Thesis (MBA)--Stellenbosch University, 2006. / Although most businesses require accurate sales forecasts in order to survive and to be successful, very little attention has been devoted to examine how sales forecasting processes should be managed, and the behavioural factors associated with the management of forecasting. Sales forecasting activities and research have by and large concentrated on the techniques or on the systems used, rather than on the forecasting management philosophy, which considers the organisational, procedural, and personnel aspects of the process. Both forecasting modelling and IT systems form the basis for the forecasting process, but the third element, namely the organisation, is potentially the most important one. Researchers have argued that improvements in this area could have a greater impact on the level of forecasting accuracy than improvements with regard to other aspects. After developing predetermined forecasting standards and principles, an audit on the author's organisation was conducted. This revealed that no formal forecasting --- existed, and that a number of business practices were in effect contaminating procedures and possibly affecting the integrity of the data. Very little forecasting knowledge existed, sales were predicted very sporadically, and simple averaging techniques were adopted. Life cycles of products, trends, seasonality or any other cyclical activity were never modelled. This obviously resulted in a very poor level of forecast accuracy, affecting a number of business activities. A decision was made to research the topic of forecasting management, develop a best practice model, and apply it to the organisation. The best practice model was based predominantly on the research work of Armstrong and Mentzer. This model requires the forecasting process to be developed in two specific phases, namely a strategic phase, in which the forecast is aligned to the organisation, the internal processes and the people, and the operational phase, in which more tangible aspects of the forecasting process are identified and constructed. This new forecasting approach and a dedicated forecasting software programme were successfully implemented, improving the overall accuracy level of the forecast.

Thesis (MBA)--Stellenbosch University, 1985. / Aangesien historiese data geredelik beskikbaar was, is 'n kwantitatiewe vooruitskattingsmetode gebruik met die doel om gebeure in die verlede te bestuur. Sodoende kon die onderliggende struktuur van die data beter begryp word en daarom kon 'n model daargestel word om die nodige inligting te verskaf vir bestuursbesluitneming. Die klassieke vermenigvuldigende tydreeks is gebruik om die toekomstige verkope van Stodels Nurseries (Edms.) Bpk. te projekteer. Aangesien die maatskappy se verkope onderhewig is aan hewige seisoenskommelings, is kontantvloeibeplanning van kardinale belang vir die finansiele bestuur van die maatskappy.

Shin Shiu Kau. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1975. / Bibliography: leaves 149-151.

The dissertation consists of a Piano Concerto, written for first performance in Fall 2008 by Blair McMillen, piano, and the Raleigh Civic Symphony conducted by Randolph Foy. The three movement work is scored for piccolo, 2 flutes (1 doubling piccolo), 2 oboes, English horn, 2 clarinets in B-flat, bass clarinet in B-flat, 2 bassoons, 4 horns in F, 3 trumpets in C, 2 tenor trombones, bass trombone, tuba, timpani, 3 percussionists, strings, and piano solo. The work is approximately twenty minutes in duration. The first movement, "Fantod," employs a neo-Romantic idiom, featuring the soloist as both aggressive virtuoso and as a subtle residual resonance which emerges from the orchestral texture. The second movement, "Lament," serves as a simple, pensive, and sorrowful aftermath to the frenzied first movement. In the third movement, "Rondoburlesque," the mood of the work becomes considerably more lighthearted, and moments of the first two movements are caricatured. The Concerto's harmonic and melodic organization derives from a set theoretical design. The first movement uses the harmonic minor scale and its inversion, the second movement uses the melodic minor scale, and the last movement uses the natural minor scale (the major scale). Important and unique subsets of these scales are used to provide both contrast and interrelatedness between movements. In particular, the main melodic theme of the first movement returns at the end of the last movement. / Dissertation

Thesis (Ph.D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2007. / Committee Co-Chair: Griffin, Paul; Committee Co-Chair: Serban, Nicoleta; Committee Member: Liang, Steven; Committee Member: Sharp, Gunter; Committee Member: Tsui, Kwok-Leung

