Optimisation of Warehouse Forecasting Sale

The data set that we have received, is the historical product demand for a manufacturing company. The manufacturing company produces a variety of goods which are stored in four central warehouses that they own. A particular type of good can be shipped to different warehouses. The challenge of this project is to be able to help forecast the product demand in order to maximize manufacturing company’s profit by meeting demand for various products as well as minimizing costs from holding inventory.

 

As there are many rows of data for various different products, we use stratified sampling to pick a various products to analyse. Through visualizing the data on Excel and statiscal analysis, we seek to find an optimal model we can use to predict the future demand, use the results to compare the consistency of the model and whether the same parameters can be used across all the different products.

Team Members
  • Kenny Ng

  • Reuben Tan

  • Lucas Ng

  • Tan Yin Ling

  • Evan Sidhi

  • Ng Jing Da