As more companies turn to data to help guide business decisions, you often come across two concepts: metrics and analytics. While the two do share some common features, they are fundamentally different in many ways. However, they are both incredibly valuable, as long as you know how to use them wisely. To help you understand their role in business more clearly, here’s what you need to know.
What is Metrics?
At their core, metrics are typically associated with operational measures1. They are used to analyze performance, efficiency and the impact of certain practices or changes. For example, if you examine the amount of turnover in a particular department and calculate it as a percentage based on that area’s total staff count, that would be a metric.
Metrics tell you what is happening, or has recently happened, based on hard data. They are often defined by an objective, such as having a particular retention rate or increasing production by a specific percentage and tend to represent a fairly rigid target.
What is Analytics?
Analytics focus on comparing variables to guide future decisions. Often, the focus is on developing business measures that can predict future outcomes, allowing you to anticipate the impact of individual decisions in advance.
Often, analytics help identify patterns that may not be easily visible. For example, you may use analytics to find commonalities between employees who chose to leave the company, allowing you to create a plan to remedy issues that may lead other workers to go down the same path.
Analytics, like metrics, are based on hard data, but they look beyond the numbers to try to find causations and correlations that may otherwise be difficult to spot.
Both metrics and analytics are powerful tools, as they provide you with insights into your company’s operations. Ultimately, metrics can feed analytics, as it is a source of vital data that, when reviewed properly, can help shape future decisions and objectives.
Generally, metrics serve as a barometer, indicating which areas of the business are performing as desired and identifying potential shortcomings. However, they alone won’t tell you what needs to be done to improve the areas that are struggling.
Analytics creates a path towards solutions, but doesn’t provide much value without the sound data metrics can provide. In that regard, the two concepts are best used in conjunction with one another, as metrics support analytics, analytics offer guidance about how to improve your metrics, and future metrics let you know if the results of the analytics were accurate.
Once you begin using them both, you’ll see the relationship is highly symbiotic, with metrics and analytics creating a circular process for measuring business health and the effectiveness of policies and procedures. However, to be reliable, high-quality data is required, as faulty data will create inaccurate results.
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