Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Accuracy in book papers' sales forecasting

The main objective of this thesis was to study if the quantitative sales forecasting methods will enhance the accuracy of the sales forecast in comparison to qualitative sales forecasting method. A literature review in the field of forecasting was conducted, including general sales forecasting process, forecasting methods and techniques and forecasting accuracy measurement. In the empirical part of the study the accuracy of the forecasts provided by both qualitative and quantitative methods is being studied and compared in the case of short, medium and long term forecasts. The SAS® Forecast Server –tool was used in creating the quantitative forecasts.

A study to adapt various sales forecasting methods for use by military club managers

The purpose of this study is to adapt and combine the following methods of sales forecasting: Classical Time-Series Decomposition, Operationally Based Data and Judgmental Forecasting for use by military club managers.

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.

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.

Improvement on the sales forecast accuracy for a fast growing company by the best combination of historical data usage and clients segmentation

Industrial companies in developing countries are facing rapid growths, and this requires having in place the best organizational processes to cope with the market demand. Sales forecasting, as a tool aligned with the general strategy of the company, needs to be as much accurate as possible, in order to achieve the sales targets by making available the right information for purchasing, planning and control of production areas, and finally attending in time and form the demand generated. The present dissertation uses a single case study from the subsidiary of an international explosives company based in Brazil, Maxam, experiencing high growth in sales, and therefore facing the challenge to adequate its structure and processes properly for the rapid growth expected. Diverse sales forecast techniques have been analyzed to compare the actual monthly sales forecast, based on the sales force representatives’ market knowledge, with forecasts based on the analysis of historical sales data. The dissertation findings show how the combination of both qualitative and quantitative forecasts, by the creation of a combined forecast that considers both client´s demand knowledge from the sales workforce with time series analysis, leads to the improvement on the accuracy of the company´s sales forecast.

Sistema avançado de previsão de vendas para as lojas Pingo Doce do grupo Jerónimo Martins

Dissertação apresentada ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Logística Orientada por: Professora Doutora Patrícia Alexandra Gregório Ramos

Gestão da cadeia de abastecimento de bens de consumo baseada em modelos de previsão lineares

Dissertação apresentada ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Logística

Les TIC a l'ensenyament de la modelització matemàtica en Ciències Econòmiques i en Ciències Experimentals

Aquest projecte proposa materials didàctics per a un nou plantejament de les assignatures de Matemàtiques dels primers cursos de Ciències Empresarials i d'Enginyeria Tècnica, més acord amb el procés de convergència europea, basat en la realització de projectes que anomenem “Tallers de Modelització Matemàtica” (TMM) en els quals: (1) Els alumnes parteixen de situacions i problemes reals per als quals han de construir per sí mateixos els models matemàtics més adients i, a partir de la manipulació adequada d’aquests models, poden obtenir la informació necessària per donar-los resposta. (2) El treball de construcció, experimentació i avaluació dels models es realitza amb el suport de la calculadora simbòlica Wiris i del full de càlcul Excel com a instruments “normalitzats” del treball matemàtic d’estudiants i professors. (3) S’adapten els programes de les assignatures de matemàtiques de primer curs per tal de poder-les associar a un petit nombre de Tallers que parteixen de situacions adaptades a cada titulació. L’assignatura de Matemàtiques per a les Ciències Empresarials s’articula entorn de dos tallers independents: “Matrius de transició” pel que fa a l’àlgebra lineal i “Previsió de vendes” per a la modelització funcional en una variable. L’assignatura de Matemàtiques per a l’Enginyeria s’articula entorn d’un únic taller, “Models de poblacions”, que abasta la majoria de continguts del curs: successions i models funcionals en una variable, àlgebra lineal i equacions diferencials. Un conjunt d’exercicis interactius basats en la calculadora simbòlica WIRIS (Wiris-player) serveix de suport per al treball tècnic imprescindible per al desenvolupament de les dues assignatures. L’experimentació d’aquests tallers durant 2 cursos consecutius (2006/07 i 2007/08) en dues universitats catalanes (URL i UAB) ha posat en evidència tant els innegables avantatges del nou dispositiu docent per a l’aprenentatge dels estudiants, així com les restriccions institucionals que actualment dificulten la seva gestió i difusió.

Rullaavan ennustamisen kehittäminen CASE: ABB Oy Service

Tutkimuksen tavoitteena oli kehittää rullaavan ennustamisen toimintaa, jotta se tuottaisi relevanttia informaatiota tapausyrityksen ohjaukselle. Tutkimuksessa sovellettiin konstruktiivista tutkimusotetta, joka on ratkaisumenetelmä liikkeenjohdollisiin ongelmiin. Tutkimustulos eli ratkaisukonstruktio innovoitiin tutkijan luoman viitekehyksen ja empiirisen tutkimuksen havaintojen avulla. Tutkimustuloksien perusteella analyyttisen rullaavan ennustamisen tarkoituksena on tyydyttää eri ohjaustasojen informaatiotarpeita ja tukea asiakaslähtöisen tapausyrityksen liiketoimintaympäristöön sopeutumista. Tutkimuksen mukaan rullaava ennustaminen on suunnittelua, joka pyrkii organisatoriseen oppimiseen. Kehittämiseen liittyviä näkökulmia, organisatorisia ja järjestelmällisiä tekijöitä löydettiin useita. Nämä eivät rajoittuneet ainoastaan johdon laskentatoimen alueelle.

