Detailed data tables

Getting to the detail behind the numbers

Quite often the numbers being collected or reported don’t tell the whole story. For example we may be collecting a sales forecast figure, but management at head office may want to know what that number represents - how many potential customers does it include, what products are they ordering and so on.Similarly, when reporting actual results, departmental managers may see a figure for expenses that were booked in the month, but what they would like to see are the detailed transactions that make up that number.The trouble with this detail is that it doesn’t fit into a regular set of rows that most planning systems require. This is important, as when consolidating data, those systems rely on the same records on every sheet being in the same position, otherwise the consolidation rules become complex and prone to error.

Making the numbers make sense

Financial Driver overcomes these issues with its unique Detailed Data Table (DDT) capability that can collect and hold details behind any number. That detail can include a range of text and other data that may be unique for a particular department.In the above example, sales forecasts can include customer and contract detail as well as potential opportunities and the probability of completing the sale. For expenses that detail can contain the GL account code, transaction ID and date posted.This data is then summarised and used to populate the appropriate member in Financial Driver’s account dimension

Making Detail part of the plan

With DDT, Financial Driver becomes a powerful planning and financial reporting tool. Rather than just handle data at a summary account level, it is able to go into detail such as when planning salaries by person, or tracking payments by invoice. All of which are then tied to the organisations P & L summary.

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