The Metrics module helps you to set and track key performance indicators and gain other meaningful business insights from your OH&S data. You can perform dynamic analyses on various measures, including both data collected in Cority’s modules and also company-specific or “custom” data.
The Metrics module uses the following terms and concepts:
A measure is a value (or measurement) of data that you would like to visualize in the Data Cube. Measures are typically numeric, e.g. a count or a rate, such as case count. Cority includes standard measures (called Cority measures), such as incident count. You can also capture custom measures, such as targets (e.g incidents or inspections), energy usage rates, production rates, or industry benchmark information.
A dimension describes how you want to categorize, organize, and aggregate the data, e.g. by location. Each Data Cube has a unique set of dimensions that can be used to portion the data for granularity. Each Cority measure has its own set of dimensions which change accordingly. Dimensions are inherently tied to measures; that is, dimensions are measure-dependent. A dimension that is available for one measure might not be available for another.
While “time” is also a dimension, it is chosen separately when constructing the Data Cube.
Custom metrics define your custom measures. You define the time dimension (or recurrence frequency, and start/end date) and the locations or areas to which it applies. For example, you can create a custom metric to capture incident targets annually for a specific location. These custom metrics are assigned to users to record the metric entry (the measure) on a one-time or recurring basis; they can also be associated to related equipment, legal requirements, permits, inspections, and findings and actions. A custom metric can be calculated using an equation that takes into account other custom or standard measures.
A data cube allows the data to be modeled and viewed in Data or Visual view. The Data Cube factors in a dimension (or time dimension), and one or more measures. You can combine Cority measures and custom measures in the Data Cube as long as the dimension(s) chosen for the Data Cube do not conflict with the built-in dimensions defined as part of the custom metric. A Data Cube is useful for comparing actual values to targets (custom values) within the same graph.
For examples of building Data Cubes, see Data Cube Examples.
The workflow for capturing custom metrics data is as follows:
An administrator defines a custom metric, including recurrence, and assigns it to one or more users (see Setting Up Custom Metrics). Multiple metrics for the same topic or program that share the same elements can be combined into a campaign (see Grouping Metrics into a Campaign) for easier completion.
An email notification can be sent to the assigned user(s). The metric entry also appears in the assignee’s My Metrics list.
The assignee completes the metric entry (see Viewing Your Metrics List).
The administrator reviews and approves the metric entry. This may be a separate process if an approval workflow has been created for the campaign (see Using Approval Workflows for a Campaign).
Approved metric entries are available for use in the Data Cube (see Using the Data Cube).