Framing the content of a Dashboard

This article aims to provide some advice and useful tips for Dashboard creation.

Four useful steps to frame a Dashboard

Designing an effective Dashboard requires careful planning and consideration. Whether you're a data analyst, risk manager (GRC), compliance officer or a business leader, following these four steps will help you to frame the content of your Dashboard in a way that delivers actionable insights and tells a powerful story.

1. Define your goal: What needs to be measured?

   To kickstart your Dashboard creation process on Panaseer, clearly identify the purpose of your Dashboard. Ask yourself, "What specific question am I trying to answer or what goal am I aiming to achieve?". Having a well-defined goal will serve as the guiding light throughout the Dashboard creation journey.

2. Split your overarching question/goal: Unravel the smaller questions

   Break down your overarching question or goal into smaller, more manageable questions. These smaller questions will act as building blocks, helping you to answer the larger question or demonstrate that the goal is being achieved. Organizing your Panaseer Dashboard in this way ensures clarity and coherence in presenting insights.

3. Define metrics and KPIs: Supporting your goal with data

   With the Panaseer platform at your fingertips, it's time to choose the right metrics and Key Performance Indicators (KPIs). Explore the metrics catalogue and select the ones that closely align with your defined goals. Ensuring a direct connection between your chosen metrics and your objectives will enhance the effectiveness of your Panaseer Dashboard.

4. Tailor your breakdowns, filters and visualizations: Crafting the story

   To convey your insights effectively on the Panaseer platform, tailor your Dashboard's breakdowns, filters and visualizations. Consider your audience, whether they are executives, team members or stakeholders, and decide on an approach that best suits their needs. Panaseer offers a range of visualizations to cater to different data analysis requirements.

Example