Is your company data-driven?
A data-driven company makes decisions based on data, not intuition. The 5 signs of analytics maturity and the most common gaps that prevent progress.
In an increasingly digital world, becoming data-driven has become the ultimate goal for companies that want to remain relevant and deliver even greater value. And this is no coincidence...
The World Economic Forum's report on the Fourth Industrial Revolution listed the key skills that employees of future companies need to have, proving that the (not-so-distant) future of business is digital, and the fundamental competencies for companies and professionals will be increasingly focused on data analysis and building more agile, assertive organizations.
With the COVID-19 pandemic in 2020 and 2021, this goal was accelerated as even more companies underwent rapid digitization, pulling innovation projects off the shelf and implementing them to find a quick response to a chaotic environment.
But what does being data-driven actually mean? In this article, Erathos explains the 8 key characteristics of companies with this profile. Is yours one of them?
What is a data-driven company?
To start off, the easiest way to describe this profile is to think of the core concept behind data-driven organizations: they are companies that put data analysis at the center and forefront of every business strategy and decision. Of course, on paper, this can mean many things, but how does it look in practice?
Being data-driven is about much more than simply collecting data, installing the right software, and having the best plug-ins in your systems. It is a complex process that begins and ends with a strong cultural transformation, globally across the organization and not just within a single department.
The revolution starts from the inside out
An article published by Forbes Magazine in early 2022 revealed 12 reasons why digital transformations fail inside companies, and it is no surprise that almost all of them translate to: focusing too much on tools, numbers, and pretty dashboards while leaving behind the creation of an end-to-end data culture. And in practice, that is what being data-driven is all about!
To find out if this is already in your company's DNA, we have highlighted 8 characteristics of truly data-driven companies to help you understand where you need to take action!
1) Data-driven companies understand that digital transformation is an ongoing process
A very common mistake is when an organization focuses on building a data case by only thinking about infrastructure implementation: deploying the latest BI tools, AI, building data warehouses, data lakes, or even implementing an efficient data lakehouse, and at the end of the process believing that "mission accomplished, we are now data-driven!" when in reality, these implementations are just a step in the process.
Being data-driven is a continuous process built into every decision, by all employees and managers. While having the necessary tools is a crucial step, it doesn't end there!
2) They know their data maturity level
A company's data maturity is an important metric for understanding how advanced its relationship is with the data it collects throughout its operations.
There are several frameworks used to measure these stages, but in short, they point to similar elements: the company's strategic objective and vision for data use; not just the tools used for collection, storage, and analysis, but also who has access to them within the organization, and how these touchpoints happen; and finally, how this data drives action and decision-making.
Companies like Uber, Airbnb, and iFood have such high data maturity that they can hardly be considered just transport, hospitality, and food delivery companies—they are tech companies because they apply a scientific approach to data that is accessible to everyone interacting with their brands. This translates into practice for both external customers and their employees.
3) They have high Data Literacy
The concept of Data Literacy is used to define the ability to read, understand, create, and communicate data efficiently. Unlike traditional literacy, this term refers to a specific set of skills that need to be developed by everyone who works with data.
Companies with high Data Literacy—meaning a large portion of their workforce can communicate effectively through critical data analysis—lead in several key market criteria and tend to be highly data-driven.
4) Their processes are automated
Using AI and automation in data collection and processing is highly strategic because it minimizes errors, improves the quality of the collected information, and provides real-time visibility into performance. This is crucial because it reduces response times for everyone involved in decision-making, crisis management, and risk mitigation.
5) Data is not treated as a hierarchical privilege
When it comes to data science, the companies that lead are those that invest in data democratization.
Collecting data just for the sake of collecting it is not an advantage—you need to apply it across end-to-end business strategies. However, how can you do this with agility if there are gaps from operations to upper management, and even to end-users, regarding who can access, interpret, and analyze this information?
In companies that are less democratic with their data, there is usually a bottleneck in information distribution, which remains concentrated in upper management with low cross-functional visibility. This is a bottleneck that slows down decision-making.
For example: if an executive is the only point of contact for metric analysis, and they are only reviewed in weekly—or even monthly, in some cases!—meetings, issues that could have been identified and resolved immediately end up going unnoticed.
6) Departmental data is interconnected
Another key factor is breaking down data silos, which are sets of data isolated from the rest of the company, locked within a single department without interacting with other areas. Cross-communication is essential to make better, data-driven decisions.
For example: if finance has real-time access to sales data or marketing metrics, the response time to market changes decreases, allowing for more targeted campaigns and motivating teams to build new strategies.
7) The company generates value through its data
As mentioned above, not having a strategy or a goal for the data you collect is one of the biggest mistakes companies make when trying to be data-driven. Using this information intelligently involves having a plan to leverage data to create the best customer experience through personalized services and products, delivering exclusive customer support.
Some companies that do this incredibly well are Nubank, Google, iFood, Netflix, and Uber: through the data they have on their users, they deliver experiences and brand touchpoints tailored to each consumer profile. This personalization builds stronger loyalty, increases value, reduces churn, minimizes detractors, and empowers users.
8) Data analysis is already part of the culture!
A truly data-driven company doesn't make decisions based on gut feeling; it generates insights based on real data. This is deeply rooted in the culture: everything is done with a rational purpose to guide decisions, from purchasing tangible resources to the employee journey, marketing campaigns, or sales team budgets.
Contrary to popular belief, having this culture does not eliminate creative thinking or processes within organizations. On the contrary, it aids innovation by providing the tools needed to implement, test, and learn quickly from the process.
Conclusion
Truly data-driven companies have a highly mature relationship with the information they generate. They have clear purposes, strategies focused on generating value through data, high data literacy, and efficient internal communication.
From the outside, it might seem like an intimidating process, but it is transformative for every part of the organization. Because of this, having a strategic partner assisting at every stage of your data-driven journey reduces your business's time-to-value and helps you reach data maturity faster.
Erathos was created with this exact purpose: to reduce the time-to-value of data initiatives to co-create data-driven organizations. Discover our solutions and join the data-driven revolution!
In an increasingly digital world, becoming data-driven has become the ultimate goal for companies that want to remain relevant and deliver even greater value. And this is no coincidence...
The World Economic Forum's report on the Fourth Industrial Revolution listed the key skills that employees of future companies need to have, proving that the (not-so-distant) future of business is digital, and the fundamental competencies for companies and professionals will be increasingly focused on data analysis and building more agile, assertive organizations.
With the COVID-19 pandemic in 2020 and 2021, this goal was accelerated as even more companies underwent rapid digitization, pulling innovation projects off the shelf and implementing them to find a quick response to a chaotic environment.
But what does being data-driven actually mean? In this article, Erathos explains the 8 key characteristics of companies with this profile. Is yours one of them?
What is a data-driven company?
To start off, the easiest way to describe this profile is to think of the core concept behind data-driven organizations: they are companies that put data analysis at the center and forefront of every business strategy and decision. Of course, on paper, this can mean many things, but how does it look in practice?
Being data-driven is about much more than simply collecting data, installing the right software, and having the best plug-ins in your systems. It is a complex process that begins and ends with a strong cultural transformation, globally across the organization and not just within a single department.
The revolution starts from the inside out
An article published by Forbes Magazine in early 2022 revealed 12 reasons why digital transformations fail inside companies, and it is no surprise that almost all of them translate to: focusing too much on tools, numbers, and pretty dashboards while leaving behind the creation of an end-to-end data culture. And in practice, that is what being data-driven is all about!
To find out if this is already in your company's DNA, we have highlighted 8 characteristics of truly data-driven companies to help you understand where you need to take action!
1) Data-driven companies understand that digital transformation is an ongoing process
A very common mistake is when an organization focuses on building a data case by only thinking about infrastructure implementation: deploying the latest BI tools, AI, building data warehouses, data lakes, or even implementing an efficient data lakehouse, and at the end of the process believing that "mission accomplished, we are now data-driven!" when in reality, these implementations are just a step in the process.
