Neha More

Forecasting Tractor Sales using Time Series ARIMA Model.

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OBJECTIVE

Building ARIMA model to forecast sale / demand of tractors for next 3 years for a farm equipment manufacturing company.

PROBLEM STATEMENT

PowerHorse, a tractor and farm equipment manufacturing company, was established a few years after World War II. The company has shown a consistent growth in its revenue from tractor sales since its inception. However, over the years the company has struggled to keep it’s inventory and production cost down because of variability in sales and tractor demand. The management at PowerHorse is under enormous pressure from the shareholders and board to reduce the production cost.

You have to develop an ARIMA model to forecast sale / demand of tractors for next 3 years.

PROJECT METHODOLOGY

The steps followed in the project are given below:

Step 1: Reading and Ploting tractor sales data as time series.
Step 2. Difference data to make data stationary on mean. (remove trend)
Step 3. log transform data to make data stationary on variance.
Step 4. Difference log transform data to make data stationary on both mean and variance.
Step 5. Plot ACF and PACF to identify potential AR and MA model.
Step 6. Identification of best fit ARIMA model.
Step 7. Forecast sales using the best fit ARIMA model.
Step 8: Plot ACF and PACF for residuals of ARIMA model to ensure no more information is left for extraction.