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Tutorial 1 - Solutions (Chapter 2 - Demand Forecasting)

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Operations Management, Supply Chain Management

Última actualización de este documento: 5 año hace

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  • 28 de marzo de 2018
  • 17 de diciembre de 2018
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Professor
Dr.-Ing. Bernd Helling-
rath
Chair for Information Systems and
Leonardo-Campus 3
48149 Münster

Tel. +49 251 83-38000
Fax +49 251 83-38009
Hellingrath@ercis.de




Tutorial Operations Management
Chapter 2 – Demand Forecasting (Part 1)
Solutions

Exercise 1: Basics of Demand Forecasting, Forecasting Methods

a)

 Basics
– A demand forecast estimates the future development of the demand.
– The demand forecast is the basis for almost all planning activities.
– Structured process

 Relevance
– Good forecasts are crucial for companies to create a competitive advantage, i.e. through
the reduction of expensive inventories, decrease of backlog etc.

 Good forecasts have these characteristics:
– Punctual/timely forecast, accuracy, reliability, reasonable units, written documentation,
easily understandable, cost-efficient

, 2


b)

 Qualitative forecasts
– Sales estimation
o Sales employees have regularly and frequently direct contact to the customers.
Therefore, they are able to gather good information about the customers’ de-
mand.
– Customer survey
o Systematic survey of customers (creation of questionnaires, Selecting repre-
sentative random survey samples of customers, Executing the survey, Evaluat-
ing the survey and creating the forecast)
– Expert estimation
o Management personnel have good information about the newest developments
and future product introductions.
– Delphi-Method
o Anonymous written answers favor honesty and prevent the group from being
dominated by only few members


 Quantitative forecasts
– Causal forecast
o A function is estimated representing the dependency of the demand on a
known variable.
o Is used if the demand can be forecasted based on a known variable.
o Methods (cf. tasks 2 and 3)
 Linear Regression
 Non-Linear Regression
– Time Series Based Forecasts
o The demand is estimated on the basis of past data.

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