Ever detected an anomaly in your operations metrics but couldn’t connect it to any root cause? Or maybe the data was too vast for you to comb through?
A business intelligence dashboard closes this gap by organizing your data into a format you can easily retrieve, analyze, and interpret to support your decision-making.
This guide covers how a business intelligence dashboard works, including how to set up one, and the best practices to consider.
What Is a Business Intelligence Dashboard?
A business intelligence (BI) dashboard refers to an interface that helps you pull, analyze, and visualize data from multiple data sources, such as CRM systems, ERP platforms, marketing tools, financial systems, and data warehouses, as interactive charts, graphs, tables, and key performance indicators (KPIs). BI dashboards came as a replacement for spreadsheets, databases, or departmental reports, which required manual analysis and interpretation by data teams before being published as reports to support decision-making.
With BI dashboards, decision-makers can use filters to find the KPIs or metrics they need and query the platforms directly for additional context. Additionally, you can configure your BI dashboard to refresh in real-time or at scheduled intervals, depending on your business needs.
There are about 5 types of BI dashboards, including:
- Analytical BI dashboards
- Tactical BI dashboards
- Operational BI dashboards
- Strategic BI dashboards
- Self-service BI dashboards
We’ll discuss each dashboard type in detail in later sections, including how they support decision-making.
Key Components of a BI Dashboard
A good BI dashboard helps turn data into actionable insights that support decision-making. To achieve this, your BI dashboard should include the following core elements:
- Data Visualization: A BI dashboard should display data as charts (bar, line, pie), graphs, gauges, and heatmaps, to help you identify trends and spot outliers quickly.
- Customizable Views: The best BI dashboards have interactive filters that let you ‘hide’ the visualizations you don’t need so you can focus on the most important ones.
- Alerts and Notifications: BI dashboards should let you set automated triggers that send alerts when metrics exceed specific thresholds. An example would be BI dashboard alerts when warehouse inventory levels fall below two weeks’ worth of stock.
- Data Source Connections: BI dashboards should support integrations with your data sources, including CRM, ERP, and IoT systems. This includes having a built-in semantic layer, allowing you to run analytics across multiple data sources simultaneously.
Types of Business Intelligence Dashboards
BI dashboards come in different formats depending on the decisions they support. For example, a dashboard built for a production line manager to track real-time output is very different from one built for a CFO to review quarterly trends. Understanding the different types of BI dashboards helps you pick the best-fit option for your business objectives.
Let’s outline the main types of BI dashboards:
- Operational BI Dashboards: As the name suggests, these dashboards help you track near-real-time metrics relating to your day-to-day business operations, such as production output, order fulfillment, and system output. As such, operational BI dashboards are best suited for users on the production side, including machine operators and supervisors.
- Tactical BI Dashboards: These dashboards help track short-term goals, such as weekly sales targets and team productivity. They help bridge the gap between operational and strategic BI dashboards by helping department managers respond to anomalies flagged on operational BI dashboards before they affect the business’s long-term goals.
- Strategic BI Dashboards: These dashboards focus on high-level KPIs tied to the company’s long-term business goals, including revenue growth, market share, and profitability trends. As such, they are built for executive and top-level managers to support their strategic decision-making without having them drill down to day-to-day operational performance.
- Analytical BI Dashboards: These dashboards complement operational and tactical platforms by helping teams conduct deeper investigations into why some metrics have anomalies. For example, the team may test hypotheses or explore patterns in historical data to determine when issues started.
- Self-Service BI Dashboards: These dashboards allow non-technical users to customize views to their decision-support needs without relying on a data analyst. This helps transform the dashboard from a static display into a living artifact, bridging the gap between having data and being able to ask questions.
5 Business Intelligence Dashboard Examples by Use Case
Some companies believe BI dashboards only benefit executive-level decision makers. However, even supervisors and floor operators can benefit from integrating BI dashboards into their daily operations. Additionally, it is essential to remember that each department usually has a different viewpoint of the same underlying data. BI addresses this concern by allowing users to customize their dashboards to their specific decision-support needs.
Let’s discuss how different departments utilize BI dashboards:
Sales Performance Dashboard
A sales performance dashboard gives the sales team and leaders visibility into metrics like revenue, win rates, average deal size, and quota attainment. With legacy platforms, sales leaders had to wait for weekly CRM exports to see declining sales and then start following up on potential causes, which could take days or weeks.
Sales BI dashboards let leaders see real-time inventory movement across stages and forecast revenue with more confidence. Additionally, they can drill down from a team-level view to individual rep or deal data to identify and address pressure points or members that are causing bottlenecks in the sales pipeline.