Being data-driven is a continuous process built into every decision, by all employees and managers. While having the necessary tools is a crucial step, it doesn't end there!
2) They know their data maturity level
A company's data maturity is an important metric for understanding how advanced its relationship is with the data it collects throughout its operations.
There are several frameworks used to measure these stages, but in short, they point to similar elements: the company's strategic objective and vision for data use; not just the tools used for collection, storage, and analysis, but also who has access to them within the organization, and how these touchpoints happen; and finally, how this data drives action and decision-making.
Companies like Uber, Airbnb, and iFood have such high data maturity that they can hardly be considered just transport, hospitality, and food delivery companies—they are tech companies because they apply a scientific approach to data that is accessible to everyone interacting with their brands. This translates into practice for both external customers and their employees.
3) They have high Data Literacy
The concept of Data Literacy is used to define the ability to read, understand, create, and communicate data efficiently. Unlike traditional literacy, this term refers to a specific set of skills that need to be developed by everyone who works with data.
Companies with high Data Literacy—meaning a large portion of their workforce can communicate effectively through critical data analysis—lead in several key market criteria and tend to be highly data-driven.
4) Their processes are automated
Using AI and automation in data collection and processing is highly strategic because it minimizes errors, improves the quality of the collected information, and provides real-time visibility into performance. This is crucial because it reduces response times for everyone involved in decision-making, crisis management, and risk mitigation.
5) Data is not treated as a hierarchical privilege
When it comes to data science, the companies that lead are those that invest in data democratization.
Collecting data just for the sake of collecting it is not an advantage—you need to apply it across end-to-end business strategies. However, how can you do this with agility if there are gaps from operations to upper management, and even to end-users, regarding who can access, interpret, and analyze this information?
In companies that are less democratic with their data, there is usually a bottleneck in information distribution, which remains concentrated in upper management with low cross-functional visibility. This is a bottleneck that slows down decision-making.
For example: if an executive is the only point of contact for metric analysis, and they are only reviewed in weekly—or even monthly, in some cases!—meetings, issues that could have been identified and resolved immediately end up going unnoticed.
6) Departmental data is interconnected
Another key factor is breaking down data silos, which are sets of data isolated from the rest of the company, locked within a single department without interacting with other areas. Cross-communication is essential to make better, data-driven decisions.
For example: if finance has real-time access to sales data or marketing metrics, the response time to market changes decreases, allowing for more targeted campaigns and motivating teams to build new strategies.
7) The company generates value through its data
As mentioned above, not having a strategy or a goal for the data you collect is one of the biggest mistakes companies make when trying to be data-driven. Using this information intelligently involves having a plan to leverage data to create the best customer experience through personalized services and products, delivering exclusive customer support.
Some companies that do this incredibly well are Nubank, Google, iFood, Netflix, and Uber: through the data they have on their users, they deliver experiences and brand touchpoints tailored to each consumer profile. This personalization builds stronger loyalty, increases value, reduces churn, minimizes detractors, and empowers users.
8) Data analysis is already part of the culture!
A truly data-driven company doesn't make decisions based on gut feeling; it generates insights based on real data. This is deeply rooted in the culture: everything is done with a rational purpose to guide decisions, from purchasing tangible resources to the employee journey, marketing campaigns, or sales team budgets.
Contrary to popular belief, having this culture does not eliminate creative thinking or processes within organizations. On the contrary, it aids innovation by providing the tools needed to implement, test, and learn quickly from the process.
Conclusion
Truly data-driven companies have a highly mature relationship with the information they generate. They have clear purposes, strategies focused on generating value through data, high data literacy, and efficient internal communication.
From the outside, it might seem like an intimidating process, but it is transformative for every part of the organization. Because of this, having a strategic partner assisting at every stage of your data-driven journey reduces your business's time-to-value and helps you reach data maturity faster.
Erathos was created with this exact purpose: to reduce the time-to-value of data initiatives to co-create data-driven organizations. Discover our solutions and join the data-driven revolution!