Business intelligence best practices have enormous implication during the implementation of any BI initiative within an organization. Coupled with business intelligence solutions available in the market, they can help businesses increase the success of getting the most out of their stored data to drive intelligent insights, better understand their customers, and take more informed business decisions.
Typical business intelligence best practices include ensuring executive sponsorship, defining clear objectives, identifying relevant data sources, establishing data governance frameworks, using intuitive dashboard visualization, enabling self-service analytics, and continuously monitoring the implementation.
Business intelligence has taken the corporate world by storm because of the positive impact it can provide by giving all the possible means to effectively analyze data and understand how any company is operating. That’s why, it is critical for organizations to derive valuable insights from the vast array of data sources created by the rapid development of technology and digitalization.
Based on my 15+ years of industry experience, I found out that implementing these best practices in addition to following up with the latest BI trends and understanding the components of BI can help you overcome related challenges and boost your implementation success rate by up to 40%.
So, let’s get started.
Business intelligence best practices you should incorporate in your organization
More than ever, our daily lives and the foundation of modern business decisions rely significantly on the intelligence of data science. With the development of big data capabilities, businesses are now able to use analytics to provide actionable insights that guide important corporate decisions and manage the full BI cycle.
If your organization follow these guidelines, it will be able to increase its productivity, awareness, and success.
The business intelligence best practices are:
1- Ensure executive sponsorship
Whenever a new initiative has to be implemented in any organization of any size, the first thing to do is to ensure that key senior executive employees are fully supporting this project. During the implementation phase, you will face many BI challenges that might need to be backed by senior management to overcome them.
The investment that has to be done during a BI initiative is crucial and involves hardware, software, trainings, and support. First you need to make sure the right budget and resources are allocated. Second you need to make sure that every key employee in every department is aligned with the overall mission in order to make it a success.
2- Clearly define objectives
Make sure to clearly define the business objectives and the goals that you are trying to achieve when kicking off a new BI initiative and how they align with the overall strategic objectives of the organization.
This step is very critical in the list of BI best practices as it will give you the opportunity later on to measure the success of failure of this project. A successful BI deployment will ultimately be aided by having clear objectives and predetermined key performance indicators (KPIs).
Moreover, this step will enable you to engage your employees with a compelling vision that fuels their motivation and fosters organizational alignment to achieve desired outcomes. Employee resistance to adopting business intelligence can be a critical factor contributing to failing of achieving the full role of business intelligence. Therefore, it is vital to actively involve and connect employees to a well-defined mission, ensuring their commitment and dedication.
By doing so, you can mitigate resistance and cultivate a shared sense of purpose and enthusiasm for leveraging BI effectively.
3- Identify relevant data sources
No matter the industry or the size of the organization, every day we collect and work with huge amount of data that is being used in internal processes. At this point, data that is being used by each department can be stored and saved in different repositories making it inaccessible and hard to find by a BI tool.
A fundamental best practice is to assess the presence of data silos within your organization and create strategies to integrate them into a central system. This approach ensures a unified and streamlined approach to visualizing data and performing analytics. By breaking down data silos and enabling access to a core system, you can enhance data visibility, eliminate redundancies, and facilitate comprehensive data analysis.
4- Establish data governance
Establishing data governance is widely regarded as one of the best practices in business intelligence (BI) due to its crucial role in ensuring the accuracy, reliability, and security of data.
The policies/standards, decision rights, accountabilities, and mechanisms of enforcement for people and information-systems as they carry out information-related operations are all covered by the large and complicated topic of data governance.
Having a robust DG framework available can help your business establish data accountability and ownership, define data quality standards, and enhance compliance with your industry regulatory and rules. It also promotes trust in the data stored which will increase the confidence of taking better informed business decision by major stakeholders available in your company.
5- Use intuitive visualization
Data is mostly understood by using charts, graphs, and intuitive dashboards. You got to make sure that the reports generated include very user-friendly graphs to help senior executives easily identify a pattern or help drive business insights.
This will help improve productivity and making the project more appealing and can be easily shared between appropriate employees. That will help you in your overall implementation as visually appealing products usually tend to have a higher adoption rate.
6- Enable self-service analytics
The aim of business intelligence is to provide a way for business decision makers to slice and dice the data stored in a smooth way without being tech savvy. Self-service analytics empowers non-technical users with the capability to work with available data in a manner that suits their specific needs and promotes better understanding, thus enabling them to extract valuable insights.
This approach grants individuals the freedom to explore and analyze data independently, without relying on IT or data experts. By providing intuitive tools and user-friendly interfaces, self-service analytics democratizes data access and analysis, allowing users to manipulate and visualize data according to their preferences.
7- Continuously monitor and evaluate
Regularly monitor and evaluate the performance of your business intelligence initiatives. Identify areas for improvement, track key metrics, and make necessary adjustments to enhance effectiveness.
As explained previously, this can only be happened when you already have a well-defined objectives that will help you to monitor the process. During the implementation phase, you need to collect feedback from employees, identify bottlenecks if any, and make sure that everyone is confident of using the dashboards available for maximum reachability.
