Big Data

How to use data to make a company data-driven

25 of January of 2023

Data has the potential to transform a company. It can make a business more organized, more productive, and ultimately, more efficient. So many companies are aiming to become data-driven. This means they leave decision-making based on opinions or estimates for something much more sure: interpreting data.

Until now, collecting, analyzing, and reporting data in the construction sector has not always gotten the attention it deserves. However, this is changing as they learn more about its advantages. Companies increasingly understand that data is essential to analyzing the present and improving the future. 

Reporting data is essential in this transformation. In this step, data becomes information that employees, managers, and other actors involved can easily understand. This is when it stops being just data and becomes a tool for making the best decisions. 

From pieces of data to valuable information

Before, many business decisions were based on “because I say so” logic. The new concept of the type of company we call data-driven seeks to change this premise and instead be based on data interpretation, which indicates the best possible option. 

The amount of data that companies can collect and organize is vast. Companies like mine that are focused on construction, employ what we might consider big data on a small scale: it uses a large data set but at a fairly limited level. 

This data can come from practically any field: we analyze the execution of projects, personnel activity, financial aspects, or everything related to material purchases, for instance. In a data-driven company, nothing should go unexamined in terms of data.

This information is collected and stored with big data tools, such as data lakes (storage repositories containing a large quantity of raw data stored there until needed). Subsequently, analyzing and organizing data are required to turn it into useful information. 

Reporting, as well as standardization and pattern-finding techniques, can help us organize these ideas and make limited catalogs of information that are easily understandable. Many aspects can be reported on within one project: the level of execution, the use of resources, or meeting deadlines, for example. 

After the analysis comes the prediction. This information helps understand what is needed, as well as improve business actions. It offers the knowledge needed to change anything detracting from the quality of a project to optimize the use of resources and to prevent repeating errors that may have caused a small delay in deadlines. Conscious decisions based on objective issues are thus made, offering a competitive edge. 

Security, equipment, and other changes

Since using data is usually related to decision-making involving different aspects, it is often difficult to identify success stories where data has been the sole driver of change. But we can point out that retrospective analytics has been fundamental to establishing improvements at our company.

One good example is accident analysis at our construction sites, which allowed us to identify factors impacting fatal accidents. We realize that it’s not enough to send out messages like “wear your helmet.” For example, data has enabled us to analyze whether workers have to drive for a long time to get to construction sites and, therefore, whether they are more tired and distracted during the work day. It gives us the opportunity to look beyond and suggest changes that had not been considered before. 

Data reporting has also been used to improve Global Workforce Planning. The Human Resources department had trouble knowing what staff was on construction sites and predicting how many workers it would need for new projects. Years ago, the department would have made decisions based on estimates or conclusions drawn from past experiences.

This time, data helped them know how many workers they should hire and which professionals in the workforce could be relocated to carry out new projects. In addition, it offered them information about which profiles were most suitable. All this was essential to optimizing the work of the Human Resources department. 

There are so many more examples of this. The fact is, data can lead to a 180-degree turn in the way work is organized at companies and organizations. In the construction sector, they can help achieve a circular evolution, adjust budgets, improve predictions, and ultimately optimize the business. 

Data lets companies like mine base their decisions on the most solid foundations there are: those that rely on objectivity. Thanks to this constant effort to collect, analyze, and interpret data, we can make sure that those decisions are data-driven and, therefore, the best decisions possible. 

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