| Summary: | Thesis (MBA)--Stellenbosch University, 2003. === ENGLISH ABSTRACT: Forecasting the future has always been one of the man's strongest desires. The aim
to determine the future has resulted in scientifically based forecasting models of
human health, behaviour, economics, weather, etc. The main purpose of forecasting
is to reduce the range of uncertainty within which management decisions must be
made. Forecasts are only effective if they are utilized by those who have decisionmaking
authority. Forecasts need to be understood and appreciated by decision
makers so that they find their way into management of the firm.
Companies still predominantly rely on judgemental forecasting methods, most often
on an informal basis. There is a large literature base that point to the numerous biases
inherent in judgemental forecasting. Most companies know that their forecasts are
incorrect but don't know what to do about it and choose to ignore the issue, hoping
that the problem will solve itself.
The collaborative forecasting process attempts to use history as a baseline, but
supplement current knowledge about specific trends, events and other items. This
approach integrates the knowledge and information that exists internally and
externally into a single, more accurate forecast that supports the entire supply chain.
Demand forecasting is not just a matter of duplicating or predicting history into the
future. It is important that one person should lead and manage the process.
Accountability needs to be established.
An audit on the writer's own organization indicated that no formal forecasting process
was present. The company's forecasting process was very political, since values were
entered just to add up to the required targets. The real gap was never fully
understood. Little knowledge existed regarding statistical analysis and forecasting
within the marketing department who is accountable for the forecast. The forecasting
method was therefore a top-down approach and never really checked with a bottom up
approach.
It was decided to learn more about the new demand planning process prescribed by
the head office, and to start implementing the approach. The approach is a form of a collaborative approach which aims to involve all stakeholders when generating the
forecast, therefore applying a bottom up approach.
Statistical forecasting was applied to see how accurate the output was versus that of
the old way of forecasting. The statistical forecast approach performed better with
product groups where little changed from previous years existed, while the old way
performed better where new activities were planned or known by the marketing team.
This indicates that statistical forecasting is very important for creating the starting
point or baseline forecast, but requires qualitative input from all stakeholders.
Statistical forecasting is therefore not the solution to improved forecasting, but rather
part of the solution to create robust forecasts. === AFRIKAANSE OPSOMMING: Vooruitskatting van die toekoms was nog altyd een van die mens se grootste
begeertes. Die doel om die toekoms te bepaal het gelei tot wiskundige gebaseerde
modelle van die mens se gesondheid, gedrag, ekonomie, weer, ens. The hoofdoel van
vooruitskatting is om die reeks van risikos te verminder waarbinne bestuur besluite
moet neem. Vooruitskattings is slegs effektief as dit gebruik word deur hulle wat
besluitnemingsmag het. Vooruitskattings moet verstaan en gewaardeer word deur die
besluitnemers sodat dit die weg kan vind na die bestuur van die firma.
Maatskappye vertrou nog steeds hoofsaaklik op eie oordeel vooruitskatting metodes,
en meestal op 'n informele basis. Daar is 'n uitgebreide literatuurbasis wat daarop dui
dat heelwat sydigheid betrokke is by vooruitskattings wat gebaseer is op eie oordeel.
Baie organisasies weet dat hulle vooruitskattings verkeerd is, maar weet nie wat
daaromtrent te doen nie en kies om die probleem te ignoreer, met die hoop dat die
probleem vanself sal oplos.
Die geïntegreerde vooruitskattingsproses probeer om die verlede te gebruik as 'n
basis, maar voeg huidige kennis rakende spesifieke neigings, gebeurtenisse, en ander
items saam. Hierdie benadering integreer die kennis en informasie wat intern en
ekstern bestaan in 'n enkele, meer akkurate vooruitskatting wat die hele
verskaffingsketting ondersteun. Vraagvooruitskatting is nie alleen 'n duplisering of
vooruitskatting van die verlede in die toekoms in nie. Dit is belangrik dat een persoon
die proses moet lei en bestuur. Verantwoordelikhede moet vasgestel word.
'n Oudit op die skrywer se organisasie het getoon dat geen formele
vooruitskattingsprosesse bestaan het nie. Die maatskappy se vooruitskattingsproses
was hoogs gepolitiseerd, want getalle was vasgestel wat in lyn was met die nodige
teikens. Die ware gaping was nooit werklik begryp nie. Min kennis was aanwesig
rakende statistiese analises en vooruitskatting binne die bemarkingsdepartement wat
verantwoordelik is vir die vooruitskatting. Die vooruitskatting is dus eerder gedoen
op 'n globale vlak en nie noodwendig getoets deur die vooruitskatting op te bou uit
detail nie. Daar is besluit om meer te leer rakende die nuwe vraagbeplanningsproses, wat
voorgeskryf is deur hoofkantoor, en om die metode te begin implementeer. Die
metode is 'n vorm van 'n geïntegreerde model wat beoog om alle aandeelhouers te
betrek wanneer die vooruitskatting gedoen word, dus die vooruitskatting opbou met
detail.
Statistiese vooruitskatting was toegepas om te sien hoe akkuraat die uitset was teenoor
die ou manier van vooruitskatting. Die statistiese proses het beter gevaar waar die
produkgroepe min verandering van vorige jare ervaar het, terwyl die ou manier beter
gevaar het waar bemarking self die nuwe aktiwiteite beplan het of bewus was
daarvan. Dit bewys dat statistiese vooruitskatting baie belangrik is om die basis
vooruitskatting te skep, maar dit benodig kwalitatiewe insette van all aandeelhouers.
Statistiese vooruitskattings is dus nie die oplossing vir beter vooruitskattings nie, maar
deel van die oplossing om kragtige vooruitskattings te skep.
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