Business intelligence: How to Turn Your Data Into Strategic Decisions

Business intelligence enables companies to better understand their data in order to make strategic decisions. When properly implemented, it becomes a powerful lever for performance, profitability and growth.

Mallette's digital transformation experts explain what business intelligence is and how to implement it effectively.

What is Business Intelligence?

Business intelligence, also known as Business Intelligence (BI), refers to all the methods, tools and processes that enable raw data to be transformed into useful information for decision-making.

His aim is to help executives and managers better understand their organisation's performance so they can make the right decisions, based on facts rather than hunches.

From raw data to decision-making information

Raw data corresponds to information collected by the company on a daily basis:

• Sales;

• Expenses;

• Production;

• Human resources;

• Inventories, etc.

In its raw state, this data is often scattered across different systems and difficult to read or interpret without prior processing.

Structuring, analysing and visualising data

Business intelligence enables this data to be structured, analysed and consolidated. It is then presented in the form of dashboards, key performance indicators (KPIs) and clear reports, making it easier for managers to understand and use.

A central tool for corporate decision-making

Once transformed into decision-making information, this data can be used directly by management teams. BI then plays a role in strategic and operational decision-making:

• Real-time performance monitoring,

• Trend identification,

• Gap detection

• Measuring the impact of actions taken.

Business intelligence and ERP

Business intelligence really comes into its own when connected to ERP. Together, ERP and BI form a solid foundation for analysing data, monitoring performance and supporting decision-making at every level of the business.

Why connect BI to ERP?

An ERP centralises the organisation's key data: finance, sales, operations, inventory and human resources. By connecting a business intelligence solution to it, the company benefits from complete centralisation of financial and operational data, avoiding information silos and multiple versions of the same figure.

This integration improves the reliability and consistency of information. The data analysed comes directly from the transactional systems, reducing data entry errors, discrepancies between reports and decisions based on incomplete or obsolete data.

Finally, the connection between BI and ERP provides a global view of the business. Managers can view financial performance, operations, sales and key indicators all in one place, facilitating more proactive management aligned with strategic objectives.

Examples of BI + ERP uses

• Financial and margin analysis: profitability monitoring by product, project or customer, comparison of actual costs versus budgets, variance analysis.

• Sales and production monitoring: visualisation of sales volumes, production lead times, inventory levels and operational performance in real time.

• Forecasts and budgets: development of more accurate financial forecasts, scenario simulations and continuous budget monitoring to better anticipate future needs.

What is a business intelligence audit?

A business intelligence audit is a structured approach aimed at assessing how an organisation uses its data to support decision-making. It provides a clear, objective picture of the current state of BI in an organisation, in terms of data, tools and usage.

Analysis of data quality

The audit begins with an in-depth analysis of data quality: reliability, consistency, completeness and updating of information from different sources (ERP, CRM, Excel spreadsheets, internal systems).

Poor quality data considerably reduces the value of analyses and can lead to incorrect decisions.

Evaluation of tools, processes and practices

The next step is to evaluate existing tools and processes. This includes examining the BI solutions in place, the dashboards used, the data collection and transformation mechanisms, and the level of adoption by the teams.

Identifying decision gaps

Finally, the business intelligence audit identifies gaps between the data available and the decision-making needs of executives and managers.

This analysis highlights missing indicators, irrelevant reports and under-exploited information, so that BI can be better aligned with business priorities.

How to implement a business intelligence solution

Implementing a business intelligence solution is based on a structured approach, aligned with the company's real objectives.

Beyond the tools, the success of a BI project depends above all on the clarity of the requirements, the quality of the data and the choice of an appropriate solution.

Step 1: Define your business objectives

Before any technological considerations, you need to clarify the business objectives that the business intelligence solution needs to support.

This stage involves answering questions such as :

• What indicators should be monitored?
  Identify the performance indicators (KPIs) that are really useful for steering the business: profitability, margins, cash flow, sales, productivity, lead times, etc.

• Who are the decision-makers?
  Determine who will use the information: general management, finance, operations, sales, team managers. Each profile has different needs.

• What concrete uses?
  Are we talking about day-to-day monitoring, strategic decisions, forecasts, budgets or one-off analyses? BI must meet specific uses, not produce unused reports.

This step avoids the common mistake of creating dashboards with no decision-making value.

Stage 2: Structuring and making data reliable

Effective business intelligence depends on reliable, well-structured data. The first step is to identify the relevant data sources:

• ERP (finance, operations, inventory)

• CRM (sales, customers)

• Excel files

• Other internal systems or databases

Next, an effective data governance must be put in place. This includes defining responsibilities, validation rules, update frequency and quality controls. Inconsistent or incomplete data directly undermines the credibility of analyses.

Step 3: Choosing the right business intelligence solution

Once the objectives and data have been clarified, the business intelligence solution that is best suited needs to be selected.

Tools like Power BI offer great flexibility, seamless integration with ERP and Microsoft 365, as well as advanced visualisation and analysis capabilities.

The main choice criteria should include:

• the simplicity of use to encourage user adoption;

• the data security, including access management and compliance;

• the evolutivity, so that the solution can grow with the business and adapt to new needs.

Turning your data into a competitive advantage

Whether we're talking about implementing an initial solution, integrating BI into an ERP system or carrying out a business intelligence audit, a well-thought-out approach tailored to the reality of the organisation is essential.

At Mallette, our digital transformation and business intelligence experts support organisations every step of the way, from analysing needs to implementing and optimising BI solutions, in order to transform data into concrete, sustainable decisions.