Browse Prior Art Database

Rolling Forecast Attributes of a Time Dimension

IP.com Disclosure Number: IPCOM000174731D
Original Publication Date: 2008-Sep-19
Included in the Prior Art Database: 2008-Sep-19
Document File: 2 page(s) / 23K

Publishing Venue

IBM

Abstract

In today's budgeting and forecasting applications, the process of rolling forecasts from one budgeting period to another is typically a manual one. On a periodic basis, budget data is locked down (actuals) and additional forecast periods are then added to the budget. The rolling forecast process may also include the removal of historical actual data from the budget (oldest) and default data may be added to new forecast periods based on standard forecast algorithms. For most companies, the steps involved in rolling a forecast forward are repeated, vary by period and can be error prone. The automation of these steps, helps reduce risk but has to be repeated for each budget system.

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Rolling Forecast Attributes of a Time Dimension

This invention proposes encapsulating rolling forecast intelligence as metadata in the time dimension. The benefits include reusable, self-documenting rolling forecast rules for budget planning applications or any application requiring the need for rolling forecasts.

Disclosed is a set of time dimension metadata enhancements, which encapsulate the concepts of rolling forecast as part of the metadata. These additional time dimension attributes support rolling forecasts. By defining rolling forecasts attributes at the time dimension level, any budgets/plans created using the time dimension automatically inherit the rolling forecasts defined.

Let's consider an example;

On the first day of every month, company ABC run their monthly forecast on the expense budget. Their monthly forecast includes the following steps:
(1) Data from the oldest month in the budget is removed by removing that period from the time dimension.
(2) Data from the most recent "closed" month is locked down (as actuals).
(3) The time dimension is extended by a month and data for the new month is generated based on forecast projections.

In this simple example, each step must be repeated for all budgets which follow the same rolling forecast rules. Each time the steps are repeated, there is a chance of error

This invention proposes to add rolling forecast intelligence to the time dimension as dimension attributes. Rolling forecast attributes of a time dimension include, but not exclusively, the following attributes;
(1) Roll: One or more "rolls" may be defined for a time dimension. Each roll would define a set of "steps" for rolling data.
(a) Name: Each roll would be uniquely named (ex: weekly, monthly, quarterly)
(b) DropPeriods: Defines a set/region of dimension members to r...