Revenue and cost forecasting model for heavy engineering industry
Ahvonen, Tuomas (2018)
Ahvonen, Tuomas
Haaga-Helia ammattikorkeakoulu
2018
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-201805066700
https://urn.fi/URN:NBN:fi:amk-201805066700
Tiivistelmä
Forecasting the revenue and costs is an important aspect of the financial management of a company and thus the process should be as accurate as possible. The forecasts, such as budgets, are used in the decision-making of the management and as such must be informative as well as reliable.
To fulfil this need, this project-based thesis aims to create an automatic forecasting model for the commissioning organisation to be used in the company’s monthly net sales as well as profit and loss forecasting process. The commissioning organisation operates in a heavy engineering industry with variable customer base and thus variable production level as well as revenue and cost level.
The objectives of this thesis are divided into one main objective and four sub objectives. The main objective of the thesis is to create the forecasting model for the commissioning organisation utilising the Excel VBA language to automate the process. The sub objectives were divided into four individual aspects: to create a more accurate forecast to allow the management to make informed decisions, reducing the manual work associated to the forecasting process, eliminating errors and creating an easy interface for the users.
All of the objectives were achieved during the project. The model is in regular use in the commissioning organisation in the forecasting process. The accuracy increase was achieved by linking the customer’s forecasts with the company’s own internal data to make an up-to-date accurate forecast that could still be modified according to the user view on the matter. The automation reduced the manual work as well as the time spent on the forecasting process, although as the forecasting tool was developed further some of this gain was lost because the accuracy of the forecast was deemed more important. The automation also reduced the possibility of errors in the transference of the data as this was done by the program created. The model has been used on multiple forecasting rounds in the company, and the usage of the final model has been easy enough to manage and extract the data needed.
The accuracy of the forecasts produced by the model were evaluated during the model’s use in the spring of 2018. Although small deviations were experienced in the comparisons between the forecasted and actual revenue and costs incurred from the operations, no significant issues were found in the forecasts. The model will be developed further in the future as new information is needed and wanted by the management regarding the financial operations of the company. For example, capacity data regarding the production is one of the main development topics for the future for the model. The overall process was successful both for the achievement of the thesis’ objectives as well as company’s management’s opinion of the final result.
To fulfil this need, this project-based thesis aims to create an automatic forecasting model for the commissioning organisation to be used in the company’s monthly net sales as well as profit and loss forecasting process. The commissioning organisation operates in a heavy engineering industry with variable customer base and thus variable production level as well as revenue and cost level.
The objectives of this thesis are divided into one main objective and four sub objectives. The main objective of the thesis is to create the forecasting model for the commissioning organisation utilising the Excel VBA language to automate the process. The sub objectives were divided into four individual aspects: to create a more accurate forecast to allow the management to make informed decisions, reducing the manual work associated to the forecasting process, eliminating errors and creating an easy interface for the users.
All of the objectives were achieved during the project. The model is in regular use in the commissioning organisation in the forecasting process. The accuracy increase was achieved by linking the customer’s forecasts with the company’s own internal data to make an up-to-date accurate forecast that could still be modified according to the user view on the matter. The automation reduced the manual work as well as the time spent on the forecasting process, although as the forecasting tool was developed further some of this gain was lost because the accuracy of the forecast was deemed more important. The automation also reduced the possibility of errors in the transference of the data as this was done by the program created. The model has been used on multiple forecasting rounds in the company, and the usage of the final model has been easy enough to manage and extract the data needed.
The accuracy of the forecasts produced by the model were evaluated during the model’s use in the spring of 2018. Although small deviations were experienced in the comparisons between the forecasted and actual revenue and costs incurred from the operations, no significant issues were found in the forecasts. The model will be developed further in the future as new information is needed and wanted by the management regarding the financial operations of the company. For example, capacity data regarding the production is one of the main development topics for the future for the model. The overall process was successful both for the achievement of the thesis’ objectives as well as company’s management’s opinion of the final result.