Theoretic part of thesis included short introduction into logistics, define question of demand planning and his role in SCM. In practical part is outlined function of SCM in Farm Frites company. Description of logistics chain, which is necessary part for understanding of whole proces of demand planning in company. Main object of thesis is to determine problems connected with demand planning and proposal of resolution of that problems in Farm Frites.

In Recent years, global supply chain management has been a popular study area due to the economic globalization. This study mainly focus on the demand planning process of demand management in global supply chain management. The purpose of this thesis is to find the key factors and obstacles in demand planning process both in theory and practice, and solutions for the obstacles. Based on many scholar researches, a brief introduction of demand management and demand planning has been made at the beginning of the theoretical framework. Key factors, key obstacles and solutions are collected and clarified from empirical study and scholar researches in the theoretical framework. Qualitative approach is adopted as basic approach. We use case study to do the research and interviews to collect data. A server manufacturer of IBM named ISTC (International System Technology Corporation) is chosen as a case for this research. The key factors, obstacles and improvements of empirical study are compared with the facts of ISTC. New factors, obstacles and their new descriptions are figured out through the comparison between theory and the fact of the case. A suggestion for improvement and solution for the demand planning process is also put forward based on the empirical study and the facts of ISTC by this method.

The thesis Management of logistics and processes in L'Oréal Czech Republic is in its theoretical part devoted to the description of functioning, principles and trends in Supply Chain Management with emphasis on the processes of demand forecasting and stock management. These learnings are in the practical part applied on the case of L'Oréal Czech Republic. The thesis goes in more detail into the processes and links between the individual parts of the supply chain in the company and a value stream map is shown for a particular division of the firm. More detailed attention is put on identification of weak points particularly in the forecasting methods and the use of out of stock analysis in practice.

The aim of this thesis is to analyze the processes of demand planning and management. This work describes the main assumptions of the successful completion of this process. It also deals with the main methods and techniques of demand planning and management, including the importance of software tools. Thesis topic was chosen due to the extraordinary importance of demand planning in terms of satisfying the constantly growing and changing subject to customer requirements. The methodological part is devoted to a comprehensive description of the main assumptions affecting this process and methods of demand planning. The analytical part focuses on the processes of demand planning in an environment of the specific pharmaceutical company. Critically evaluates these processes and offers their solutions.

The clothing industry is multifaceted and is characterised by garments with a short life cycle, unstable customer needs and varying fashion styles. This affects the accuracy of demand planning. In SA, the clothing industry has experienced a decline in the number of clothing manufacturers and manufacturing outputs as well as fluctuations in employment. This study investigates demand planning practices in the Gauteng clothing industry. A descriptive and exploratory study was conducted based on a semi-structured questionnaire. The structured data was descriptively analysed using SPSS and inferentially analysed using the Kruskal‒Wallis test as well as content analysis for the unstructured questions. The findings revealed that demand planning practices in the Gauteng clothing industry are conducted using the hierarchical and optimal demand planning approaches. The results also revealed that there are certain factors which affect the way demand planning is conducted in the clothing industry in Gauteng. These factors includes: scheduling, fashion clothes, point of sale system, imports, estimation, recession and lead time. Furthermore, the study revealed that there are differences in the factors affecting demand planning regarding the three key clothing stakeholders (fabric suppliers, clothing manufacturers and fashion designers). The study revealed that key demand planning practices employed in the Gauteng clothing industry are production planning, uncertainty prevention, forecasting and production machine capabilities. These practices are important attributes of the hierarchical and optimal demand planning approaches. The study recommends that the hierarchical demand planning approach is more effective when planning for basic clothes (which involved planning horizon of twelve months), while the optimal demand planning approach is effective when planning for fashion clothes (which involved planning horizon of six months). The study recommends that the Gauteng clothing industry should consider factors which affect demand planning when planning for customers' needs as they affect the level of productivity in the organisation. / Entrepreneurship Supply Chain Transport Tourism and Logistics Management / M. Com.(Logistics)

No description available.

