Domains› Church Management› Reporting› Metrics›

Intro to Metrics

Metrics are defined with categories, very similar to data views and reports. This allows you to organize them in a way that makes sense for your organization. One thing that is unique about metrics is that they can be linked to more than one category. This allows you to re-use them in several areas of your metric hierarchy.

So how do we create a new metric? Administrating metrics is done under Tools > Metrics. For our example we'll create a new metric that displays the number of adult members and attendees we’ve had each week. Here are the details of the completed metric with callouts for each field.

  1. Schedule and History - At the top of the page, you can see the current schedule this metric is running on, and the last time the Metric was run.
  2. Title - Be sure to provide detailed titles for your metrics that not only make sense to you, but also to those who will be using these metrics in the future.
  3. Icon CSS Class - The CSS class of the icon you wish to associate with the metric. This is used in the display of the metric. Rock uses the Font Awesome icon set by default, but any CSS based icon set can be used if properly configured.
  4. Subtitle - The subtitle will be shown on graphs and charts.
  5. Description - You'll be tempted to just skip right over this field, but you'll regret that in the future. No matter how obvious you feel this metric is, future you is screaming for you to add details about what is being measured, how it's calculated, any filter specifics (like only members), etc. Be kind to future you and document as much as you can. When you're done, go ahead and thank yourself ahead of time.
  6. Metric Champion - One of the keys to good metrics is good documentation. In that regard we’ve worked hard to be sure that metrics become self-documenting. The metric champion allows you to note the person in your organization who is responsible for confirming that this metric is meeting its goals.
  7. Metric Administrator - The metric administrator is the individual in your organization who is responsible for ensuring that the metric data is entered correctly and is valid.8 CategoriesThis field allows you to link your metric to one or more categories.
  8. Measurement Classification - Classifies the metric, to ensure it’s known what the metric is measuring. For instance, the Total Weekend Attendance classification would be tied to the single metric that’s used for tracking total weekend attendance. This enables the system to utilize these metrics for analytics. See below for additional details.
  9. Units Label - The y-axis label describes the units of what is being measured (people, groups, money, etc.)
  10. Cumulative - Some metrics make sense to compare year-to-date, others - not so much. For instance, it's often helpful to look at year-to-date values for adult members and attendees. But a metric that tracks attendance for a service or event often does not make sense to evaluate the same way. This field allows Rock to know if cumulative comparisons make sense for this specific value.
  11. Unit Type - Metrics can track different types of data, so you can use the Unit Type setting to tell Rock you're working with numbers, currency or percentages. What you choose here will determine how the metric values appear in different areas, like on the metric's chart. For instance, if you select Percentage then the y-axis on the chart will show 10%, 20%, etc.
  12. Enable Analytics - Check this box if you want the metrics to be made available for use by analytic tools such as Power BI.
  13. Source Type - The source type defines how the metrics will be entered into the system. The options are:
    1. Manual: Metric values will be entered in manually.
    2. SQL: A SQL statement will be run to populate the values. Once you select this option a SQL entry input will be displayed. The help menu for the SQL field provides in-depth information on how your SQL should be formatted.
    3. Data View: A data view will be executed, and the count of its values will be added to the metric with the date it was run. The help field here also displays information on configuring your data view.
    4. Lava: Lava will be used to generate the values. When you select this option, a Source Lava field will be displayed. This is where you add your Lava code. The help menu offers examples of Lava that could be used for metrics. To learn more about Lava, go to
  14. ScheduleThe b - metric schedule helps determine how often this metric is calculated. When used with the SQL, Lava and Data View source types, this field will actually tell Rock when to automate the harvesting of metric values.
  15. Auto Partition on Primary Campus - Data View source types don't support partitions, with one exception. If your data view returns people, and if you only have a single Partition of type Campus, you can select this option to have the metric return people by campus.
  16. Series Partitions - For simple metrics you're done, you can skip this section. Often times though you want to break your metrics down by campus, or maybe campus then service time. Setting up series partitions allows you to do just that. You always get the date partition (that's free), but you can set up as many partitions as you feel necessary (but more than two can get a bit complex).

Tip

Supercharge Your Metrics with Lava
Using Lava as the data source for your metrics is powerful. With Lava entity commands you can now access data from external systems and include it in your reporting. For example, you can use the web request command to make remote API calls and pull bank account balances from your accounting system, data from Planning Center, or info from Church Metrics. When it comes to Lava and reporting, the sky is the limit! To learn more about Lava, go to https://community.rockrms.com/lava.  

Measurement Classifications

Measurement Classifications help Rock unlock deeper insights from your metrics by adding meaning and context to the data they capture. Each metric in Rock can be assigned a specific classification that indicates exactly what that metric measures. For example, you might classify a metric as "Total Weekend Attendance" to give Rock a clear, consistent understanding of that data point across all systems.

The Measurement Classifications that ship with Rock are listed below:

  • Total Weekend Attendance: This metric measures the total weekend attendance for the organization, partitioned by campus and schedule.
  • Volunteer Attendance: Measures the number of volunteers that served for the given week. Partitioned by campus and schedule.
  • Prayer Requests: The number of active prayer requests for the given week. This metric should be partitioned by campus.
  • Prayers: The number of prayers for the given week. This metric should be partitioned by campus.
  • Active Families: The number of active families in the given week. This metric should be partitioned by campus.
  • Baptisms: The number of baptisms in a given month. This metric should be partitioned by campus.
  • Giving: This metric represents weekly giving. It's up to you to define the financial accounts that make up this metric. This metric should be partitioned by the campus of the financial account. Review the account list in this metric to decide if you want to modify the 
  • eRA Weekly Wins: Tracks the number of individuals who attained eRA status within the current week. This metric should be partitioned by campus.
  • eRA Weekly Losses: Monitors the number of individuals who exited eRA status in the current week. This metric should be partitioned by campus.

Using one metric for each classification ensures that we have a single, reliable source of truth for critical data like attendance or giving. This accuracy allows Rock to automate tasks, create reports, and even generate future features that draw directly from your specific metrics, tailored to match what each metric represents. Without Measurement Classifications, Rock could only see raw data points. Now, it knows what each one means.

To use Measurement Classifications effectively, select the correct classification for applicable metrics and be sure to configure your metrics precisely as specified. Each classification is associated with a Defined Value, which outlines essential configuration requirements for that metric. Think of these requirements as a blueprint. They help ensure the data tagged with a classification fits consistently within Rock’s framework. If a metric doesn't exactly match these requirements, it shouldn't carry the classification, since even small discrepancies could lead to inaccurate results.

Metrics Add Metrics Values