Use of Statistical Methods in Demand Planning

In a very volatile industry of high technology it is of utmost importance to accurately forecast customers’ demand. However, statistical forecasting of sales, especially in heavily competitive electronics product business, has always been a challenging task due to very high variation in demand and very short product life cycles of products. The purpose of this thesis is to validate if statistical methods can be applied to forecasting sales of short life cycle electronics products and provide a feasible framework for implementing statistical forecasting in the environment of the case company. Two different approaches have been developed for forecasting on short and medium term and long term horizons. Both models are based on decomposition models, but differ in interpretation of the model residuals. For long term horizons residuals are assumed to represent white noise, whereas for short and medium term forecasting horizon residuals are modeled using statistical forecasting methods. Implementation of both approaches is performed in Matlab. Modeling results have shown that different markets exhibit different demand patterns and therefore different analytical approaches are appropriate for modeling demand in these markets. Moreover, the outcomes of modeling imply that statistical forecasting can not be handled separately from judgmental forecasting, but should be perceived only as a basis for judgmental forecasting activities. Based on modeling results recommendations for further deployment of statistical methods in sales forecasting of the case company are developed.

Sales Forecasting e Demand Planning all'interno del processo di Sales & Operations Planning: il caso Cefla s.c.

Il presente elaborato di tesi è stato realizzato coerentemente con quanto osservato in Cefla s.c., azienda italiana composta attualmente da 4 Business Unit che operano a livello internazionale in settori distinti. I temi trattati riguardano nel dettaglio la Business Unit Medical Equipment, la quale realizza prodotti a supporto del professionista sanitario in tutte le fasi della sua attività, comprendendo riuniti odontoiatrici, apparecchiature per l’imaging e radiologia digitale e sistemi di sterilizzazione. L’obiettivo di questo elaborato è quello di descrivere l’attuale processo di Sales & Operations Planning all’interno di questa divisione dell’azienda e contribuire alla progettazione del piano per la sua strutturazione, reso necessario dalla situazione di forte criticità che Cefla s.c. è stata costretta ad affrontare. Vengono quindi descritte le problematiche che caratterizzano i processi interni all’azienda allo stato attuale, la cui valutazione è stata supportata da consulenti esterni, al fine di evidenziare gli aspetti più critici ed elaborare proposte di miglioramento. Queste ultime sono distinte in funzione delle diverse figure coinvolte che hanno contribuito alla loro realizzazione e ai sottoprocessi interessati e che costituiscono il Sales & Operations Planning: Sales Forecasting, Demand Planning e Supply Planning. In particolare, vengono approfonditi i processi che riguardano la previsione della domanda, in quanto per essi è stato possibile collaborare nell’elaborazione di proposte di miglioramento mirate. Visti i tempi medio lunghi che caratterizzano le soluzioni proposte all’azienda si è cercato di contribuire con la progettazione di proposte quick-win in ambito di Sales Forecasting e Demand Planning. Infine, si è tentato di quantificare i costi sostenuti da Cefla s.c. per far fronte alla situazione di criticità affrontata tramite valutazioni economiche e KPI, potendo così stimare l’impatto dato dall’implementazione di proposte di miglioramento.

The demand-supply balancing process in supply chain management - case mining & metals industry equipment

The aim of this thesis is to search how to match the demand and supply effectively in industrial and project-oriented business environment. The demand-supply balancing process is searched through three different phases: the demand planning and forecasting, synchronization of demand and supply and measurement of the results. The thesis contains a single case study that has been implemented in a company called Outotec. In the case study the demand is planned and forecasted with qualitative (judgmental) forecasting method. The quantitative forecasting methods are searched further to support the demand forecast and long term planning. The sales and operations planning process is used in the synchronization of the demand and supply. The demand forecast is applied in the management of a supply chain of critical unit of elemental analyzer. Different meters on operational and strategic level are proposed for the measurement of performance.

