Defining a revenue metric in Transform (Part 2): Add context, ask questions, and assign metrics owners

Revenue is a very important, but very tricky metric to define. In part 1 of this series, we looked at how a fictional song manufacturing company, CustomSong Inc, uses Transform’s Metric Framework to create alignment by defining their metrics in code.

In this article, we’ll discuss how you create alignment across teams by:

  • Adding context with metadata and annotations
  • Sharing how a metric was built with metric lineage
  • Creating accountability with metric owners
  • Ranking metrics by business priority

Recording important metric metadata and annotations

Because revenue is a complicated metric, it requires a lot of context to understand. In the same way, if you use data for your day-to-day decision-making, you've probably thought about how a metric was constructed—where it comes from, who constructed it, and how it was defined. You’ve probably also had some questions around its context, including how the metric value has changed over time.

Now that you have a consistent definition for revenue, that definition needs to be accessible and associated with other relevant information about the metric. With Transform, a complete history of the metric’s metadata, like a metric owner, is displayed alongside the metric.

The Transform Metrics Catalog provides an easy-to-use UI for your data consumers to explore and understand the context around important metrics. When paired with the Metrics Framework, the Metrics Catalog becomes a single source of truth for your organization's metrics where data and business teams can collaborate.

Aligning on a common definition for revenue:

Metric description and definition are meant to help business users understand what a metric means. At the top of the Metric Page, you will find a configuration section that includes the definition. There are two definitions. The definition with a lock next to it is the one defined in code in the Metrics Framework. This definition cannot be changed unless done in code. There is also a text-editable description that metric owners can edit to provide additional context to consumers of the data—and this text supports markdown format.

Understand how your revenue metric was built:

With Metric Lineage, you can understand the source and calculation of your revenue metric. Opening the Metric Lineage panel will expose what Data Source the metric comes from, what measure it's derived from, and the metric definition itself. Clicking into the YAML link will open a code snippet for each respective component. If the metric is derived from multiple measures (e.g., ratio or expression), the lineage will indicate this. Finally, you can click "View Code" which will navigate you to Github where these files were committed to Transform.

Rank your metrics by business value:

Metric tiers represent the importance of the metric in a given organization. Tiers options are 1, 2, and 3. Tiers ensure that the most important metrics—like revenue—are treated with utmost priority, and also provide context to a business consumer on the relative visibility/priority of a given metric. Transform recommends that users set a scale for metrics based on trust, importance, or visibility. For example, Tier 1 might be the most visible and important metrics that are accessed by everyone in a company, while Tier 3 might be only used by particular teams.

Add context with annotations:  

There are many scenarios where a notable spike or dip is present in the data, but the knowledge about those events is siloed. In this example, CustomSong did a Halloween promotion to create custom spooky tunes. The Transform Annotations feature captures that annotation and relates it to all relevant metrics and dimensions. Annotations aim to change the paradigm so anyone—including both consumers or producers of data—can get the context that they need about a metric value. Annotations are exposed on the metric chart for all metrics and dimensions affected through an icon at the top of the graph. They are shown by default and you can optionally hide them by using the graph toggle. Clicking into the annotation on the graph will show you a summary of the annotation.

Metrics questions and answers:

Pull conversations out of email and direct messages and into a space that allows others to learn from those conversations. Questions on the metric page allow users to interact and ask questions of metric owners in order to get a better understanding of the metric.

Slice and dice your revenue metric by dimensions:

Many data consumers want to understand a metric value as it applies to a particular attribute of the data. For example, the CustomSong growth team focused on Canada and France since their team has a special interest in global revenue metric as it applies to those two countries. As opposed to reaching out to an analyst to write an arbitrary query for this data, Transform has lightweight visualizations in the Metrics Catalog. These charting features allow for simple dimensional slices on a metric value so that end users can self-serve while simultaneously having confidence in their provided data:

These simple cuts of data can get both business users and analysts far in their analysis and open up doors to more insights.

Bring accountability to your revenue metric

Assign an owner to your metric:

Metric owners help with governance and metric management. For the revenue metric, this is often a finance team. Data consumers want to know who to come to with questions and who is the ultimate approver for the metric definition. This way, there is always an accountable person or team responsible for approving the metric.  because consumers of data will always know which teams or users to talk to about particular metrics, and there is an accountable party who will approve the metric. Transform allows for either team or individual owners, but we recommend team ownership to ensure redundancy across an organization.

“Approve” a metric to establish trust:

Metric approval is an important part of the lifecycle management of a metric. It dictates how often the metric is reviewed by an owner so that consumers can be confident that it is ready to share broadly. Having consistent approval cadences ensures the metric is up to date, accurate, and can be used for reporting within an organization. The "Last Approved Date" indicates the last time the owner(s) approved the metric.

Get all your teams on the same page

Defining a consistent revenue metric is critical for every company. But without the proper context, teams can still have trouble with alignment.

Transform’s Metric Catalog gives everyone insight into how a metric was built and how it has changed over time. And with metric owners, there is a foundation of accountability and a point of contact for questions and discussion. Learn more about Transform’s Metric Catalog and the Annotations feature.

Belinda Bennett

Belinda Bennett

Belinda is a Data Science Manager at Transform.