6 Things to Consider for Building Analytics Dashboards

Andy Sawyer is a data strategy leader and advisor, who is currently leading data teams at Easy Agile.

Let’s be honest, there’s an undeniable allure to sleek, colourful dashboards that promise to distil complex information into easily digestible visuals. As managers of analytics teams, you’ve likely encountered the pressure to produce these eye-catching displays. But are we, as an industry, becoming too enamoured with the sizzle and forgetting about the steak? This article aims to challenge the prevailing dashboard-centric mindset and refocus our attention on the true value of analytics.

The Dashboard Dilemma

Dashboards, when used appropriately, can be powerful tools for communicating data and monitoring key metrics. They offer a quick snapshot of business performance and can make complex data more accessible to non-technical stakeholders. However, I am concerned that many companies are overinvesting in dashboard development at the expense of deeper, more impactful analytics work. Indeed, while working in consulting, we were engaged more often than not to produce a set of dashboards. Not to perform analysis and assist the business in improving efficiencies.

Unpacking the Roles: Insights Analyst vs. Dashboard Developer

To understand this issue better, let’s first distinguish between two crucial roles in the data world:

The Insights Analyst
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• Responsibilities: Insights Analysts are the detectives of the data world. They dive deep into datasets, using statistical methods, machine learning models, and other analytical techniques to uncover hidden patterns, trends, and correlations.
• Skills: Proficiency in data manipulation, statistical analysis, and programming languages like Python or R. More importantly, insights analysts possess critical thinking skills and business acumen to translate data findings into strategic recommendations.
• Output: Actionable insights that drive business decisions and strategy.

The Dashboard Developer
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• Responsibilities: Dashboard developers are the artists of data visualisation. They design and build interfaces that present key metrics and trends in an easily digestible format.
• Skills: Expertise in visualisation tools like Tableau or Power BI, a keen eye for design, and the ability to structure data for optimal presentation.
• Output: Visual representations of data that facilitate quick understanding and monitoring of KPIs.

While both roles are valuable, the danger lies in conflating them or overemphasising one at the expense of the other.

The Illusion of Insight: When Dashboards Fall Short

It’s easy to fall into the trap of equating a beautiful dashboard with valuable insights. However, dashboards, in themselves, don’t generate new knowledge or drive action. They’re tools for presentation, not analysis.

Consider these potential pitfalls of an over-reliance on dashboards:

1. Superficial Understanding: Dashboards often present aggregated data, which can mask underlying complexities or issues. This can lead to oversimplified interpretations and misguided decisions.
2. Analysis Paralysis: An abundance of dashboards can overwhelm users with information, making it difficult to focus on what truly matters.
3. False Sense of Data-Driven Culture: Organisations might believe they’re data-driven simply because they have dashboards, neglecting the crucial step of acting on insights.
4. Resource Misallocation: Excessive focus on dashboard development can divert time and talent away from deep analytical work that could uncover game-changing insights.

The Right Time and Place for Dashboards

This isn’t to say that dashboards are without value. When used judiciously, they can be powerful tools. Here are two scenarios where in my opinion dashboards truly shine:

1. Tracking North Star Metrics at the Executive Level: Long-lived dashboards that monitor critical KPIs can help leadership keep a pulse on overall business health and progress towards strategic goals.
2. Monitoring Project Performance: Short-term dashboards can be invaluable for tracking the impact of specific initiatives or experiments. Once the project concludes, these dashboards can be retired.

The key is to view dashboards as a means to an end, not the end itself. They should support and complement deeper analytical work, not replace it.

Case Study: A Data-Driven Approach to Marketing Optimization

Let’s examine a real-world scenario that illustrates the effective use of dashboards in conjunction with deep analytics.

A few years ago, I worked for a healthcare company. They specialised in cardiac care, and operated a network of practice centres that received patient referrals from General Practitioners (GPs) at various clinics around the country. Our marketing team had a hunch that they might be experiencing marketing cannibalism within the referral network. Specifically, they hypothesised that when GPs from the same clinic referred patients to different HeartCare practice centres, it led to inefficient marketing efforts as multiple practice centres would compete for future referrals from the same group of GPs.

To investigate and address this issue, the analytics team developed a dashboard with a clear, specific purpose:

1. Initially, to visualise and quantify the extent of potential marketing cannibalism.
2. Subsequently, to track changes in referral patterns over the course of a defined project aimed at optimising marketing efforts.

