Best Practices for Leveraging Metrics
Follow these guidelines to maximize the value gained from using metrics in analytics:
- Clarify goals – Identify the specific business objectives, processes or capabilities being measured. Metrics must align to goals and desired outcomes.
- Limit to critical few – Select a focused set of 4-5 metrics per domain to avoid overload. Too many dilutes focus on what matters most.
- Provide context – Metrics alone do not gives complete information, interpret together with other data. Context gives meaning.
- Set targets – Define measurable quantitative desired outcomes for each metric. Targets drive strategic alignment.
- Track trends – Monitor metrics over time via dashboards to identify patterns and changes. Trend analysis provides insights.
- Automate collection – Incorporate metric capture and calculation into systems to simplify analysis. Manual metrics are difficult to collect consistently.
- Visualize results – Charts, dashboards and reports should make metrics easy to understand.
- Re-evaluate periodically – Review metrics against objectives and refine as needed.
- Supplement with qualitative data – Combine quantitative metrics with user information and context.
What is a Metric in Analytics ?
Metrics are foundational elements in the world of data analytics and business intelligence. A metric refers to a quantifiable measure that is used to track, monitor, and assess the performance of individuals, teams, systems, and organizations toward desired results.
Choosing the right metrics effectively provides good value in driving data-informed decisions and strategy. In this article we will see what is a metric along with guidelines and examples for applying metrics successfully in analytics.