Marketing Attribution Dashboard
Attribution is among the most challenging tasks for marketing teams required to justify their budgets or ROI. As such, a BI dashboard helps the marketing team connect marketing spend to the revenue or pipeline it actually generates or the advertising channels, such as paid search, social, email, or events, eliminating guesswork.
Consequently, marketing teams can identify specific channels that generate the most revenue for the company and allocate resources proportionally.
Finance and FP&A Dashboard
Finance teams widely use BI dashboards to monitor cash flow, budget-to-actual variance, gross margin, burn rate, and revenue forecasts. One standout reason is that BI dashboards apply a semantic layer that uses the same definitions for metrics like revenue and churn, ensuring consistent outputs across departments.
Additionally, finance teams can use BI dashboards to model different scenarios and test hypotheses to help them refine the budget forecasts before submitting them to the executive.
Product Analytics Dashboard
This dashboard helps development teams learn how clients utilize their products or specific features, including engagement, retention, and funnel drop-off. Consequently, teams can identify and address friction points or prioritize high-engagement features to maximize conversions.
Additionally, teams can connect product usage data to the CRM or billing system, helping them connect specific features to revenue expansion or churn.
Supply Chain and Operations Dashboard
A BI dashboard connects to multiple data sources, such as ERP, MES, and supplier systems, allowing the supply chain team to monitor inventory levels, supplier performance, lead times, equipment utilization, and production throughput in real-time.
By consolidating the data, the team can quickly identify and address systemic supply chain bottlenecks or anticipate and mitigate supply disruptions. This helps organizations strengthen supplier relationships and achieve high order fulfillment rates, building an edge over their competitors.
How to Create a Business Intelligence Dashboard in 7 Steps
Your BI dashboard should offer more than just displaying performance charts. It should help you connect the dots about variations in your operational efficiency and suggest data-backed process improvements.
Here’s a step-by-step guide for building a BI intelligence dashboard for your business:
1. Define Business Objectives and KPIs
Start by outlining the key business decisions that you want the BI dashboard to support, including the relevant KPIs to help you track progress.
However, avoid the temptation to track all business goals, as this could cloud your BI dashboard, causing you to miss the most essential KPIs because of ‘noise.’ As such, limit the dashboard to your five most important business objectives/KPIs.
2. Select a BI Dashboard Tool
Explore the available BI dashboard software in the market and pick the best-fit option depending on your existing data infrastructure and target end user.
For example, if you don’t have a data team, consider self-service BI tools, as they allow users to query the system using natural language.
3. Connect to the Data Layer
Integrate the BI dashboard with your data sources. Create a unified data layer that sits on top of your warehouse as opposed to pulling from standalone sources. This helps enforce data governance and implement a semantic layer more effectively, ensuring consistent output across departments.
Lastly, ensure the data layer refresh frequency matches the required decision speed, i.e., syncs in real time if you need to make near-real-time interventions to optimize operations.
4. Customize the Dashboard
Design your BI dashboard layer to match the target users and reflect the objectives you outlined in Step 1. This includes positioning the most critical KPIs at the top or center, depending on your BI dashboard layout, with supporting data in the background for drill-downs.
Additionally, select your preferred visualization tools, such as line charts or bar charts, depending on whether you want to monitor trends or compare KPIs over periods.
5. Add Interactive Filters
Create filters for variables such as date range, department, region, product line, or sales representative to help different users customize the dashboard to their needs without generating a separate dashboard. You could even configure the dashboard to allow users to filter the output using keywords to enhance drill-downs.
Self-service BI dashboard may also support citations, allowing users to see which query was run and which filters were applied, so they can modify the request to match their data needs.
6. Test and Validate
Verify that the data, calculations, and visualizations are consistent with your source system prior to rolling out the BI dashboard.
Additionally, you can implement a pilot phase with a small group of users and observe how they interact with the dashboard, including whether it is supporting their decisions or introducing more bottlenecks.
7. Deploy and Maintain
Train the target users before rolling out so they feel confident interacting with the BI dashboard. Additionally, establish a regular cadence for collecting user feedback to determine whether the BI dashboard is meeting their decision support needs or whether they are encountering usability challenges you can address through training.
It will also be important to review and improve the BI dashboard regularly to ensure it remains aligned to your goals and objectives as the business evolves.
As your business grows and its operations become more complex, your team will need more than a BI dashboard where they can only monitor trends. Your business context and priorities will evolve, causing your team to ask new questions that weren’t captured when building your dashboard.
