Organized data: the next step in digital maturity

After digitalization comes the question of data

Digital transformation in companies often begins with the use of new platforms: CRM, ERP, marketing platforms, or internal management tools. This first step is important because it eliminates manual tasks and makes employees more agile in their day-to-day work. But as digital transformation progresses, an inevitable question arises: is the data generated by these platforms really being put to good use?

This is when many companies realize that digitizing is not the same as evolving digitally. When information is scattered, poorly structured, or unreliable, it becomes difficult to take real advantage of technology. Therefore, organizing and working with data is the next step in digital maturity, the one that allows existing technology to be transformed into efficiency, predictability, and growth.

What is meant by “data” in a company

When we talk about data, we are not just talking about complex reports or advanced statistics. In a company, data is everything that describes the operation and allows you to understand the business: customer contacts and history, leads generated, commercial interactions, sales made, orders, stocks, delivery times, support tickets, response times, documents, among others.

In other words, data is the company's memory. It is a record of what happens on a daily basis and the basis for understanding what is working, what is failing, and where there is room for improvement. Without this foundation, technological evolution is limited to isolated improvements with no structural impact.

Data is the driving force behind business evolution

As businesses grow, complexity increases. There are more teams, more processes, more points of contact with customers, and more decisions to make. In this context, data becomes essential because it allows you to move from reactive decisions to informed decisions.

Well-organized data helps identify patterns of operation and customer behavior, detect inefficiencies or unnecessary expenses, track results clearly, adjust strategies based on evidence, and measure impact and growth over time.

This is the leap that distinguishes companies that merely “have technology” from companies that use technology to continuously improve.

Data as the basis for automation and Artificial Intelligence

Automation and Artificial Intelligence depend directly on the quality of the information available. Without consistent data, automation fails, repeats errors, or generates unreliable results. The same is true for AI: intelligent models can only support decisions when they have access to structured and relevant data.

Therefore, the issue is not “having AI” as a novelty. It is understanding where AI and automation make sense and what kind of data is needed to generate value. In many companies, the first step begins with the use of existing solutions, tailored to the specific needs of the business and departments. The key is to recognize that AI applied with impact requires well-prepared data.

Simple examples of data use with real impact

You don't have to be a large company to benefit from data. Small applications can generate clear improvements in everyday life:

• Commercial management and leads: by analyzing where the best contacts come from and which ones evolve into real opportunities, it becomes possible to prioritize actions and reduce effort.
• Support and customer service: data on frequent requests or response times helps improve internal processes and even automate simple responses.
• Internal operations: measuring times, repetitive tasks, and failures allows you to automate flows and eliminate rework.
• Marketing: campaign data helps you target and communicate more accurately, avoiding generic actions with no return.
• Sales and planning: by identifying demand patterns, it is possible to predict needs and plan with greater confidence.

These are some examples that show that data brings value when used for concrete decisions, even if in small and progressive steps.

The big obstacle: scattered data

A very common problem in companies is the dispersion of information. Data is scattered across various platforms—CRM, ERP, Excel, email, support tools, and even informal channels such as messages or loose files. Each team ends up working with its own “version of the truth,” which can lead to inconsistencies, duplication of information, operational errors, contradictory reports, time wasted confirming data, difficulties in automating processes, and decisions based on estimates rather than facts.

It is important to note that this is not just a technological problem. It is also a problem of internal organization and processes. The lack of structured data prevents existing technology from reaching its full potential.

How to start organizing data

The process of organizing a company's data can be gradual, as long as there is a clear direction. A few simple steps will help you move forward safely:

1. Define the main source of information: identify where you should centralize the most important data (for example, customers and leads in CRM, and all billing in ERP).
2. Centralize scattered information: reduce the number of systems where important data is stored.
3. Create update rules: define who updates, when, and with what criteria.
4. Eliminate duplication and inconsistencies: standardize fields and ensure that information follows a common logic.
5. Start with simple metrics: before investing in advanced models, start by measuring the essentials and ensuring reliability.

Organized data is the next step in business evolution

Digital maturity is not just about using technological tools. Digital evolution involves using data to improve operations, support decisions, and create continuous efficiency. Without organized data, automation fails and AI cannot be relevant.

Working with data is an inevitable step for any company that wants to evolve sustainably. It is not about accelerating at any cost, but about building a solid foundation that allows for clear growth. Digitization creates the structure, and data is the answer for the evolution of companies.