There are plenty of tools in the market that support some, if not all, of an organization's forecasting and reporting needs; however this book is not about forecasting tools, so there is no advantage in detailing and debating which tool to use—we'll just pick one of the better ones, that is, IBM Planning Analytics.
If you are not familiar with the tool, the following may provide a bit of perspective:
- (IBM.com)
Another fine reason for choosing this tool is that IBM Planning Analytics not only empowers users, but facilitates practices such as driver-based planning and rolling forecasts. Users of IBM Planning Analytics can perform complex dimensional calculations to analyze product profitability, sales mix, and price/volume variance, and so on.
Perhaps the most important point is that:
- (IBM.com)
So, the key objective of this chapter's project is to use Watson Analytics to (hopefully) improve on a user-created (in Planning Analytics) forecast. We will use Watson Analytics to explore sales data at a deeper level with rich visualizations and identify new insights on the available product performance data.