It was a short-term dashboard, designed to show:

• Clinics with GPs referring to multiple HeartCare practice centers
• The volume of referrals from each GP and their destinations
• The catchment overlap in marketing efforts directed at these clinics

This dashboard served as a powerful tool for several reasons:

1. Clear Purpose: It was created to address a specific business question, not just to display general metrics.
2. Actionable Insights: The visualisation made it easy for the marketing team to identify areas of overlap and inefficiency.
3. Project Tracking: As a living document, it allowed the team to monitor the impact of their interventions in near real-time.

However, the dashboard itself was just the starting point. The real value came from the deep analytical work that supported it:

1. Data Analysis: The analytics team dug into the referral data, conducting statistical analyses to confirm the hypothesis of marketing cannibalism and quantify its impact.
2. Root Cause Identification: Through discussions with the practice managers and analysis of geographical and demographic data, they uncovered the reasons behind split referrals from single clinics.
3. Strategy Development: Based on these insights, the team developed a targeted strategy to optimise marketing efforts, including:

• Assigning new, State-based marketing managers to view marketing more holistically across the business
• Developing a coordination system for marketing outreach to prevent overlap

The dashboard played a crucial role throughout this process, not just in identifying the initial problem, but in tracking the effectiveness of these interventions over time. Marketing teams could see in near real-time how their adjusted strategies were impacting referral patterns.

The result? Over the course of the project, the HeartCare business was able to significantly reduce marketing cannibalism. This led to more efficient marketing spend, improved relationships with referring clinics, and ultimately, better patient care through more streamlined referral processes.

This case study showcases the ideal use of dashboards in analytics:

1. It was created with a specific, strategic purpose in mind.
2. It visualised complex data relationships that might have been missed in traditional reports.
3. It served as a launching point for deeper analysis, not an end in itself.
4. It was used to track the impact of data-driven interventions over time.
5. Most importantly, it led to concrete, measurable business improvements.

By balancing effective dashboard usage with in-depth analytics, the business was able to turn data into actionable insights and tangible business results.

Striking the Right Balance: Analytics-Driven Dashboard Strategy

So, how can we ensure that dashboards enhance rather than hinder our analytical efforts? Here are my six tips:

1. Start with the Why: Before creating a dashboard, clearly define its purpose and the decisions it will inform. If it’s not driving action, it might not be necessary.
2. Embrace Iteration: Treat dashboards as living documents. Regularly review and refine them based on user feedback and changing business needs.
3. Promote Data Literacy: Invest in training to ensure that dashboard users understand how to interpret the data and, more importantly, when to dig deeper.
4. Integrate with Deep Analytics: Use dashboards as starting points for investigation, not endpoints. Encourage users to ask “why” when they see interesting trends.
5. Prioritise Action: Design dashboards that not only display data but also suggest next steps or areas for further analysis.
6. Measure Dashboard Effectiveness: Regularly assess whether your dashboards are driving decisions and adding value. Don’t be afraid to retire dashboards that have outlived their usefulness.

The Future of Analytics: Beyond the Dashboard

Looking forward, the most successful companies will be those that view dashboards as just one tool in a comprehensive analytics toolkit. Here are some trends to watch:

• Augmented Analytics: AI-powered systems that not only visualise data but also automatically identify trends, anomalies, and potential areas for investigation.
• Storytelling with Data: Moving beyond static dashboards to interactive, narrative-driven presentations of insights.
• Democratized Data Science: Tools that empower business users to perform deeper analyses without relying solely on data scientists.

Conclusion: Realigning Our Focus

It’s easy to be seduced by the allure of flashy dashboards. However, as managers of analytics teams, it’s crucial to remember that the true value of analytics lies not in the presentation of data, but in the insights we derive and the actions we take.

By all means, leverage dashboards for their strengths — monitoring KPIs, communicating high-level trends, and alerting us to areas that need attention. But don’t let them become a crutch or a substitute for rigorous analysis.

Encourage your teams to look beyond the charts and graphs. Foster a culture of curiosity where asking “why” is more important than admiring “what.” Invest in developing the skills and tools needed for deep, impactful analytics work.

Remember, a beautiful dashboard might impress in the short term, but it’s the actionable insights and data-driven strategies that will drive long-term success. Let’s ensure we’re not just seeing our data, but truly understanding and leveraging it to achieve our business goals.

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