Running a Model

When you run a model, you should keep these points in mind:

• Before you run a model, the input data must be available in the solution variable. For example, before running the income.calc model (shown earlier in this chapter) with actual as the solution variable, you must have current data in the revenue, cogs, marketing, selling, r.d, and taxes line items of actual.
• Before running a model that contains a block of simultaneous equations, you might want to check or modify the values of some OLAP DML options that control the solution of simultaneous blocks. Simultaneous equations are discussed in the section entitled "Solving Simultaneous Equations".
• If your model contains any dimension-based equations, then you must provide a numeric solution variable that serves both as a source of data and as the assignment target for equation results. The solution variable is usually dimensioned by all the dimensions on which model equations are based, and it can have "extra" dimensions as well.
• When you run a model, a loop is performed automatically over the values in the current status list of each of the extra dimensions of the solution variable.
• If a model equation bases its calculations on data from previous time periods (for example, if you use a LAG function), then the solution variable must contain data for these previous periods. If it does not, or if the first value of the time dimension is in the status, then the results of the calculation will be NA.

Using Data from Past and Future Time Periods

Several OLAP DML functions make it easy for you to use data from past or future time periods. For example, the LAG function returns data from a specified previous time period, and the LEAD function returns data from a specified future period. The Oracle9i OLAP DML Reference help lists some built-in functions that are useful in analyzing financial data.

When you run a model that uses past or future data in its calculations, you must make sure that your solution variable contains the necessary past or future data. For example, a model might contain an assignment statement (that is, the = command) that bases an estimate of the revenue line item for the current month on the revenue line item for the previous month.

DIMENSION line month
.
.
.
revenue = LAG(revenue, 1, month) * 1.05

If the month dimension is limited to apr96 to jun96 when you run the model, then you must be sure that the solution variable contains revenue data for mar96.

If your model contains a LEAD function, then your solution variable must contain the necessary future data. For example, if you want to calculate data for the months of April through June of 1996, and if the model retrieves data from one month in the future, then the solution variable must contain data for July 1996 when you run the model.

Solving Simultaneous Equations

An iterative method is used to solve the equations in a simultaneous block. In each iteration, a value is calculated for each equation, and compares the new value to the value from the previous iteration. If the comparison falls within a specified tolerance, then the equation is considered to have converged to a solution. If the comparison exceeds a specified limit, then the equation is considered to have diverged.

If all the equations in the block converge, then the block is considered solved. If any equation diverges or fails to converge within a specified number of iterations, then the solution of the block (and the model) fails and an error occurs.

You can use OLAP DML options to exercise control over the solution of simultaneous equations. For example, you can specify the solution method to use, the factors to use in testing for convergence and divergence, the maximum number of iterations to perform, and the action to take when the = command diverges or fails to converge.