Trust in Data: The Clarity of Shared Definitions
Allan WillePublished 2025-06-03Summary: In today's data-driven world, trust in the information we rely on is paramount. When everyone is on the same page regarding what metrics mean, making informed decisions becomes much easier. However, when definitions diverge, confusion and mistrust quickly follow. This article addresses the common challenge of data mistrust and offers advice for data professionals and business users aiming to foster a data-trustworthy environment.
Hey everyone! I keep running into this challenge, and I'm sure many of you do too: differing interpretations of data. When we can't agree on what our metrics mean, building trust in data becomes incredibly difficult. So, let's talk about the power of shared definitions and how they can make all the difference.
The Growing Pain of Data Discord
As organizations expand, more people seek data to support their roles, leading to an increased demand for reports and dashboards. Unfortunately, with this growth often comes disagreement on how key metrics should be defined. Imagine a typical Monday morning meeting where sales figures are discussed. One person reports one number, while another offers a slightly different figure, and accounting may even have yet another. The underlying issue is rarely that someone is wrong, but rather, that they are using slightly different definitions for the same term—in this case, "sales."
For example, John might be reporting gross sales, Mary might be using net sales (after taxes), and the accounting team might be looking at net sales after accounting for refunds and returns. While each number is valid in its respective context, the use of the same term with different meanings leads to confusion and distrust.
Watch this quick video to see what I mean:
The Importance of Definitive Definitions
To resolve this issue, it's essential to be definitive about the definitions, expressions, and calculations of your metrics. This means clearly outlining what's included in the metric, how it's calculated, and where the data originates. Key questions to address include:
- What is it called? Ensure everyone uses the same term.
- Does everyone agree on the definition? Achieve consensus on what the metric represents.
- How is it calculated? Provide a clear formula or method.
- Where does the data come from? Specify the source of the information.
By establishing these details, you are implementing what we refer to as the "semantic movement" where meaning and lineage are applied to data and metrics. This process helps ensure that everyone has a shared understanding and, consequently, identical numbers when discussing the same metric.
Practical Steps for Establishing Shared Definitions
To cultivate trust in your data, take the following steps:
- Document Definitions: Create and maintain a central repository of metric definitions. This should include the name, definition, calculation method, and data source for each metric.
- Gain Consensus: Involve key stakeholders from various departments in defining metrics. This collaborative approach ensures everyone understands and agrees on the definitions.'
- Communicate Clearly: Regularly communicate the definitions to all relevant parties. Ensure that reports and dashboards include clear descriptions of the metrics used.
- Maintain Data Lineage: Track the origin and transformation of your data. This provides transparency and helps troubleshoot discrepancies.
- Regular Review: Schedule periodic reviews of metric definitions to ensure they remain relevant and accurate as business needs evolve.
By establishing and adhering to clear, shared definitions, organizations can significantly enhance data trust. When everyone agrees on what the numbers mean, productive and efficient meetings become more frequent and decisions will be based on trustworthy and consistent information.