Evaluating and improving demand forecast practices for B2B and B2C sectors

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. Former literature points out that even though many forecasting methods and approaches are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, it’s relatively rare that researches are focused on the differences in forecasting between consumer and industrial companies. The aim of this thesis is to investigate the potential of improving demand forecasting practices for B2B and B2C sectors in the global supply chains. Business to business (B2B) sector produces products for other manufacturing companies. On the other hand, consumer (B2C) sector provides goods for individual buyers. Usually industrial sector have a lower number of customers and closer relationships with them. The research questions of this thesis are: 1) What are the main differences and similarities in demand planning between B2B and B2C sectors? 2) How the forecast performance for industrial and consumer companies can be improved? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from a case company. Evaluation and improving in organizing demand forecasting can be found in three interlinked areas: 1) demand planning operational environment, 2) demand forecasting techniques, 3) demand information sharing scenarios. In this research current B2B and B2C demand practices are presented with further comparison between those two sectors. It was found that B2B and B2C sectors have significant differences in demand practices. This research partly filled the theoretical gap in understanding the difference in forecasting in consumer and industrial sectors. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Defining Sales and Operations Planning Process in an Environmental Management Company

Sales and operations research publications have increased significantly in the last decades. The concept of sales and operations planning (S&OP) has gained increased recognition and has been put forward as the area within Supply Chain Management (SCM). Development of S&OP is based on the need for determining future actions, both for sales and operations, since off-shoring, outsourcing, complex supply chains and extended lead times make challenges for responding to changes in the marketplace when they occur. Order intake of the case company has grown rapidly during the last years. Along with the growth, new challenges considering data management and information flow have arisen due to increasing customer orders. To manage these challenges, case company has implemented S&OP process, though initial process is in early stage and due to this, the process is not managing the increased customer orders adequately. Thesis objective is to explore extensively the S&OP process content of the case company and give further recommendations. Objectives are categorized into six different groups, to clarify the purpose of this thesis. Qualitative research methods used are active participant observation, qualitative interviews, enquiry, education, and a workshop. It is notable that demand planning was felt as cumbersome, so it is typically the biggest challenge in S&OP process. More proactive the sales forecasting can be, more expanded the time horizon of operational planning will turn out. S&OP process is 60 percent change management, 30 percent process development and 10 percent technology. The change management and continuous improvement can sometimes be arduous and set as secondary. It is important that different people are required to improve the process and the process is constantly evaluated. As well as, process governance is substantially in a central role and it has to be managed consciously. Generally, S&OP process was seen important and all the stakeholders were committed to the process. Particular sections were experienced more important than others, depending on the stakeholders’ point of views. Recommendations to objective groups are evaluated by the achievable benefit and resource requirement. The urgent and easily implemented improvement recommendations should be executed firstly. Next steps are to develop more coherent process structure and refine cost awareness. Afterwards demand planning, supply planning, and reporting should be developed more profoundly. For last, information technology system should be implemented to support the process phases.

Nestle's dynamic forecasting process: Anticipating risks and opportunities

Nestlé’s Dynamic Forecasting Process: Anticipating Risks and Opportunities This Work Project discusses the Nestlé’s Dynamic Forecasting Process, implemented within the organization as a way of reengineering its performance management concept and processes, so as to make it more flexible and capable to react to volatile business conditions. When stressing the importance of demand planning to reallocate resources and enhance performance, Nescafé Dolce Gusto comes as way of seeking improvements on this forecasts’ accuracy and it is thus, by providing a more accurate model on its capsules’ sales, as well as recommending adequate implementations that positively contribute to the referred Planning Process, that value is brought to the Project

Kysynnän ennustaminen leipomotuotteille ja ennusteen tarkkuuden arviointi

Tässä diplomityössä tutkittiin kysynnän ennustamista Vaasan & Vaasan Oy:n tuotteille. Ensin työssä perehdyttiin ennustamiseen ja sen tarjoamiin mahdollisuuksiin yrityksessä. Erityisesti kysynnän ennustamisesta saatavat hyödyt käytiin läpi. Kysynnän ennustamisesta haettiin ratkaisua erityisesti ongelmiin työvuorosuunnittelussa.Työssä perehdyttiin ennustemenetelmiin liittyvään kirjallisuuteen, jonka oppien perusteella tehtiin koe-ennustuksia yrityksen kysynnän historiadatan avulla. Koe-ennustuksia tehtiin kuudelle eri Turun leipomon koe-tuotteelle. Ennustettavana aikavälinä oli kahden viikon päiväkohtainen kysyntä. Tämän aikavälin erityisesti peruskysynnälle etsittiin ennustetarkkuudeltaan parasta kvantitatiivista ennustemenetelmää. Koe-ennustuksia tehtiin liukuvilla keskiarvoilla, klassisella aikasarja-analyysillä, eksponentiaalisen tasoituksen menetelmällä, Holtin lineaarisella eksponenttitasoituksen menetelmällä, Wintersin kausittaisella eksponentiaalisella tasoituksella, autoregressiivisillä malleilla, Box-Jenkinsin menetelmällä ja regressioanalyysillä. Myös neuroverkon opettamista historiadatalla ja käyttämistä ongelman ratkaisun apuna kokeiltiin.Koe-ennustuksien tulosten perusteella ennustemenetelmien toimintaa analysoitiin jatkokehitystä varten. Ennustetarkkuuden lisäksi arvioitiin mallin yksinkertaisuutta, helppokäyttöisyyttä ja sopivuutta yrityksen monien tuotteiden ennustamiseen. Myös kausivaihteluihin, trendeihin ja erikoispäiviin kiinnitettiin huomiota. Ennustetarkkuuden huomattiin parantuvan selvästi peruskysyntää ennustettaessa, jos ensin historiadata esikäsittelemällä puhdistettiin erikoispäivistä ja –viikoista.