Sales forecasting is an essential tool for the planning function of corporate restaurant management. Accurate sales forecasts allow functional areas, such as marketing, advertising, human resources, and finance, to effectively develop programs to advance the company. Examples of these programs include budgets, promotion and advertising campaigns, training programs, and capital equipment proposals. Research in restaurant sales forecasting will aid restaurant corporations in properly allocating resources for more efficient utilization. Utilizing a descriptive sales forecasting benchmarking model developed by Mentzer et al. (1996; 1999), and adapting the model into the restaurant industry, the research sought to determine the relationship that the dimensions of the sales forecasting benchmarking model (functional integration, approach, systems, and performance measurement) had with level of accuracy of the sales forecast and level of managers'; satisfaction with the sales forecasting process. The adapted model addressed two research questions. The first question was what is the relationship of the four dimensions of the sales forecasting benchmarking process (Mentzer et al., 1996; 1999) with the level of accuracy of the sales forecast in the commercial restaurant setting? The second question was what is the relationship of the four dimensions of the sales forecasting benchmarking process (Mentzer et al., 1996; 1999) with the level of managers' satisfaction with their sales forecasting process in the commercial restaurant setting? A qualitative research methodology combining McCracken's (1988) 4-step method of inquiry and Strauss & Corbin's (1990) grounded theory research methodology allowed investigation of this phenomena. Two propositions guided the research and a scheme was developed that allowed for analyzing the company participants based on the constructs of functional integration, approach, systems, and performance measurement, level of accuracy of the sales forecast and level of managers' satisfaction with the sales forecasting process. The analysis revealed that there was a relationship between the dimensions of the sales forecasting benchmarking model and the level of managers' satisfaction with the sales forecasting process. The analysis also revealed that the constructs of performance measurement and level of accuracy of the sales forecast might actually be one construct. Another dimension emerged, training, and scenarios were developed to relate training to the original dimensions. Recommendations were developed based on the research findings and hypotheses were developed based on the propositions. The findings suggest that there is a positive correlation between the dimension of the sales forecasting benchmarking model and the level of managers' satisfaction with the sales forecasting process. That is to say the more evolved a company may be in a dimension, the higher the level of managers' satisfaction with the sales forecasting process. / Ph. D.

<p>In a world that is moving faster and faster, a company’s ability to align to market changes is becoming a major competitive factor. Forecasting enables companies to predict what lies ahead, e.g. trend shifts or market turns, and makes it possible to plan for it. But looking into the future is never an easy task.</p><p>“Prediction is very difficult, especially if it’s about the future.” (Niels Bohr, 1885-1962)</p><p>However, progress in the field of forecasting has shown that it is possible for companies to improve on forecasting practices. This master thesis looks at the sales forecasting practices in MNCs primarily operating in emerging and developing countries. We examine the whole process of sales forecasting, also known as forecasting management, in order to develop a comprehensive model for forecasting in this type of companies. The research is based on a single case study, which is then later generalized into broader conclusions.</p><p>The conclusion of this master thesis is that forecasting is a four-step exercise. The four stages we have identified are: Knowledge creation, knowledge transformation, knowledge use and feedback. In the course of these four stages a company’s sales forecast is developed, changed and used. By understanding how each stage works and what to focus on, companies will be able to improve their forecasting practices.</p>

In a world that is moving faster and faster, a company’s ability to align to market changes is becoming a major competitive factor. Forecasting enables companies to predict what lies ahead, e.g. trend shifts or market turns, and makes it possible to plan for it. But looking into the future is never an easy task. “Prediction is very difficult, especially if it’s about the future.” (Niels Bohr, 1885-1962) However, progress in the field of forecasting has shown that it is possible for companies to improve on forecasting practices. This master thesis looks at the sales forecasting practices in MNCs primarily operating in emerging and developing countries. We examine the whole process of sales forecasting, also known as forecasting management, in order to develop a comprehensive model for forecasting in this type of companies. The research is based on a single case study, which is then later generalized into broader conclusions. The conclusion of this master thesis is that forecasting is a four-step exercise. The four stages we have identified are: Knowledge creation, knowledge transformation, knowledge use and feedback. In the course of these four stages a company’s sales forecast is developed, changed and used. By understanding how each stage works and what to focus on, companies will be able to improve their forecasting practices.

The purpose of this research is to investigate current company business process from sales forecasting perspective and provide potential improvements of how to deal with unstable market demand and increase overall precision of forecasting. The problem which company face is an unstable market demand and not enough precision in sales forecasting process. Therefore the research questions are:  How current forecasting process can be improved?  What methods, can be implemented in order to increase the precision of forecasting? Study can be described as an action research using an abductive approach supported by combination of quantitative and qualitative analysis practices. In order to achieve high degree of reliability the study was based on verified scientific literature and data collected from the case company while collaborating with company’s COO. Research exposed the current forecasting process of the case company. Different forecasting methods were chosen according to the existing circumstances and analyzed in order to figure out which could be implemented in order to increase forecasting precision and forecasting as a whole. Simple exponential smoothing showed the most promising accuracy results, which were measured by applying MAD, MSE and MAPE measurement techniques. Moreover, trend line analysis was applied as well, as a supplementary method. For the reason that the case company presents new products to the market limited amount of historical data was available. Therefore simple exponential smoothing technique did not show accurate results as desired. However, suggested methods can be applied for testing and learning purposes, supported by currently applied qualitative methods.

