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Build Strategic Dashboards to Drive Business Growth
From now on, you should view a dashboard as a strategic asset, not just a reporting tool that simply summarises past activities.
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Why a well-designed dashboard is essential
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When built on solid foundations, a well-designed dashboard becomes a powerful driver of business strategy. Specifically, it can:
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- Guide you where to focus next
- Flag opportunities and emerging risks
- Deliver actionable insights that drive growth and shape the future of your business.
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There are numerous dashboard tool providers and data consultancies that focus primarily on delivering slick, visually appealing dashboards. While aesthetics are certainly important, the true value of a dashboard as a strategic asset goes far beyond its appearance.​
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Key practices Datagator Solutions employ for building effective dashboards
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1. Thorough planning
Thorough planning is crucial to building a dashboard that truly serves your business. Investing time upfront ensures it is reliable, scalable, and aligned with your specific goals. This process involves:
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- Understanding business objectives
- Conducting staff interviews
- Defining relevant KPIs
- Performing a data audit
- Creating wireframes
It can be tempting to use an off-the-shelf dashboard template which is designed for your industry, however your unique business model should drive KPI selection. For example, North Star metrics can work well for product-led companies, but diversified businesses with multiple products will require a broader range of KPIs to accurately capture their performance.
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​2. Unified, clean data infrastructure
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Once your data is properly connected together and cleaned, it becomes a valuable resource that everyone, not just data analysts, can tap into. Connected and clean data allows teams to easily drill down into metrics, analysing the 'whys' behind performance trends. Additionally, connected data streamlines any automation you do, saving valuable hours, or even days of manual reporting.
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3. Unlock deeper insights with an Analytics Platform​
Dashboards are not appropriate places for deeper analysis.
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To truly understand the 'whys' behind your data, you’ll need to get a bit messy. This might involve creating new visualisations, adjusting metrics and applying multiple filters to uncover insights. Attempting to do this within a dashboard would quickly become chaotic, making the interface cluttered and far less intuitive to navigate. That’s why you need an Analytics Platform - a 'playground' where users can dig deeper into the data, experiment with different views, and perform more advanced analysis.
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4. Advanced analytics techniques
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There’s so much more you can extract from your data beyond basic metrics like 'users' and 'bounce rate’. Advanced techniques deliver metrics on your dashboard that unlock deeper insights, empowering you to make more informed decisions:​​​​​​​​​​​​
Using some methods called 'Feature Importances' and 'SHAP Values', we can help you understand the key drivers behind performance metrics. This highlights which factors matter most, allowing you to focus on areas for improvement.
By analysing patterns among users who have churned (or 'dropped-off'), you can
identify users most at risk of churning in the future. This allows you to take proactive measures, like offering discounts or additional support to retain those customers.
Momentum mapping, a unique method developed by Datagator Solutions, provides businesses with a clearer understanding of how products, content, or services perform over time. By tracking momentum, companies can anticipate demand, adjust inventory, and optimise marketing efforts, focusing on promoting items with long-term value while avoiding overinvestment in short-term trends.
Segmentation allows you to break down data by specific product lines, user demographics or behaviours. This offers a clearer picture of what’s driving value.
We use something called 'Weighted Composite Scoring' (AKA Product Value Scoring) to combine multiple metrics into a single, insightful score that reflects overall performance. Instead of relying on just one metric like 'revenue' or 'add to basket,' this method considers all key metrics, giving a fairer and more balanced ranking of products, ensuring no single metric skews the results.
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What-if scenario analysis, also known as 'Optimisation Models', can help solve complex problems, such as inventory management or resource allocation. Dashboards can display optimal solutions for minimising costs or maximising efficiency based on multiple constraints and business rules.
5. One size does not fit all
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Aside from executive dashboards that focus on the top-level KPIS, unfortunately dashboards are not a one-size-fits-all solution.
Trying to creating one or two dashboards to meet everyone’s needs may sound appealing but it doesn’t work in practice. Each department or even each individual within a department has different goals and responsibilities. Trying to cram all those needs into one dashboard leads to cluttered, unfocused views that end up serving no one.
Bespoke dashboards should be tailored to each department, and eventually, to individual users. Over time, with guidance, users should feel confident in creating and evolving their own dashboards, allowing them to not only monitor key metrics but also perform top-level investigatory analysis that answers both the ‘whats’ and the ‘whys.’​
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6. Evolve, don't bloat
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Just as a business needs to update its strategy and goals to changing priorities, dashboards need to evolve to reflect this.
Sticking with a static dashboard is like trying to navigate with an outdated map - it doesn’t get you where you need to go. Instead, regularly refining and adapting dashboards allows businesses to stay agile and responsive to changing conditions.
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7. Data literacy training
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Last but certainly not least, every user in your business should have the confidence to self-serve their own data. Empowering users to independently access and analyse data exponentially accelerates decision-making across the organisation. It also reduces the bottlenecks associated with relying solely on data analysts.
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