Data with Purpose: 3 Principles for Passing the 'So What' Test
The 'So What' test in analytics assesses the significance of data insights by examining their real-world impact on the business. It serves as a checkpoint to challenge analysts to delve deeper than surface-level observations and provide actionable insights. Let's delve into three guiding principles to effectively get you to the 'So What'.
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Treat your stakeholders as you would your most valued customers. Understand their needs, wants (targets), and pain points, integrating these insights into your analysis/visualization strategy. This approach empowers you to tailor visualizations that truly resonate with your stakeholders, ensuring that the insights you present are clear, relevant, and actionable. And remember, this is an iterative and collaborative process; ensure you follow up with your audience for feedback to continually refine and optimize your analytics and visualizations.
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2. Treat KPIs like 'aha moments'
Your data and visualizations should weave a compelling narrative, guiding your audience towards uncovering those 'aha moments'.
By laying a solid foundation; providing a clear framework and methodology you'll establish credibility and a shared understanding.
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And, by using storytelling and guiding your audience through the journey that led to your results, other will do the same to find meaningful aha moments.
This is the sweet spot for effective data presentation.
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3. Take the Marie Kondo approach
Marie Kondo revolutionized living spaces with a simple approach to decluttering; adopt a similar approach to your visualizations. Simplify complex data and strip away unnecessary elements that detract from the core message.
Embrace the ethos of clean design principles, leveraging color strategically and opting for intuitive layouts. Remember, the ultimate goal is not merely to present data but to facilitate understanding and informed decision-making.
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Lastly, BE BOLD. You've spent hours, days, in some cases weeks/months, uncovering and building your insights and visualizations; be bold and champion your data. You won't always have a positive story to share with your analysis, but it's one that needs telling.