire. Findings: The results revealed that both hierarchical and optimal approaches should be considered in clothing manufacturing. Managerial implications: In order to improve demand planning practices in the clothing industry, managers are recommended to apply hierarchical and optimal demand planning approaches, which might bring about improvements to demand planning in the Gauteng clothing industry. Conclusion: It is recommended that clothing manufacturers consider the types of product offering before making decisions about adopting the hierarchical or optimal demand planning approaches. When planning for basic clothes, manufacturers should consider a hierarchical demand planning approach, whereas the optimal demand planning approach is recommended for fashion clothes.

Background: In modern days’ dynamic consumer markets, supply chains need to be value driven and consumer oriented. Demand planning allows supply chain members to focus on the consumer and create optimal value. In demand planning, Point-of-Sale (POS) data are an essential input to the process thereof; however, literature suggests that POS-based demand planning is often overlooked by demand planners in practice. Objective: The main purpose of this study was to determine the extent to which South African clothing retailers use POS data in demand planning. Method: This study followed the grounded theory approach based on the collection of qualitative data. The data collected was analysed following the grounded theory analysis using codes that resulted in various categories which then developed into themes. Findings: Findings suggest that companies within the clothing retail industry make considerable use of POS data and is a fundamental input factor in the demand planning process. However, this study also found that POS data cannot be applied in the planning for all types of clothing products, and that there are variables other than POS data that form a critical part of the demand planning process. Conclusion: POS data plays a fundamental role is the demand planning process and should be accurately collected and used with other qualitative and quantitative factors as an input factor to the demand planning process. The role of POS data in demand planning is expected to grow as customers are becoming increasingly demanding concerning customer service levels.