In an era where data is the true added value of a business, companies need to collect and analyse it in detail to gain a competitive advantage in the market. Business Intelligence projects are, therefore, an added value when it comes to data analysis for better decision-making.

Agile methodologies were introduced to the world in the first decade of the 2000s. And, with them, web and software development became faster and more efficient. However, Agile methodologies are not only used by developers and those in development. Currently, these methods are present in many areas of a company, and especially in Business Intelligence.

In this article, we will address what Business Intelligence is, how Agile methods relate to this practice and how important they are when moving forward with BI projects.

 

Table of contents

What is Business Intelligence?

Agile Methodologies Applied to Business Intelligence

1. Agility in Business Intelligence projects
2. Best practices in implementing Agile Business Intelligence

Conclusion

 

What is Business Intelligence?

Business Intelligence (BI) is a recent, but increasingly common, practice in companies. The ultimate objective is to help managers and CEOs make more accurate decisions that lead a business to have more revenue, to be more innovative in the products/services it develops and, consequently, to make it more competitive.

To achieve this, BI involves using data collection and analysis platforms and presenting findings in easy-to-read formats. This way, it is possible to analyse data and understand the evolution of a business to date, as well as compare past performance with current performance.

Business Intelligence can be carried out through various strategies of data mining, process mining, predictive analytics, performance management, and benchmarking, among others.

Thus, BI can be valuable to gain a new perspective on a business and to adapt the strategy to gain a competitive advantage.

 

Agile Methodologies Applied to Business Intelligence

For Business Intelligence to have even better results, companies have started to use Agile methodologies in the various facets of this process.

In short, Agile methodologies are approaches to project management that allow projects to be completed faster and with fewer errors. That is, these methodologies break the project into smaller, more manageable parts (also known as “Sprints”) that are delivered regularly. These attribute more flexibility to a given project, as it can be continuously improved.

When applied to Business Intelligence, Agile methodologies value collaboration between employees and departments and the flexibility to make changes to a project depending on the conclusions of data analysis and even the opinion of customers/users.

 

Agility in Business Intelligence projects

Agile methodologies have been applied in Business Intelligence projects as a way to make this process more flexible to market changes, as well as so that managers and CEOs can make more informed and accurate decisions for the business.

Through the data analysis that characterises BI so much, companies are now able to identify performance trends. On the other hand, through Agile methodologies, they can reduce the time it takes to present the results of data analysis.

By combining these two practices, Business Intelligence is now called Agile Business Intelligence (Agile BI). By applying an Agile approach to a BI project, you are contributing to:

• Reduction of errors when entering data.
• Data consolidation.
• Accessibility and data analysis.
• Greater collaboration between teams and investors.
• Greater value added to the project and final product.
• Long-term business sustainability.
• Greater competitiveness in the market.

In addition to the results, Agile Business Intelligence is also responsible for having numerous benefits such as:

• Greater flexibility – Crucial for adjusting planning as time progresses, more data is collected, and more decisive conclusions are drawn for the business.
• More quality – The ‘sprints’ characteristic of the Agile methodology allows each part of the project to be launched, reviewed, and improved whenever necessary.
• Greater cooperation – the Agile Business Intelligence method encourages greater collaboration between teams, investors and even customers or users, resulting in better results being achieved.
• More trust – Both from investors and customers or users, as data analysis allows personalised interactions and the development of products/services based on their experiences.

 

Good practices in implementing Agile Business Intelligence

To successfully implement Agile Business Intelligence in a company, it is advisable to follow a series of good practices, such as:

• Making decisions based on data, to the detriment of intuition or just following the previous plan.
• Implement ‘Sprints’ and continuous improvement strategies to make task development faster, while adding more value to the final product.
• Open communication channels to encourage collaboration between teams, and investors and even to receive feedback from customers/users. In this way, teams become more independent and responsible, leading them to make better decisions.
• Adjust planning whenever necessary to meet business needs and changes in markets.

 

Conclusion

Having agility in Business Intelligence projects is more than moving quickly through data analysis to present them in a model that is easy to read and interpret.

Although Business Intelligence is concerned with collecting and understanding data to make accurate decisions, Agile methodologies come into play to make this process more efficient and with fewer risks.

Thus, Agile Business Intelligence is a practice that makes a plan more flexible, means there is more cooperation between teams and investors, and adds more value to a product.

And, as a result, a business can gain more sustainability, as well as more competitiveness in the market.