Metrics, in terms of Business Intelligence
, are quantitative values that are used to measure progress towards a set of objectives over time. The term 'performance metrics' is often used, and some metrics are also associated with Key Performance Indicators
which are directly tied to the goals of an organization.
Metrics are quantitative in nature, while dimensions
are qualitative, or categorical. Dimensions are used to slice and dice metrics. For example, if a report highlights the number of sales per product, sales is the metric and product is the dimension. If the report is further broken down to show state specific figures, state is another dimension in the report.
- What Makes a Metric?
- Association Metrics
- See Also
- Sources and further reading
What Makes a Metric?
Every metric needs a clear definition that includes the following information:
- A unique name: Often different departments in the same organization may use the different formulas for a similar metric. To ensure that all audiences understand which metric they are analyzing, enforce unique and descriptive names. For example using the name of Sales is not descriptive, it leaves open for interpretation if the metric is Gross Sales or Net Sales.
- A description: Describe the metric in as much detail as possible
- A formula: Indicate how the metric is derived. Is it a count of something, an average, or is there a custom formula involved?
- Units of measurement: Indicate how the metric is measured. For example it could be measured in currency or centimeters.
- Associated Values: A metric should have at least two values associated with it. The first value is the current actual value of the metric and the second value is the target value. In addition to these values there are several optional values that may be calculated such as an expected standard deviation and high and low thresholds.
The metrics tracked by different organizations vary depending on the strategic goals and objectives of the organization. An example of a common goal and its potential associated metrics are listed below.
Membership can be increased over time by adding new members to the association and also retaining existing customers. Some sample metrics that are useful when measuring progress in this area are:
- Beginning of Period (BOP) Members: Defined as the number of individuals who held membership on the first day of the year.
- New Members: Defined as a count of individuals who were not members on the first day of the year but are currently members.
- Lost Members: Defined as a count of individuals who were members on the first day of the year but are not currently members.
- End of Period (EOP) Members: Calculated as EOP = BOP + New Members - Lost Members.
- Churn: Defined as the percentage of members who discontinue membership during the time period specified. Churn calculations are an area of controversy. One of the widely accepted formulas is Lost Members / (BOP Members + New Members).
In addition to this set of somewhat obvious metrics, there are many metrics that may not come to mind immediately, but might have a direct impact on the goal at hand. Customer Satisfaction
for example impacts a member's decision to renew membership year after year. Sometimes there is a clear way to measure this metric, such as through the use of a survey or poll. Other times different metrics that contribute to the overall experience of the customer have to be considered. For example, if a product is sold to a customer, examining the Return Rate
provides insight into the customer's satisfaction with the product. If a computer service is offered to the customer, examining the number of Trouble Tickets
may provide critical insights in this area.
See Also:DimensionsCubesBusiness IntelligenceBalanced ScorecardKey Performance Indicators
Sources and further reading:
The core of this entry was written by:
Solutions ArchitectSusquehanna Technologies