8 mistakes to avoid in Business Intelligence (BI)



Published26 August 2022at10:58, updated on11 January 2023at15:16

8 mistakes to avoid in Business Intelligence (BI) cover

IDC estimates that the business intelligence market will continue to grow at a rate of 8 percent through 2022. But despite the success of these types of business software solutions, most projects fail at some point in their implementation. What are the causes? How can they be avoided? To help you, we at Mindquest collected a list of 8 mistakes to avoid when it comes to Business Intelligence.

Also read our Business Intelligence Analyst job description

Business Intelligence: decision-making technology

The purpose of Business Intelligence (BI) solutions is to provide information that facilitates decision-making with real-time data. Therefore, in an ever-changing environment, BI software is increasingly indispensable.

Moreover, the union between BI and Data Science is expanding the horizon of possibilities of Business Intelligence to limits that were unimaginable just a few years ago.

But in order for your company to benefit from all this business decision-making technology, it is necessary to carry out a good implementation.

The following are the 8 most common mistakes to avoid when it comes to Business Intelligence.

The 8 mistakes to avoid in Business Intelligence

mistakes to avoid Business Intelligence

Business Intelligence mistakes that companies often make are often the same. Therefore, let’s take a look at the “manual of bad practices” in Business Intelligence implementation.

Firstly, avoiding a BI software implementation problem means anticipating it, which is why it is necessary to know in advance.

1. Not defining the objectives of the software properly in the planning phase

To start, it is a big mistake to think that just by setting up a BI solution it will work by itself, as if by magic. Business Intelligence is just a tool, and it will work as long as it is handled with skill.

For it to work, the objectives to be achieved with the implementation need to be set from the outset. These must also be aligned with the business objectives. This is the only way to get a return on the investment in Business Intelligence.

2. Give all the power over the BI tool to the IT department.

Related to the previous point, for the software to be aligned with business objectives, the implementation must transcend the IT department.

In other words, the more business-oriented managers and executives must actively participate in defining the objectives that the BI must meet.

3. Choosing a Business Intelligence technology that does not meet the requirements of the business.

There is a multitude of software vendors with different technical and functional solutions on the market, and then there are customized solutions. Whatever your company may select, the software must be tailored to your business needs.

Be suspicious of one-size-fits-all solutions. Since the best business intelligence technology will depend, in most cases, on the size of your company, the sector in which you operate, the type of activity, etc.

4. Not doing a good job of integration

For the BI solution to deliver the desired results, integration with the company’s databases is crucial.

Companies that still rely on Excel for everything have a problem in this regard, and need a complete overhaul of their systems. BI that is well integrated with data from ERP, CRM, etc., is crucial.

5. Neglecting data quality

One of the consequences of not doing a good job of integrating with the company’s databases is poor data. But there are other reasons why data may be of poor quality, irrelevant or incomplete.

There must be controls in place to avoid loading erroneous data into Business Intelligence, ETL (Extract, Transform, Loud) processes, etc.

6. Prioritize the front-end and leave the back-end in the background.

Although the purpose of a BI tool should be to present dashboards, reports, and charts visually that facilitate the analysis of information (front-end), the configuration of internal processes (back-end), which are responsible for processing all the information that is then to be displayed, should not be overlooked.

Giving equal importance to the back-end and front-end is crucial for choosing the right technology when implementing or developing a Business Intelligence solution.

7. Not sufficiently protecting your BI data

Certainly, developing a solution with self-service options that democratize data and extend it to more internal users is often beneficial to a company.

Mobility also enables more practical use of technology, allowing, for example, access to reports from a smartphone or other device from anywhere.

But all this can also pose a serious security problem when an employee views information to which he or she should not have access or an employee loses his or her smartphone, opening the company’s doors to any stranger. Effective controls need to be put in place to ensure legal compliance and company security.

8. Forgetting the end user

Last but not least, training the employees and professional profiles that must handle the Business Intelligence solution is fundamental if we want them to use it.

Low adoption is one of the main reasons why the implementation of BI in the company can fail.

A good training program is very useful, but it is not enough. The employee must understand why it makes sense for the company to use Business Intelligence, and why it is important for them to use it.

Also read the differences between Big Data and Business Intelligence


To conclude, Business Intelligence is the ability to visualize data in an easily interpretable way with powerful top-down navigation that makes it easy to get to the source of the detected problem.

If we associate it directly with information technology, we can say that BI is the set of applications, technologies, and methodologies that can collect and transform data into valuable and structured information that can be used and analyzed directly.

For this reason, it is important to know the most common mistakes to avoid in Business Intelligence, to convert information into valuable data for decision-making.

You can also read : 11 Best Business Intelligence Tools of 2023

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