Informed decision-making ultimately leads to greater access, opportunities, and technological advancement. Very often, the most important factor in determining success comes down to who engages in factual and informed decision-making and who follows hunches and suppositions. But what is one strategic business intelligence (BI) mechanism that is absolutely necessary in the digital age? A BI dashboard. How can you create one? Thanks to specific BI dashboard best practices.
Such dashboards can have a lot of different features, mainly having a customizable interface, a certain level of interactivity as well as the possibility to pull data in real-time from multiple sources. By enabling the user to visualize otherwise complex and heavy raw data, they simplify the data processing for our brain and give readers an at-a-glance overview of the past, current, and future performance.
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BI dashboards organize data cohesively while alleviating any potential clutter that can arise when working with complex sets of information while applying advanced intelligence tools to your various strategies. Using highly visual representations and tools, you can produce graphs, charts, and other powerful visualization instruments that empower you to interpret the data and transform it into actionable insights that will benefit your company in many ways. To outline the unrivaled value of creating such a dashboard, here are the primary benefits of utilizing them:
As mentioned, these best practices refer to methods and techniques made and recommended by our expertise from working on hundreds of BI projects with customers around the world to get the maximum value out of your dashboards and reports. These 12 key BI considerations hold all of the facts you need to hit the ground running with your newfound data-powered organizational strategies, including practical advice on business intelligence dashboard design.
Before selecting your tool, it is important to know what types of dashboards are available. Once you understand each type, you can make an informed decision regarding the purpose and implementation of your dashboard. Remember, informed decision-making for maximum ROI is the whole point!
Analytical: The analytical type is engineered to provide detailed analyses pertaining to trends (the what, the why, the how). Analytical solutions place a particular emphasis on measuring data variables in relation to time (week, month, year, etc.). An example would be to conduct an analysis of supply chain management, together with product sales, over a designated period of time in order to determine what trends, mutually dependent factors, and potential strategic consequences exist (if any). A great analogy for analytical dashboards would be that of a general medical practitioner. He or she may not be an expert in one specific medical field, but they can effectively monitor the overall health of the body by comparing current symptoms to what would be an ideal state of health. This is exactly the role of analytical dashboards. As they take into account a multitude of different measurables for the purposes of aligning goals with performance, they have a tendency to be complex and highly focused.
It is a major fallacy to assume that what you think is a more visually appealing dashboard will communicate more effectively with your audience. Communication is a science, and BI dashboard design should reflect quick, concise, and clear fact-based communications. One of the unfortunate tendencies of data professionals in the digital age is the self-defeating habit of overburdening audiences with clutter. This is why you should follow the 5-second rule, which states that your dashboard should provide the relevant information in about five seconds.
Consistent Alignment: Ideal data alignment for dashboarding purposes is likely to be determined on a case-by-case basis. A good default rule is to have your most informative data positioned in the upper left (the upper left corner of the page is likely a leading candidate for informative text). Knowing what to place and where is as important as knowing what not to place. Therefore, a second general rule is to avoid ALL temptation to place diagonal elements and fill patterns. Diagonal data elements, especially those linear in nature, add little benefit while significantly reducing alignment efficiency.
In order to make the analysis experience as efficient and intuitive as possible, you need to make sure that your BI dashboards are not static. When building them, a best practice is to always have interactivity in mind. This can be achieved with the help of various filters that make your data easier to navigate. Some common interactivity filters that you can apply include:
In order to properly analyze the role of data within a specific dashboard, everyone from the CEO to a first-year product salesperson needs to understand the notion of context. Data analyses and visual representations lacking context will be limited in their utility and ROI. It is normal for data points to generate more questions than answers. However, observers should be fully informed, nonetheless. For example, if a dashboard is monitoring product marketing effectiveness, and one of the data points included is total sales, this data point will be useless without knowing the measurement time frame. Is it this week? This month? This quarter? This fiscal year? Absent time-specific context, it is next to impossible to know the intended significance of the data. Also, answer yourself if you additionally need to develop KPI scorecards to update information on a periodical basis only.
Are your audience members internal stakeholders, potential investors, or existing company partners? Or are your internal users working on a specific campaign or part of a focused department? If so, what data access will they need? All of this is integral to shaping your efforts to succeed. Sit down collaboratively and consider all of these questions before setting up your dashboard.
The design is consistent with several shades of blue that do not clash with each other, while the graphs and figures displayed are not cluttered and follow a clear visual order so every marketing KPI is comprehensible. The message of that dashboard is understood in a glance and the alignment and white space give a rest to the eyes, who are not struggling in getting to the point.
One of the best business intelligence dashboards for profitability, our sales dashboard below is focused on helping you hit sales targets and foster growth on a consistent basis, boosting your KPI monitoring processes and, ultimately, bottom line. Concentrated on high-level metrics, this example will enable you to cultivate a data-driven environment, crucial in generating more revenue and, ultimately, increasing profits.
One of the best BI dashboard examples for those that need a general financial overview of a company or department, our financial KPI example serves up a wealth of metrics based on improving processes and eliminating processing inefficiencies.
This financial dashboard sample breaks down a number of financial processes into digestible segments. You can gain a deep working insight into your working capital, cash conversion cycle, and vendor payment error rate. This mix of invaluable insights offers all of the key ingredients for developing seamless processes that help to save on unnecessary costs while significantly boosting productivity.
Just like our logistics example, a manufacturing factory can also highly benefit from an interactive business intelligence dashboard. When dealing with production and machinery, unexpected issues are highly likely to appear. Putting in place analytical practices to stay ahead of these issues and tackle them before they become bigger can significantly increase operational efficiency. Additionally, extracting the maximum potential out of your manufacturing data can help you spot trends and patterns to optimize several production processes.
Business intelligence and dashboards are extremely cost-effective by minimizing the potential for human error and streamlining the decision-making processes dependent on data interpretation. To help you on your way, you might want to consider datapine as your BI provider. Established in Germany with a long tradition of highest security layers in the world, datapine is continuously disrupting the EU and markets across the world, no matter if you need us for your management or data science efforts.
* You have to share the dashboard with at least one person/group for it to become visible - share it with yourself for example. If this is not done, tiles are not visible - the dashboard can still be embedded, but not separate tiles.
Power BI is a business analytics service that gives you a single view of your data, with the ability to monitor the health of your business using live dashboards, create rich interactive reports and access your data on the go, from your mobile devices.
The new dashboard would not necessarily help grid operators prepare for catastrophic black swan events that might happen only once in 100 years. Instead, Bienstock and his colleagues hope to apply some lessons from financial modeling to measure and manage risk associated with more common events that could strain the capabilities of the U.S. regional power grids managed by independent system operators (ISOs). The team plans to build and test an alpha version of the dashboard within two years, before demonstrating the dashboard for ISOs and electric utilities in the third year of the project.
In the spirit of customer-obsession, teams within AWS have also built intelligence dashboards, such as Cost Intelligence Dashboard available from Well Architected Labs and CUDOS framework based on AWS Serverless technologies. These dashboards allow you to visualize trends across AWS accounts and AWS Service Categories. You can find step-by-step instructions to automatically ingest the CUR data into Amazon Athena and provision pre-built Amazon QuickSight dashboards, in either Cost Intelligence Dashboard, or CUDOs framework. 2ff7e9595c
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