Business intelligence means analyzing business data to extract insights that are helpful in decision-making. Since the rise of big data, organizations have been spending heavily on business intelligence tools. Resultantly, the global business intelligence software market is valued at $25.73 billion in 2023, and it will be $34.16 billion in 2028, growing at a CAGR of 5.83%.
But unfortunately, 60% of the investment in data analytics goes to waste because insights obtained were never used in decision-making. So, it becomes essential for organizations to learn business intelligence best practices. Best practices help organizations gain a competitive edge.
What is a BI dashboard, and why use one?
A BI dashboard is a tool that connects with various business data sources and enables users to create customized visualizations. Users perform BI reporting to extract insights from the data.
It displays all businesses’ key performance indicators in one place, which helps in decision-making. BI reporting is done for two main reasons:
1) Regular Reporting: Regular reporting has standardized insights. It provides insights such as daily sales volume.
2) Ad-hoc Reporting: Customized research is required if the business wants an answer to a particular business problem. The data analyst analyzes data to find answers to specific questions, such as Why did sales drop on the weekend?
It is essential to follow best practices because only 27% of executives believe that their BI investments were helpful in decision-making.
The roadmap for business intelligence best practices is as follows:
1. Understand the business requirements
Understanding the needs and expectations of key stakeholders is crucial in business intelligence reporting. Understanding business requirements involves the exploration of business processes.
It’s important to have a comprehensive meeting with key stakeholders to understand their BI requirements. Stakeholders turn to BI solutions to address particular pain points. Here, it becomes important to ask the following question:
What is our business problem, and what kind of BI reporting do we need for decision-making?
2. Define clear objectives
Once you have understood business requirements, the next step is clearly stating the business objectives. To derive actionable insights from the data, the objectives should be Specific, Measurable, Achievable, Relevant, and Time-bound.
For example, reducing BI reporting time by 30% by using BI tools. Or, the goal could be to increase sales by 20% by leveraging insights obtained from data. It is essential to collaborate with stakeholders to define objectives.
Unclear objectives can lead to BI projects going nowhere. Moreover, it is important for data analysts to stay in touch with stakeholders at each step.
3. Prioritize readability
The whole point of creating data visualization on reporting tools is to enhance readability. In this step, a data analyst needs to ask:
Who is my audience?
You can use complex visualizations and jargon if the audience consists of the data team, like data engineers or data scientists. However, when explaining insights to non-IT members of the business, such as key stakeholders, you must create easily understandable dashboards. Minimalistic visualizations that convey the most amount of information enhance readability and engagement.
Factors that enhance readability are as follows:
Using the appropriate color scheme
Adding title, axes name, and legends
Describing the insight obtained from the data.
Adding sections and sub-sections to the report
4. Identify the right data sources
Data is the heart and soul of any BI project. Identifying the data sources that overlap with the business objectives and stakeholders’ needs is a major BI reporting step.
For example, if the objective is to understand customer behavior, data sources such as CRM systems and social media posts will be helpful in this regard. Ensuring that the data literacy levels of the tech team are at par with business requirements is necessary.
After identifying the data sources, it is crucial to formulate a comprehensive data governance strategy to maintain its quality, access, and security measures.
5. Choose appropriate visualizations
Business intelligence best practices involve a comprehensive understanding of visualization types. To make appropriate visualizations, it is essential to understand what you are trying to communicate. For example:
For comparison, use a bar chart or line chart.
For distribution, use the histogram or boxplot.
For composition, use a pie chart or stacked bar chart.
For relationships, use a scatterplot or correlation matrix.
Nitty-gritty details of visualization choice are given in the following image: