Development of outbound volume forecast model
Seppälä, Karolina (2018)
Seppälä, Karolina
Tampereen ammattikorkeakoulu
2018
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2018060713093
https://urn.fi/URN:NBN:fi:amk-2018060713093
Tiivistelmä
The commissioner of this thesis is Metso Minerals Oy. One of company’s biggest distribution centers is a 3PL warehouse located in the Netherlands. The objective of the research was to create a forecasting model for outbound volumes as currently warehouse strictly relies on data from corresponding period of previous year. Unexpected fluctuations of volumes cause challenges with distributing human resources. Better forecasting and resourcing could increase warehouse’s reliability and performance which has also a positive impact on customer satisfaction.
Research methods were mostly quantitative as these were based on statistical data and numerical calculations. In addition to that, analysis was prepared by using judgmental techniques, knowledge of SAP software and business-related facts which had an influence on forecasting.
Forecasting was tested by using several techniques using commonly in business analytics. Moreover, an additional model was developed using available SAP transactions. Testing and statistical data analysis have resulted in creating forecasting dashboard including most suitable methods and elements vital for forecasting and strategy making.
The recommendations included factors which need to be considered for better forecasting and possible scenarios. Additionally, there is a list of practices on how to distribute the volumes more evenly. Improvement suggestions were presented to the management of Distribution Center Europe in Tampere, Finland.
Research methods were mostly quantitative as these were based on statistical data and numerical calculations. In addition to that, analysis was prepared by using judgmental techniques, knowledge of SAP software and business-related facts which had an influence on forecasting.
Forecasting was tested by using several techniques using commonly in business analytics. Moreover, an additional model was developed using available SAP transactions. Testing and statistical data analysis have resulted in creating forecasting dashboard including most suitable methods and elements vital for forecasting and strategy making.
The recommendations included factors which need to be considered for better forecasting and possible scenarios. Additionally, there is a list of practices on how to distribute the volumes more evenly. Improvement suggestions were presented to the management of Distribution Center Europe in Tampere, Finland.