At Zenlytic, we cater to this shift through Zoë’s self-learning capabilities, which help her improve her context over time. Additionally, our BI dashboard comes with a built-in Clarity Engine that combines SQL and a semantic model mechanism to provide ready-to-use answers and insights to support decision-making.
See how the Zenlytic BI self-service dashboard can transform your business’s data into trusted answers.
BI Dashboard Best Practices
Many businesses build their BI dashboards once and then never refine them, so they slowly drift out of sync with how their operations actually run. Instead, you should review your BI dashboard regularly to ensure it remains relevant to your business objectives and supports your decision-making.
Here’s how to keep your BI dashboard accurate and relevant:
- Set Clear Goals and KPIs: Define which decisions your BI dashboard should support and the metrics that matter. If you have multiple goals, prioritize the most important ones to keep your BI dashboard clean and easy to scan.
- Integrate Your Data: Build a unified data layer that sits on top of your warehouse so that your BI dashboard pulls information from a single connected source. Additionally, add a semantic layer to ensure metrics from sales, operations, finance, and other departments stay consistent across the organization.
- Link to Multiple Dashboards: Connect related dashboards to facilitate drill-down capabilities, allowing users to move back and forth between summary metrics and detailed root-cause analysis reports.
- Provide Context: Facilitate quick data interpretation by pairing metrics with targets, historical trends, or benchmarks, so viewers can quickly tell whether a figure is good, bad, or cause for alarm.
- Test and Iterate: Schedule regular reviews to revise the set goals and KPIs to ensure they remain aligned with your most important business objectives. Additionally, remove outdated metrics and reset your filters, so the BI dashboard reflects current priorities.
How to Choose the Right Business Dashboard Software
There are at least a dozen BI dashboard software in the market. As such, the BI software you choose significantly depends on your selection criteria, as this also determines whether team members adopt it organization-wide or stick to their legacy platforms.
Evaluate closely for the following factors when choosing a BI dashboard for your business:
- Check for Integration: Confirm that the BI dashboard integrates seamlessly with your unified data layer that sits on top of your ERP, CRM, and marketing platforms, without needing manual exports or regular reconnections.
- Confirm Ease of Use for Non-technical Users: Look for a BI dashboard that decision-makers can use and query independently, even without advanced SQL skills or rerouting questions to the data team.
- Ensure Semantic Layer Consistency: Go for a BI dashboard software that enforces a single, governed definition of core metrics, so that variables of numerical values carry the same meaning across the organization, whether viewed by sales, finance, or operations.
- Governance Controls: The BI dashboard should support role-based access and data residency requirements, especially if some of the connected data sources contain sensitive information and company secrets.
- Test for Scalability: Ensure the BI tool you pick can support a growing number of users or increasing data volumes without needing you to invest in more hardware or overhauling your information management system.
Frequently Asked Questions (FAQs)
This section answers common questions managers and departmental heads ask about building a business intelligence dashboard.
What Is the Difference Between a BI Dashboard and a Report?
A BI dashboard leverages interactive visualizations to provide near-real-time visibility into performance metrics, supporting and accelerating decision-making. On the other hand, a report is often a detailed static document that summarizes status metrics as of the time of generating it.
What Data Sources Can a BI Dashboard Connect To?
A BI dashboard can connect to multiple data sources, including CRM platforms, ERP systems, marketing tools, and operational systems like IoT sensors. The best BI dashboards use a centralized semantic layer, so businesses can analyze data from different sources simultaneously.
How Many KPIs Should a BI Dashboard Display?
There’s no limit to how many KPIs a BI dashboard should display, as the focus should be on the most important metrics and not the number. Most BI dashboards are customizable to a specific business objective and can display five to 10 KPIs at a time.
What Is a Semantic Layer in a BI Dashboard?
A semantic layer refers to a standardized way of defining business metrics, calculations, and relationships across multiple data sources. As such, all teams use the same formulas, ensuring the output is consistent.
Conclusion
A well-set-up BI dashboard supports your team’s decision-making, allowing them to act fast and with certainty. However, most legacy platforms can’t accommodate new questions from your team, meaning they have to reroute them to the data team.
We built Zenlytic to help teams move from spending time interpreting reports to trusted answers. Zoë, our AI-powered data analyst, combines Zenlytic’s Clarity Engine, artifacts, and self-learning capabilities to help teams investigate new questions and explore alternative solutions without sending additional SQL requests.
Ask Zoë a business question and receive a data-backed answer you can trust.