IBM BPM, V8.0.1, All platforms > Authoring services in Integration Designer > Developing monitor models > What are monitor models? > KPI models > KPIs

KPI time filters and data filters

When you define a key performance indicator (KPI) based on the aggregation of a metric, you can specify a time filter to limit the period of time over which the KPI value is calculated. You can also use other metrics as data filters to restrict the set of information that is included in the KPI calculation.

Time filters

When you define a KPI based on the aggregation of a metric, you can specify a limited time period over which the KPI value is calculated. The time period is based on a metric from the same monitoring context as the metric on which the KPI is based. The metric must have a type of Date or DateTime.

For example, if you are monitoring a process, you might have a Start Time metric based on the arrival of the event that starts the process.

The time period can be a repeating (last completed or current period) interval, a rolling (sliding) interval, or a fixed interval.

Repeating interval

Choose a repeating time period to calculate the KPI based on data from a repeating interval of a specific length, which can be a day, a month, a quarter, or a year. You can choose only one such time period to calculate the KPI; for example, the last month. You must also choose whether you want to evaluate data for the last full period or for the current period. If you set the repeating period to monthly and select the last full period, then the KPI will always reflect the value based on the last complete month.

For example, if it is March, the last complete month was February. When April starts, the KPI value is no longer based on the data from February but is based on the data from March. At all times, the KPI is evaluated based on a full month of data. Alternatively, if you select the period in progress, the KPI is evaluated based on the current month. If it is March, the KPI is evaluated based on the March data so far. When April starts, the KPI value is no longer based on the data from March but on the (initially very little) April data.

If you want to see the results from more than one month at the same time, define two KPIs in the model: one for the current month and one for the previous month. Then use a third KPI to compare them and display the result.

Rolling (sliding) interval

Choose a sliding interval to evaluate the KPI data over a window of time that moves continuously, based on minutes, hours, days, months, or years.

For example, you might always want to see the unit sales for the last 90 days. If you set the sliding interval to 90 days, you will see the value of the KPI from 90 days ago up to the current time (not from midnight to midnight).

For example, if it is currently October 17th, 2007 12:30 PM and you select 3 months, the KPI is based on all instances from July 17th, 2007 12:30 PM to October 17th, 2007 12:30 PM. Sliding interval KPIs simply take the current server system time to query the instances in the database.

Fixed interval

Choose a fixed interval if you want the KPI to be calculated for a single time period. You specify a start date and an end date, such as January 1, 2008 to January 31, 2008. If you specify a start date only, the KPI is calculated beginning at that date and continuing to the current date. If you specify an end date only, the KPI is calculated using all data up until the end date.

For repeating time periods and fixed time periods, you can also choose a time zone.

For example, if you wanted to track the average order amount for all orders placed yesterday from a Pacific Standard Time (PST) perspective, you could specify the time zone as GMT-8. The value specified for the time zone helps to determine the values to be included in the KPI calculation. An order that was placed at 2:00 AM Eastern Standard Time (GMT-5) today translates to 11:00 PM PST (GMT-8), and therefore would be included in the calculation.

If you are measuring a period of time that crosses a daylight saving time boundary, you can optionally specify a location based on the time zone you choose. When the KPI is calculated, an hour will be subtracted or added as appropriate for that location.

Data filters

When you define a KPI based on the aggregation of a metric, you can use other metrics as data filters to restrict the set of information that is included in the KPI calculation.

For example, you might have a KPI called Average Price in London. You want to take the Price metric and average it, but you want to use only the monitoring contexts for which the city is London. You select the City metric, select IN for the comparison operator, and type London for the value.

Alternatively, you could have a KPI that measures price values for which the city is either London or Toronto, or a KPI that measures price values in any city that starts with the letter L, or any city that occurs in a list of cities that you specify. As another example, you might be interested in calculating an Average Order Amount KPI when the Customer metric contains the value GOLD or SILVER but not when it contains other values. You can enter a list of values for comparison.

Key performance indicators (KPIs)

Related concepts:
KPI targets and KPI ranges
Aggregate and expression KPIs