The importance of data analysis in decision making

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It has become increasingly essential for companies to incorporate a data-driven culture, especially with the advancement of digital technologies for data analysis. Advances in machine and deep learning techniques and big data has created incredible opportunities to use these strategies for business growth.

With the advancement of Generative Artificial Intelligence and research into the creation of General Artificial Intelligence, there is still the possibility of beginning a new phase of this approach soon. If your company wants to be prepared for a smart, data-driven future, you need to start these changes today.

Below, we will show some points that highlight the importance of starting to invest in adopting data analysis in your company's decisions.

The importance of data analysis

According to Gartner, one of the largest technology consultancies in the world, around 60% of companies will have adopted a data-driven approach by 2025. This shows the power of data analysis, in practice, and how it is a trend around the world.

Check out some of the reasons why it has stood out below and why it is important that you consider adopting it in your company.

Extraction of relevant KPI list

A robust data analysis strategy does not think about the volume of information, but rather its relevance to the company. The idea is not to analyze everything, deepening the focus on consistent indicators, which really matter for the objectives.

Often, an excess of data that is not, in fact, essential, can confuse decision makers more than be useful. A well-designed strategy can identify which KPIs are really relevant and correlate them with each other in an intelligent way. As a result, the organization always has accurate data focused on what really matters in this scenario.

Taking the organization into the digital age

The future is digital and requires companies to be aligned with this paradigm. And data is increasingly part of this process, going beyond decision making. For example, they allow you to better understand target audience trends, analyze financial scenarios, identify crises more quickly, among other points.

Performance analysis

One performance analysis Guided by data analysis strategies, it allows us to know the internal bottlenecks in the company. This points out spaces that need attention and care and even indicates possibilities for automation in these fields.

For example, a manager can monitor, in data analytics, that rework rates in a certain sector are above the company average. This may indicate that there is a problem that is affecting the execution of tasks — for example, a process design error.

This way, management can make diagnoses and corrections more precisely and prevent these problems from affecting other sectors. In some cases, it is possible to adopt solutions that allow process automation in these areas.

Use of resources more rationally

A common problem in companies from different segments is the waste of financial resources due to making decisions that could seem interesting. However, with a more strategic analysis, you can see that focusing on this is not that advantageous.

For example, the decision to change positioning for a certain new target audience may seem attractive at first, in line with an apparent trend in the market in general. However, when analyzing data from internal consumers, it would be possible to see that the consumer public differs from the market average.

By analyzing this information, strategic resources are saved that could be used, for example, for internal modernization of the company or other important actions. Something that can be solved with a culture of data-driven decision making.

Data-driven decision making

From the data observed in data analytics, it is possible to obtain interesting views and make decisions that really add positively to the growth of the business. Furthermore, it is possible to act proactively in possible crisis scenarios.

A common mistake is actions defined by a feeling. This is because observation of the scenario does not show nuances and trends that are beginning to appear, while the data is capable of demonstrating this.

Furthermore, with information in hand, it is possible to show the coherence of decisions to stakeholders, investors and shareholders, favoring fundraising processes. This is a criterion that highlights the maturity of the business and increases the confidence of these actors in the company's management capacity.

How to use data analytics techniques for decision making

Now that you know the importance of using data for decision-making, it's time to move forward and implement this approach in your company. Check out some steps below that will be essential for this.

Implement a data-driven culture in your company

Before thinking about processes, solutions and technologies, it is necessary to reformulate the company's internal culture, turning it towards data-driven. This means that your professionals will be encouraged to collect, store, analyze and protect this data, recognizing patterns and identifying possible problems based on them.

It is also part of redesigning processes so that they are, whenever possible, supported by strategic information or that provide data that can be used in the future.

Have data experts working with your company

Whether allocated internally or by hiring partner companies, it is essential to have specialists in data strategies and technologies (such as big data, adoption of solutions based on machine and deep learning, business intelligence, among others).

These specialists may include professionals from:

  • data engineering and architecture;
  • machine learning engineering;
  • data science (or data science), among other possibilities.

Invest in data analytics solutions

Data analytics tools, together with internal changes and support from experts, will be responsible for the adoption of data-driven strategies. In this case, it is important to analyze some important points, including:

  • if the solution allows you to analyze strategic KPIs for your business;
  • whether it has security protocols to protect data and whether it is aligned with the LGPD (General Data Protection Law);
  • whether the supplier provides adequate support in case of questions and problems.

Tips for implementing a data-driven culture in organizations

Making internal cultural changes can be a challenge in companies, especially those just starting out. digital transformation process now. Therefore, some tips that can help in this process are:

  • have a clear, quantifiable objective with a deadline for this change;
  • involve employees in decision-making, communications and training to centralize data-driven decisions;
  • define the strategic KPIs that should be analyzed;
  • choose the tools most aligned with the business proposal;
  • review transformation processes when necessary.

Data analysis is capable of transforming a company, making it more strategic, efficient and reducing errors and rework. Adopting it can provide significant internal changes that will be essential for the organization's growth.

Do you have other questions about the subject? Leave it in the comments and we will respond!


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