How do you create risk dashboards using software?

1 Choose a software tool

Choosing a software tool that meets your needs and preferences is the first step. There are many options available, ranging from general-purpose spreadsheet or presentation software to specialized risk management software and online dashboard platforms. Factors to consider include the complexity and size of your risk data and analysis, the level of customization and interactivity, the compatibility and integration with other tools and systems, the cost and availability of licenses and support, as well as the ease of use and learning curve.

2 Define your dashboard objectives

The next step is to define your dashboard objectives and scope. What are the main questions you want to answer with your dashboard? Who are your target audience and stakeholders? What are their information needs and expectations? How often and how will you update and share your dashboard? These questions will help you clarify the purpose, scope, and format of your dashboard, as well as the key performance indicators (KPIs) and metrics you will use to measure and display risk.

3 Design your dashboard layout

Designing a dashboard layout and structure is the third step. This involves deciding how to organize and arrange dashboard elements, such as charts, tables, graphs, maps, gauges, and icons. You should create a clear, concise, and consistent layout that follows logical and hierarchical structure to guide the eye from the most important to the least important information. Additionally, use a grid system to align and balance your elements and avoid clutter. Color, contrast, and white space can be used to highlight and differentiate your elements and data. Furthermore, use simple and appropriate visualizations that match your data type and message. Labels, legends, and annotations should be used to explain your elements and data. Last but not least, interactive features such as filters, sliders, drill-downs, and tooltips can enhance user engagement and exploration.

4 Build your dashboard data model

The fourth step is to build your dashboard data model and logic. This involves preparing and processing your risk data and connecting it to your dashboard elements. To ensure a robust, reliable, and scalable data model, you should use a consistent and standardized format and structure for your risk data, as well as a single source of truth to avoid duplication and inconsistency. Additionally, you should employ data validation and quality checks to guarantee accuracy and completeness. Furthermore, formulas, functions, and calculations can be used to transform and aggregate your data. You can also leverage data filters, parameters, and variables to control and customize your data display. Lastly, you should take advantage of data refresh and automation features to keep your data up to date.

5 Test and refine your dashboard

The final step is to test and refine your dashboard before deploying and sharing it. This involves checking and improving its functionality, performance, and usability. To create a user-friendly, error-free, and fast-loading dashboard, you should test it on different devices, browsers, and screen sizes to ensure compatibility and responsiveness. It’s also important to test the dashboard elements, data, and logic to ensure functionality and accuracy. Additionally, you should optimize loading time by reducing the size and complexity of your data and elements. Furthermore, it’s essential to test the dashboard user experience and feedback to improve clarity, relevance, and value. Lastly, you should check the dashboard security and access to ensure compliance with data protection and privacy policies.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?