Learn how to do demand forecasting in under two minutes with VAYU, the no-code data science notebook!
The FMCG industry is full of complexities. An enormous amount of transactions are generated by this fast-moving sector, creating numerous challenges along the way, especially where big data analysis is concerned.
The main challenge is to interpret this data, to make it meaningful and actionable.
So how then do we translate this information into insight, for more profitable operations and more effective strategies?
Follow along with this step-by-step guide and video to forecast demand for your own dataset (or use one that we’ve provided).
Demand Forecasting in 8 steps!
Sign up to GYANA here and follow these eight easy steps to forecast demand.
- Add your historical demand dataset
- Add a table to your project, then connect your data to this table
- Next, add a chart and connect it to your table
- To model your historical demand, drag Date or MonthYear into the x-axis field, and SUM (Order Demand) into the y-axis field
- To view the historical demand across different categories, try dragging variables such as Warehouse or Product Category into the colors field
- To model monthly demand instead, place Date into the x-axis field and clarify this by MONTH
- Select a bar chart from the visualization options, and color the data by product to model how demand for products might vary throughout the year
- Make use of the mean, median, sum and range functions, as well as many more, to visualize all aspects of your demand data.
8 steps. 2 minutes.
1 insightful demand forecast.