Herramienta funcional para desarrollo y manejo de un modelo de gestión de inventarios

Esta tesis surge como una oportunidad de crear una herramienta de mejora en las empresas, para controlar los inventarios de la manera más adecuada. Debido a los desórdenes de los precios en el mercado, las promociones no planeadas, y la confrontación de pronósticos optimistas Vs. Pronósticos conservadores, se presenta un gran volumen de devoluciones, repercutiendo en el deterioro de la cartera y afectando directamente las metas estratégicas de las empresas. Tras esta clara oportunidad de mejora, se toma la decisión de evaluar el modelo de pronóstico que arroje los valores más acertados para la planeación de la demanda. Por otro lado, se analizo el mejor modelo de inventarios con sus respectivos indicadores de control. Dando como resultado una herramienta parametrizada en Excel, que arroja datos de pronósticos de ventas más acertados y optimiza la gestión de los inventarios. Esta herramienta contiene un modelo de gestión de inventarios de revisión continua, lo cual brinda información más acertada de la demanda que enfrenta la compañía, las ventas que puede generar, y los procesos que necesita planear para respaldar su actividad.

Web user interface architecture for advanced planning and scheduling systems Case: Nokia Demand / Supply Planning Applications

In modem hitec industry Advanced Planning and Scheduling (APS) systems provide the basis for e-business solutions towards the suppliers and the customers. One objective of this thesis was to clarify the modem supply chain management with the APS systems and especially concentrate on the area of Collaborative Planning. In order Advanced Planning and Scheduling systems to be complete and usable, user interfaces are needed. Current Visual Basic user interfaces have faced many complaints and arguments from the users as well as from the development team. This thesis is trying to analyze the reasons and causes for the encountered problems and also provide ways to overcome them. The decision has been made to build the new user interfaces to be Web-enabled. Therefore another objective of this thesis was to research and find suitable technologies for building the Web-based user interfaces for Advanced Planning and Scheduling Systems in Nokia Demand/Supply Planning business area. Comparison between the most suitable technologies is made. Usability issues of Web-enabled user interfaces are also covered. The empirical part of the thesis includes design and implementation of a Web-based user interface with the chosen technology for a particular APS module that enables Collaborative Planning with suppliers.

Demand of children in Colombia : guessing or planning

El artículo analiza los determinantes de la presencia de hijos no deseados en Colombia. Se utiliza la información de la Encuesta Nacional de Demografía y Salud (ENDS, 2005), específicamente para las mujeres de 40 años o más. Dadas las características especiales de la variable que se analiza, se utilizan modelos de conteo para verificar si determinadas características socioeconómicas como la educación o el estrato económico explican la presencia de hijos no deseados. Se encuentra que la educación de la mujer y el área de residencia son determinantes significativos de los nacimientos no planeados. Además, la relación negativa entre el número de hijos no deseados y la educación de la mujer arroja implicaciones clave en materia de política social.

Transmission network expansion planning considering uncertainty in demand

This paper presents two mathematical models and one methodology to solve a transmission network expansion planning problem considering uncertainty in demand. The first model analyzed the uncertainty in the system as a whole; then, this model considers the uncertainty in the total demand of the power system. The second one analyzed the uncertainty in each load bus individually. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The models presented are solved using a specialized genetic algorithm. The results obtained for several known systems from literature show that cheaper plans can be found satisfying the uncertainty in demand.

Transmission network expansion planning considering uncertainty in generation and demand

This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering uncertainty in demand and generation. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The model presented results in an optimization problem that is solved using a specialized genetic algorithm. The results obtained for known systems from the literature show that cheaper plans can be found satisfying the uncertainty in demand and generation. ©2008 IEEE.