Build only the dashboards you need – overcome the 7 biggest problems first

The difference between a bad (ineffective) and good (effective) dashboard

Before diving into the main challenges, let’s first distinguish between ‘bad’ and ‘good’ dashboards.

Of course, we understand that in the early stages of Business Intelligence and dashboarding, you have to start somewhere. Often, this means beginning with the data and uncovering various insights. This is a valuable process because it showcases the potential of dashboards to users. But during this phase, it’s important to transition to smarter dashboards as quickly as possible. Below are some key challenges and solutions to help make that transition smooth and effective.

Problem #1: Lots of accountability but little direction

Organizations today are overwhelmed by the sheer volume of detailed information they must provide to demonstrate accountability. In the process, they often lose sight of how to effectively steer their operations, with dashboards and controls becoming cluttered by accountability data. As a result, they rely on external or top-down interventions, placing their fate in the hands of auditors and regulators rather than taking control themselves. For example, banks must comply with thousands of data submission requirements to regulators like the Federal Reserve and the Office of the Comptroller of the Currency (OCC), with new requirements added every year. Similarly, healthcare organizations must report hundreds of quality indicators that are costly to produce and offer little internal value.

Accountability, as it currently operates, is an outdated, rigid system—a relic from another era. In today’s environment, organizations need energy, commitment, inspired leadership, and sharp insight, not outdated practices that hinder progress. Moving away from hierarchical accountability and siloed reporting is essential. Reporting for the sake of reporting serves no purpose—after all, who’s actually reading all those reports?

Problem #3: Lack of standards and targets

Without clear standards and targets for your KPIs, managing performance effectively becomes impossible. Establishing, monitoring, and adjusting these benchmarks is essential for successful performance management and data-driven work. Without targets, discussions about performance with your team become meaningless and unproductive—just empty talk. You might try to hold yourself accountable, but without clear goals, it’s like trying to chase two rabbits—you’ll catch neither. This is the Achilles’ heel of KPIs and dashboarding.

Before building a dashboard, it’s critical to define target values for your KPIs. Failing to do so often leads to a flood of additional requests for more dashboards and insights—distractions that shift attention from what really matters.

Many managers tend to introduce new ideas or innovations when problems arise, but they often avoid addressing the underlying issues. However, continuous improvement—addressing root causes—is itself a form of innovation. To set meaningful standards and targets, you need to determine what a good benchmark looks like. Data analysis is the first step, as it reveals current performance. But avoid the trap of immediately building new dashboards; instead, focus on setting the right targets to guide your efforts effectively.

Problem #5: Decisions stay out of focus

When developing a dashboard, it’s common to ask prospective users, “What do you want to see?” or “What are you aiming for?” However, these questions assume that the user can clearly articulate what they need and, more importantly, how they will act on the information provided. This approach often results in an excessive number of dashboards, many of which offer little real value. To avoid this, it’s crucial to ask deeper questions, such as:

• Why do you need this information?
• What actions will you take based on this data?
• What decisions will improve as a result?

By shifting the focus toward decision-making and process improvement, you naturally create fewer but more impactful dashboards. This approach ensures that dashboards contribute directly to better business outcomes and establishes the right tone for data-driven work. A significant underlying issue lies in the composition of many data teams, which often consist predominantly of technical roles—such as dashboard developers, data engineers, and data scientists. While these experts are essential, they alone cannot bridge the gap between data and effective decision-making. To create dashboards that lead to better decisions, organizations need senior business analysts and, in some cases, experienced business consultants who understand performance management, BI, and data-driven work. Ultimately, the key is to focus on well-defined use cases and ensure that the right subject-matter experts are involved in their development.

Problem #7: Artificial Intelligence and Data Analytics are overlooked

The foundation of success in BI, data-driven work, and dashboarding lies in data analysis, as highlighted in our blog ‘Without data analysis, BI is pointless‘. Dashboarding is often mistaken for data-driven work. However, data-driven work simply isn’t possible without thorough data analysis. How can you determine the right actions to improve a KPI if you don’t uncover the root cause behind the KPI’s performance? Only by analyzing the underlying data can you make informed decisions to drive meaningful improvements. This is why investing in data analysis skills is essential.

With the rise of Artificial Intelligence, which increasingly automates data analysis, it’s equally important to explore how AI can be applied in your organization. By using AI effectively, you can reduce the need for manual dashboards. With AI, a single algorithm can eliminate the need for 100 reports or dashboards, providing insights more efficiently and automatically. Focusing on AI and data analysis not only enhances your organization’s decision-making capacity but also ensures you build only the dashboards that are truly necessary.