Os avanços na Tecnologia da Informação e a proliferação de itens de consumo, entre outros aspectos, mudaram o cenário e o desempenho das previsões. Os processos de previsão devem ser reexaminados, estabelecendo mecanismos de comunicação formais que compartilhem a informação entre os diferentes níveis hierárquicos dentro da organização, eliminando ou reduzindo o desconforto das previsões paralelas e desconexas oriundas de níveis hierárquicos diferentes. O objetivo deste trabalho é propor um sistema de apoio à decisão baseado em métodos matemáticos e sistemas de informação, capaz de integrar as previsões de vários níveis hierárquicos de uma empresa por um repositório de dados (Data Warehouse ou DW) e um Sistema de Apoio à Decisão (SAD) com sistema Business Intelligence (BI), onde os níveis hierárquicos acessem as informações com o nível de detalhe apropriado dentro do processo de decisão, alinhado às expectativas corporativas de crescimento. Assim, a modelagem realizada neste trabalho teve como foco a geração de cenários para criar um sistema de apoio à decisão, prevendo demandas agregadas e individuais, gerando uma estrutura de integração entre as previsões feitas em diferentes níveis e alinhando valores oriundos de métodos quantitativos e julgamento humano. Uma das maiores preocupações foi verificar qual método (séries temporais, métodos causais) teria destaque em um processo integrado de previsão. Entre os diferentes testes efetuados, pode-se destacar os seguintes resultados: (1) a suavização exponencial tripla proporcionou melhor ajuste (dos dados passados) de séries históricas de demandas mais agregadas e proporcionou previsões mais precisas de representatividades agregadas. Para séries históricas de demanda individual e representatividade individual, os outros métodos comparados apresentaram desempenho muito próximo; (2) a criação de diferentes cenários de previsão, fazendo uso de um repositório de dados e sistema de apoio à decisão, permitiu análise de uma gama de diferentes valores futuros. Uma forma de simulação para apoiar a formulação das expectativas da diretoria foi adaptada da literatura e sugerida; (3) os erros de previsão nas abordagens top-down ou bottom-up são estatisticamente iguais no contexto desta pesquisa. Conclui-se que o método de suavização exponencial tripla traz menos erros às previsões de séries mais agregadas, se comparado com outros métodos abordados no trabalho. Esse fato está de acordo com asserções encontradas na literatura pesquisada de que o método de suavização exponencial é cada vez mais utilizado na previsão, em detrimento dos métodos causais como a regressão múltipla. Conclui-se, principalmente, que os sistemas SAD e BI propostos deram suporte aos vários níveis hierárquicos, proporcionando variedades de estilos de decisão e que podem diminuir o hiato entre o raciocínio qualitativo adotado em nível estratégico e o aspecto quantitativo mais comum em níveis operacionais em qualquer empresa. / Advances in Information Technology (IT), and the increase of consumption items, among other things, changed the performance in the forecasts predictions. It is not uncommon that organizations will perform parallel forecasts within the various hierarchical levels without communicating with each other. The objective of this work is to build an integrated \"infrastructure\" for forecasting through a repository of data (Data Warehouse or DW) and a Decision Support System (DSS) with Business Intelligence (BI) where the hierarchical levels have access to the information with the appropriate level of detail within the process, aligned to the corporate growth expectations. The modeling in this work focused in the generation of scenarios to create a decision support system, predicting individual and aggregate demand, create a structure for integrating and aligning the estimated forecast generated by quantitative and qualitative methods. After a series of experimental tests, main results found were: (1) triple exponential smoothing provided the best fit using historical aggregated demand, and provided a more precise estimate of aggregate representation. For historical series of individual demand and individual representation, the other methods used for comparison performed similarly; (2) the creation of different scenarios for prediction, using data repository and decision support system, allowed for analysis of a range of different future values. The simulation to support management expectations has been adapted from the literature; (3) the prediction errors in the top-down and bottom-up approaches are statistically the same in the context of this research. In conclusion, the method of triple exponential smoothing has fewer errors in the forecasts of aggregated series when compared to other methods discussed in this work. Moreover, the DSS and BI systems provided decision-making support to the various hierarchical levels, reducing the gap between qualitative and quantitative decision processes thus bridging the strategic and operational decision making processes.