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In the context of the ERP solutions, NSI IT Software & Services is a Microsoft’s ERP solutions
provider. This company has different types of customers: some big customers who use
Microsoft Dynamics AX and some smaller customers like very small enterprises (VSE) and
small and medium enterprises (SME) who use Microsoft Dynamics NAV. NSI has noted that
some of the customers using Microsoft Dynamics NAV did not have the sufficient maturity to
understand the theme of the forecasts and realize them. Moreover, it also exists a demand from
some of these customers to have a tool in Microsoft Dynamics NAV that helps them to
understand and compute demand forecasts. The final objective of this project-thesis is to obtain
a functional didactic and intuitive tool for the final users.
Firstly, this project-thesis is focused on the analysis of the existing solutions and their
features and also on the identification of the customers’ needs with the interview of two NSI’s
project leaders.
Secondly, the different types of forecasting methods are exposed and explained but the
list of the forecasting methods in this project-thesis is non-exhaustive. The quantitative
forecasting methods from the time series analysis (exponential smoothing, moving average,
linear regression) are chosen to realize the functional didactic and intuitive forecasting tool.
Finally, the last step of this project thesis is the development and the conceptualization
of the forecasting tool. This forecasting tool has to be intuitive and didactic. Now this tool is
developed in an Excel format but it can be developed later as an add-on or an extension for
Microsoft Dynamics NAV to be fully-integrated. The tool appears as follows: the first step is a
questionnaire for the user; the different elements and their effect are explained. Then, with the
user’s answers the tool is able to attribute a forecasting method thanks to possible answers
combinations.

Demand forecasting --- ERP --- forecasting methods --- forecasting tool --- IT --- Microsoft Dynamics NAV --- MRP --- Sciences économiques & de gestion > Production, distribution & gestion de la chaîne logistique