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.

Researching Manufacturing Planning and Control system and Master Scheduling in a manufacturing firm.

The objective of this thesis is to research Manufacturing Planning and Control (MPC) system and Master Scheduling (MS) in a manufacturing firm. The study is conducted at Ensto Finland Corporation, which operates on a field of electrical systems and supplies. The paper consists of theoretical and empirical parts. The empirical part is based on weekly operating at Ensto and includes inter-firm material analysis, learning and meetings. Master Scheduling is an important module of an MPC system, since it is beneficial on transforming strategic production plans based on demand forecasting into operational schedules. Furthermore, capacity planning tools can remarkably contribute to production planning: by Rough-Cut Capacity Planning (RCCP) tool, a MS plan can be critically analyzed in terms of available key resources in real manufacturing environment. Currently, there are remarkable inefficiencies when it comes to Ensto’s practices: the system is not able to take into consideration seasonal demand and react on market changes on time; This can cause significant lost sales. However, these inefficiencies could be eliminated through the appropriate utilization of MS and RCCP tools. To utilize MS and RCCP tools in Ensto’s production environment, further testing in real production environment is required. Moreover, data accuracy, appropriate commitment to adapting and learning the new tools, and continuous developing of functions closely related to MS, such as sales forecasting, need to be ensured.

Kysynnän ennusteprosessi elintarvikealan pk-yrityksissä

Kysynnän ennustaminen on aina ollut suuri ongelma toimitusketjun hallinnassa. Useat päätösprosessit, kuten varastonhallinta, tuotekehitys, tuotanto ja toimitusketjun suunnittelu vaativat ennustamista, jonka tarkka määrittäminen on kuitenkin erittäin hankalaa. Kysynnän ennustaminen on kirjallisuudessa laajasti tutkittu aihealue, mutta sen tutkimukset rajoittuvat suuressa määriin erilaisten ennustemenetelmien vertailemiseen ja ennustevirheiden tutkimiseen. (Chase 1997; Kahn 1998; Makridakis ja Wheelwright 1998; Goodwin ja Fildes 1999) Ennustemenetelmien käyttö ja mahdolliset ennustevirheet ovat kuitenkin seurausta sarjasta peräkkäisiä toimenpiteitä eli prosessista. Siksi onkin paljon mielenkiintoisempaa tutkia kokonaisvaltaisesti koko sitä prosessia, joka ennustamiseen yhdistetään, kuin pelkkiä ennustemenetelmiä tai niiden käytön seurauksena havaittuja virheitä. Tässä tutkimuksessa kartoitetaan viiden elintarvikealalle erikoistuneen pk-yrityksen ennusteprosesseja, joita verrataan keskenään sekä Mentzerin, Bienstockin ja Kahnin (1999) tekemään tutkimukseen ”Benchmarking Sales Forecasting Management”. Tutkimusongelman voidaan katsoa olevan ”millainen on pk-yritysten ennusteprosessi ja mitkä asiat selittävät mahdollisia eroja kohdeyritysten ennusteprosesseissa?”. Tämä tutkimus hyödyntää laadullista tutkimusotetta ja on tarkoitukseltaan kartoittava. Empiirinen aineisto kerättiin teemahaastatteluiden avulla ja haastateltavina toimivat viiden kohdeyritysten toimitusjohtajat. Tämän tutkimuksen aineiston analyysissä on hyödynnetty aineiston ryhmittelyä teemoiksi ja pyritty löytämään samankaltaisuuksia ja eroavaisuuksia kohdeyritysten välille. Tutkimuksen tuloksena havaittiin, että elintarvikealan pk-yritysten ennusteprosessi on hyvin yksinkertainen. Tämän voidaan nähdä selittyvän kohdeyritysten tyytyväisyydellä omaa ennusteprosessia kohtaan, mikä estää prosessin kriittisen tarkastelun ja sitä kautta kehittämisen. Voidaan myös nähdä, että tietämättömyys, inertia ja resurssien rajallisuus estävät ennusteprosessien kehittämisen kohdeyrityksissä. Kohdeyritysten ennusteprosessit olivat hyvin samanlaisia keskenään ja merkittävimmät erot selittyvät, kun tarkastellaan toimialojen luonteiden eroja.

Previsão de vendas para uma indústria de equipamentos pesados: seleção de técnicas e análise

The continuous advance of the Brazilian economy and increased competition in the heavy equipment market, increasingly point to the need for accurate sales forecasting processes, which allow an optimized strategic planning and therefore better overall results. In this manner, we found that the sales forecasting process deserves to be studied and understood, since it has a key role in corporate strategic planning. Accurate forecasting methods enable direction of companies to circumvent the management difficulties and the variations of finished goods inventory, which make companies more competitive. By analyzing the stages of the sales forecasting it was possible to observe that this process is methodical, bureaucratic and demands a lot of training for their managers and professionals. In this paper we applied the modeling method and the selecting process which has been done for Armstrong to select the most appropriate technique for two products of a heavy equipment industry and it has been through this method that the triple exponential smoothing technique has been chosen for both products. The results obtained by prediction with the triple exponential smoothing technique were better than forecasts prepared by the industry experts