The planning of an Aftermarket Supply Chain is a very complex task. This is due to an unpredictable demand which is driven by the need for maintenance and repair. This drive translates to a high variety of lead times, a large number of stock-keeping units (SKUs) and the capacity to deliver spare parts during its full lifecycle. With all these complexities in place, optimizing and parametrizing the planning process is a difficult and time-consuming task. Moreover, the current optimization tool focuses only on one node (each warehouse individually) of the whole Supply Chain, without considering the information such as inventory levels of the other nodes. Hence, the Supply Chain is not completely connected, making it difficult to get a better understanding of the system performance to identify cost draining areas. This leads to capital being tied up in the upper stream of the Supply Chain and later adding unnecessary costs like high inventory costs, rush freight costs, return or scrapping cost. In this study, Discrete Event Simulation (DES) is explored as an additional optimization tool that could analyse and improve the performance of the whole Supply Chain. To do that, the functioning of a node is modelled by replicating the logics behind the flow of material, which includes analysing some manual workflows which are currently present. In Addition, all the information needed from the orders, order lines and parts are mapped. The later part of the study aims to connect all the nodes to form a whole overview of the Supply Chain and further perform optimizations globally.  As an outcome, Multi-Echelon Inventory Optimization has been performed on the whole Supply Chain after connecting all the nodes and thus getting an overview. Furthermore, the impact of different parameters has been studied on the whole model to understand the sensitivity of parameters such as variations in lead time and demand. Finally, different what-if scenarios such as COVID and problems with delay in suppliers were studied, which could help understand the impact of unforeseen situations. / Planeringen av en eftermarknadskedja är en mycket komplex uppgift. Detta beror på en oförutsägbar efterfrågan som drivs av behovet av underhåll och reparation. Enheten översätter till många olika ledtider, ett stort antal lagerhållningsenheter (SKU) och kapacitet att leverera reservdelar under hela dess livscykel. Med alla dessa komplexiteter på plats är optimering och parametrering av planeringsprocessen en svår och tidskrävande uppgift. Dessutom fokuserar det nuvarande optimeringsverktyget bara på en nod (varje lager separat) i hela leveranskedjan utan att beakta informationen som lagernivåerna för de andra noderna. Därför är försörjningskedjan inte helt ansluten, vilket gör det svårt att få en bättre förståelse för systemets prestanda för att identifiera kostnadsavtappningsområden. Detta leder till att kapital binds i den övre strömmen i försörjningskedjan och senare lägger till onödiga kostnader som höga lagerkostnader, snabba fraktkostnader, retur- eller skrotningskostnader. I denna studie undersöks Discrete Event Simulation (DES) som ett ytterligare optimeringsverktyg som kan analysera och förbättra prestanda för hela försörjningskedjan. För att göra det modelleras en nods funktion genom att replikera logiken bakom materialflödet, vilket inkluderar analys av några manuella arbetsflöden som för närvarande finns. Dessutom kartläggs all information som behövs från beställningar, orderrader och delar. Den senare delen av studien syftar till att ansluta alla noder för att bilda en hel översikt över försörjningskedjan och ytterligare utföra optimeringar globalt. Som ett resultat har Multi-Echelon Lageroptimering utförts i hela försörjningskedjan efter att alla noder har anslutits och därmed fått en översikt. Dessutom har effekterna av olika parametrar studerats på hela modellen för att förstå känsligheten hos parametrar som variationer i ledtid och efterfrågan. Slutligen studerades olika tänkbara scenarier som COVID och problem med förseningar hos leverantörer, vilket kan hjälpa till att förstå effekterna av oförutsedda situationer.

One challenge organizations are facing in all industries is determining the likely events of the future and developing strategies to handle these challenges. Sales and operations planning are a decision-making process and tool that helps organizations to allocate resources not only to handle the challenges but also to take advantage of future conditions by balancing supply and demand. There is only a limited amount of framework and models available today. This project will divulge and reveal a new framework for sales and operations planning which has been developed in collaboration with an organization operating in the aerospace and defence industry. The basis of the framework consists of a monthly five step process that facilitates the organization in making decisions based on long term (five-years) organizational goals and tying them in with project specific needs. Ultimately, this will provide a centralized system in meeting current project specific demands whilst ensuring future operations are not compromised but enhanced. The company’s current sales and operations planning maturity level was evaluated and compared to the developed framework to find gaps of what needs to change for the company to have proactive sales and operations planning.

Companies face constant change in today's dynamic business landscape, navigating shifting customer demands, globalization, and economic fluctuations. To thrive, businesses must optimize costs and meet customer needs, making supply chain management necessary. At its core lies demand management, a strategic and operational process that aligns customer needs with the capabilities of the supply chain. The ever-changing demand sets challenges for the integration between supply and demand that need to be studied. While other studies may focus on individual activities, this study treats demand management as a holistic process. Through a case study in ABB Robotics focusing on the spare parts industry, renowned for its stringent service level requirements and extensive availability. This thesis investigates demand management practices, emphasizing integration between demand and supply units, uncovering challenges across the supply chain, and exploring improvement opportunities. The study employs a single case study design with an exploratory abductive approach, using a qualitative method and interviews to gather empirical data that is later analyzed against theoretical frameworks based on prior research. Despite solid inventory planning and collaboration levels, the study identifies several challenges the company faces in meeting demand effectively, including inadequate coordination and failure to incorporate supply capabilities, divergent goals, departmental silos, lack of alignment, and systematic process deficiencies hindering informed decision-making alignment. Also, unclear allocation strategies in supply limitations and customer prioritization are present. Figure 8 in this study advocates integrating demand and supply teams equally, which is crucial for optimized cost and value. The study suggests adopting Sales and Operations Planning (S&OP) to involve stakeholders systematically. Necessary actions include understanding roles and responsibilities, setting clear goals, sharing knowledge, enhancing customer and marketing segmentation, and increasing data transparency. In conclusion, successful demand management necessitates viewing it as an integrated process involving all teams focused on reducing variables through continuous information flow.

Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools. In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management. Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented.