In a context where companies have ever-increasing volumes of data at their disposal, Business Intelligence (BI) is emerging as a major driver of management and performance. However, despite significant investments, many BI projects struggle to deliver on their promises: dashboards are rarely used, data is considered unreliable, and delivery times are too long.
Why these repeated failures? And above all, what are the concrete keys to a successful BI project, beyond the choice of tools? Drawing on our experience in the field, we share the determining factors for transforming data into a real decision-making aid.
1. Understand the business challenges before talking about technology
One of the main causes of BI project failure is an overly technology-focused approach. Implementing a powerful tool is not enough if business needs are not clearly identified.
A successful BI project begins with:
- Identifying decisions that need improvement (commercial management, financial monitoring, industrial performance, etc.);
- The definition of indicators that are truly useful to the business lines;
- Prioritizing high value-added use cases.
This scoping phase allows concrete use cases to be identified that are directly aligned with the company's priorities. BI then becomes a tool that serves the strategy, rather than an end in itself.
2. Ensure data reliability and governance from the outset
Data quality is an essential prerequisite. BI based on incomplete, inconsistent, or poorly understood data quickly loses user confidence.
The most effective projects incorporate the following from the outset:
- A shared definition of indicators;
- An analysis of the quality of source data;
- Clear rules for data management and processing;
- Governance defining roles (data owner, business representative, IT).
Implementing pragmatic governance tailored to the maturity of the organization ensures the sustainability of BI and its evolution over time.
3. Design a scalable BI architecture
BI needs are evolving rapidly: new business lines, new scopes, growing volumes of data. A fixed architecture quickly becomes a hindrance.
Best practices observed in the field include:
- A clear separation between data ingestion, storage, and retrieval;
- The use of modular architectures, often cloud-based;
- Anticipating volumes, performance, and future analytical uses.
The goal is to build a platform capable of supporting the company's growth without calling into question the existing system with each new development.
4. Choosing tools: a means, not an end
The choice of BI tools remains an important factor, but it must come after the business challenges, architecture, and governance have been clarified. Solutions such as Power BI, Tableau, and Looker now offer rich and complementary capabilities, provided they are selected based on usage, existing constraints, and the organization's data maturity.
Experience shows that the success of a project depends on the right combination of methods, tools, and support.
5. Engage users to promote adoption
A BI project is only successful if it is used on a daily basis. End-user adoption is therefore a key issue.
The key factors for membership are:
- Involvement of business lines from the design phase onwards;
- Simple and easy-to-read dashboards;
- Ergonomics tailored to user profiles;
- Comprehensible and actionable indicators;
- Change management support (training, support, iteration).
BI that is perceived as a control tool is rarely adopted. However, when it becomes a decision-making aid, it naturally becomes part of everyday practices.
6. Adopt an iterative and pragmatic approach
BI tunnel projects, delivered after several months without intermediate visibility, are increasingly rare—and often risky.
Feedback shows the effectiveness of one approach:
- Incremental, with regular deliveries;
- Value-oriented, with each iteration responding to a specific need;
- Adjustable, thanks to quick user feedback.
This approach makes it possible to secure the project, gradually improve usage, and quickly demonstrate ROI.
7. The key role of the IT services company: expertise, methodology, and support
Beyond technical implementation, the IT services company plays a key role in the success of a BI project. Its contribution lies in particular in:
- The ability to translate business challenges into data solutions;
- Mastery of best practices from a variety of projects;
- Support for change and data acculturation.
It is this combination of technical expertise and business understanding that makes it possible to secure projects and maximize their impact.
The success of a Business Intelligence project does not depend solely on the choice of tool or technology. Above all, it is a business project that combines business vision, data quality, governance, and user support.
By relying on a proven methodology and an experienced partner, BI becomes a powerful strategic management tool that supports performance and decision-making.
At Antaes, our BI consultants help organizations get the most out of their data by designing decision-making solutions that are aligned with their business challenges and performance goals.
By Vincent T.
Business Intelligence Consultant
