A verdade sobre a maturidade analítica nas grandes corporações

Criado em:
September 9, 2020
Atualizado em:

Data driven brings several advantages to companies, but most of them do not have a developed analytical capacity - not even large corporations. And we will prove it in this post.

The jargon " data is the new oil " is no longer new to anyone, much less to large organizations.

But make no mistake: there are still analytically lagging companies , especially small and medium-sized ones . And they navigate the first stage of the data driven journey , without exploring the real value of their data.

However, Thomas Davenport, author of the book Analytical Competition , states that far fewer companies - at least among large corporations - are in the first stage of analytical maturity.

For him, most of these organizations are probably in the second stage of the analytical competition, which we usually call launch .

Launch: predominant stage in large companies

At this stage , there is progress in the use of analytics and data, but these technologies are not yet a priority , nor are they seen as a competitive advantage.

Here, companies recognize the importance of data in business . They perform specific analyzes and have localized analytical software or tools. On the other hand, they need to develop important analytical capabilities to evolve in terms of data, technologies, people and processes.

In summary, the main aspect of step 2 is the decentralization of information .

Like this?

Even though the implementation of BI by department is common, there is no cross-referencing of information between the different areas of the business.

In other words: important data is under the exclusive domain of business departments and there is no sharing of valuable information.


At this stage, information storage and collection practices are conducted randomly for specific and localized analysis by different business departments.

Furthermore, there is no centralized structure for its storage like a data warehouse , for example.

As a result, powerful information becomes available in the hands of a few.

We explain better:

At this stage, the data is truly isolated from the organization's other systems, under the control of specific departments, in the famous data silos .

As a result, it is not possible to extract the real value of the information from these companies. After all, there is no integrated database for carrying out in-depth analytical research.

These dysfunctions cause numerous losses such as:

  • Waste of resources
  • Greater possibility of human error
  • Rework and repetitive efforts
  • Wrong or limited planning and strategies
  • Unassertive analyzes


During launch, there is a proliferation of analytical tools throughout the organization.

What does that mean?

Specific departments have basic analytics tools for specific queries such as localized business intelligence systems.

However, there is no type of information integration, much less unified databases for general analytical research.

This way, departments deal with their data individually. As a result, fundamental business information remains isolated from the rest of the company.

It is worth highlighting that, despite technological advances, spreadsheets are still protagonists in this stage, as well as in stage 1 of the Journey.

Other technologies and analytical techniques prevalent at launch are:

  • Individual analytics initiatives
  • Statistical packages
  • Basic Statistics
  • Database query


Here, executives understand the power of data but are not exploiting its full potential. They do not prioritize a data driven culture nor do they have a plan to implement a coherent data strategy.

In other words: the use of data science and analytics is dissociated from the business strategy and is often overshadowed by other company activities.  

The consequence? An organization with disjointed data and communication problems.

At this stage, teams have a certain analytical awareness and companies begin to aspire to the benefits of using data. However, there is little adherence to the data driven movement for reasons such as:

  • Lack of incentives from top management
  • Lack of leadership
  • Lack of analytical processes
  • Lack of organization
  • Lack of direction

Furthermore, these companies do not have established analytical teams. In other words, they generally have few analysts who belong to different sectors and do not participate in the overall business strategy.

Finally, there is little cooperation between departments regarding the use of data, as each sector treats its information individually.

This results in the creation of several data silos that disrupt and impede the flow of important information between different departments, making communication and assertive decision-making difficult for the company.

Law Suit

At this stage, there are already analytical efforts at the departmental level, however there is no structured data process throughout the organization.

Data collection and storage, for example, is conducted by specific departments, in a manual and disorganized manner , without crossover between areas or supervision from senior management.

In terms of analytics, each department carries out localized analyses, without following strategies or processes, with the help of simple analytical tools that are not communicated to the rest of the organization.

To top it off,   there are no unified databases and the databases are spread across business departments. As a result, information becomes isolated and stored in silos.

And this isolation is a big problem. Do you know why?

When information is collected randomly, without following processes, it ends up being lost by the organization.

And this sea of ​​data makes it difficult to carry out specific analyzes fundamental to companies’ decision-making processes.

Some results of this are: less productivity, little collaboration and loss of competitiveness.

Therefore, defining analytical processes is a fundamental step for companies that want to advance in analytical competition.

How to overcome the challenges of the launch phase?

Remember: investing in thousands of analytical tools for occasional use is not the solution for those who want to advance to the next stage of the data driven journey.

Before that, it is necessary to take information out of the hands of a few and democratize access to business insights for everyone.

Check out some key aspects below to evolve in this challenge:

  1. Invest in a robust data infrastructure;
  2. Integrate and store your data in a data warehouse
  3. Invest in analytical technologies
  4. Develop the analytical capacity of all business departments
  5. Commit to the data driven culture

Evolua na jornada data driven com a Indicium

It's clear that the launch phase is full of challenges, but you can overcome them to build a winning data driven strategy .

Indicium specializes in developing personalized data science solutions for the different sectors of your company.

Get in touch and discover the most suitable services for your business.

data driven

Isabela Blasi

CBDO and co-founder at Indicium

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