Finding the right metrics for your analytics dashboard

In today's data-driven business landscape, companies heavily rely on data analytics to steer their decision-making processes. Building an efficient data analytics system entails more than just assembling charts and graphs. It necessitates a careful selection of metrics that actively aid users in solving problems and achieving business goals. This article outlines a three-step process to assist you in pinpointing the crucial business metrics that truly matter.

1. Define Your Goals and Objectives

To embark on a successful analytics journey, you must first establish clear and specific business goals. These goals serve as your guiding star, forming a robust foundation for selecting the appropriate metrics that align with your strategic objectives. Failure to achieve this alignment can leave users adrift, making decisions that don't contribute to the overarching mission.

For example, consider the objective of "Increasing recurring revenue for the business." This objective provides a precise target to focus your efforts and resources towards a unified direction.

2. Identify Performance Indicators (Determining What)

Once you've solidified your goals, the next step is to pinpoint the key performance indicators (KPIs) that enable you to gauge your progress toward these goals. These indicators serve as your navigation tools, offering insights into your progress in achieving your objectives.

For instance, if your business goal is to "increase recurring revenue," you should monitor metrics like overall revenue growth trends, revenue growth from existing customers, and the rate at which you acquire new customers. These metrics offer a comprehensive view of your progress toward your revenue-related objective.

3. Implement Explanatory Metrics (Uncovering Why)

While performance indicators are vital for tracking progress and understanding what's working or not, they often fall short in explaining why something isn't working or how to rectify it. This is where explanatory metrics come into play. They delve deeper into the underlying causes and provide guidance on making improvements.

For instance, if you notice a decline in revenue from existing customers, you can gain insights by examining explanatory metrics such as customer churn rate, the number of customer-reported defects, product feature utilization rates, or the count of outstanding support tickets. Analyzing these metrics uncovers the primary reasons behind the revenue decrease and provides actionable insights for corrective measures.

4. Suggest Prescriptive Actions (Addressing How)

In addition to using performance indicators and explanatory metrics to tackle new challenges, there's a powerful strategy for recurring issues characterized by predictable patterns and known solutions. By implementing a rules engine that leverages these performance indicators and reasoning metrics, you can automate the prescription of specific actions. This not only enhances the actionable nature of problem-solving but also standardizes processes, making it a valuable resource for newcomers and facilitating efficient decision-making and problem resolution.

In conclusion, constructing an effective analytics dashboard begins with setting clear goals and aligning them with relevant metrics. These metrics are essential for identifying problem areas and making informed decisions for effective corrective actions. By following the above guidelines, you can ensure that your analytics efforts are not only data-centric but also action-oriented, ultimately driving your organization's growth and prosperity.