What is Data-Driven Organization?

Today, many companies are trying to become data-driven and thus progress. But what is a data-driven organization? Becoming data-centric is more than just installing the right tools and programs.

To become data-oriented, data analysis should be considered part of the organization’s strategy. On the other hand, the way of thinking of the organization should be changed and culture should be implemented in this context.

As a short answer to the question of what is a data-driven organization? it can be said that a data-driven organization places data and analytics in its business strategy. This type of organization differentiates itself from the competition by focusing on the optimal placement of data in daily operations.

What is Data-Driven Organization?

A data-driven organization is an organization that is not only aware of the benefits of collecting raw data but also knows that decisions cannot be made using raw data alone. Rather, being truly data-driven requires digging deeper into the data collected, refining it, and finding ways to use the insights extracted from the big data to grow and increase profitability.

This means that such type of organization uses appropriate types of data whenever needed and in a variety of ways, including observing customer behavior, analyzing demographic data, collecting survey responses, etc.

Becoming a data-driven business isn’t always easy, and there are likely to be obstacles along the way. This is because data and technology alone do not make an organization more successful. This requires a change of mentality and efforts of the leadership and employees.

Characteristics Data-Driven Organization

In data-driven management, the basis of decision-making and planning is not based on beliefs but based on evidence and data. Being data-driven means that progress in an activity is accomplished by data rather than by internalizing personal experience.

A data-driven organization has the following characteristics:

  • It considers data as its strategic asset.
  • Its different organizational layers (front office and back office) have been datafication.
  • The data-driven decision-making process is ongoing at all its management levels.
  • A data-driven culture is promoted in it.
  • It has a transparent data strategy.
  • It uses data analysis for continuous improvement and innovation in its products, services, and processes.
  • Considers data flow management as a strategic priority.

Benefits of a Data-Driven Organization

Unlike traditional companies, data-driven organizations do not grow linearly, but grow exponentially. Just look at the dramatic growth of companies like Amazon and Google, which have built their entire business models around the exploration and exploitation of information.

What these companies have in common is their data-driven approach that goes beyond operational excellence? This requires them to embed data and analytics into everyday business processes and to think beyond company walls to create meaningful collaborations.

To become a data-driven organization, you must aim to create a data culture. By doing this, you will solve some of the most dubious business problems, such as customer acquisition and retention, focused and effective marketing, product innovation and development, quality control and assurance, and more. You will also gain a competitive advantage for near and long-term success.

 

data-driven organization examples

How Do Create a Data-Driven Organization?

Being data-driven does not only mean collecting data and analyzing them. A data-driven organization is an organization that uses the results of data analysis to make decisions and policies. So you might be wondering how we can turn our organization into a data-driven organization. Here are 4 ways to become a data-driven organization:

1- Create a Mechanism to Collect Data

A data-driven organization should always be collecting data that will help improve its performance. Because the profitability of any business depends on the number of its customers. In order to recognize and attract these customers, you need to collect data about them.

For this, you will need specialized forces or use systems that collect and present data. You can hire them or train your organization’s human resources in order to obtain expert personnel. Either way, you need to invest in your IT and human resources.

2- Make Your Business Decisions Based on Data

A truly data-driven organization connects different data and their results and defines new and creative ways for the organization. For example, a data-driven organization uses various data obtained from CRM software, advertising feedback data, user behavior when using products, survey data, etc. to make decisions about the production and development of its products.

3- Look For Reliable Data

One of the requirements of becoming a data-driven organization is the reliability of the data used. Poor quality data destroys the work results of everyone in the organization. Therefore, when collecting data and analyzing them, attention should be paid to their quality.

Data-driven organizations receive a variety of data from a variety of sources. They review the data as they collect it and check its sources to ensure the quality of the data. They also use data quality control teams or tools and control metadata.

4- Use Specialized Data Software

A data-driven organization uses multiple software and tools to collect and analyze data. These softwares can include artificial intelligence, machine learning, management dashboards, business automation, analytics tools, and report generators.

These softwares help to automate the data collection and analysis process and increase its speed. On the other hand, they help businesses to have a better understanding of the results of data analysis.

Data-Driven Organization Structure

A data-driven organization structure is consist of five levels. These levels must be necessary to create a data-driven organization structure.

Data-Driven Organization structure

Data Resistance Level

Error sentence: We used to do these things all the time and it’s nothing new!

The reason why organizations face the stage of data resistance:

  • Fear: Worrying about increasing the informational and functional transparency of employees and the organization
  • Excuse: Data may not uncover hidden performance challenges.
  • Fear: Data may highlight politically difficult individual contributions.
  • Afraid: It is possible for the data to suppress the brand and its message.
  • Fear: It is possible for the data to show the organization as an organization with an uncoordinated strategy.

Passing the stage of resistance to data is usually an entrepreneurial effort from within, i.e. individuals/organizational units who need to improve efficiency in their domain start using data without an organizational mandate.

Data-Aware Level

A data-aware organization is aware of the existence of its data within its organizational boundaries and knows that these data have implicit and hidden value for it, even if this value has not been revealed until today.

Organizations at this level of maturity focus on data collection and are often aware of the potential value of data through the following systems;

  • Web analysis
  • Social media analysis
  • Automation of sales forces/customer relationship management
  • ERP systems
  • Accounting and financial planning

The answers to the following questions are important for a data-aware organization:

Q1: What’s in the data?
Q2: What wealth is likely to lie within the data?

Data-Driven Level

The focus at this level is on extracting any kind of value from the data. It, therefore, emphasizes data analysis and what happened within the data, i.e. descriptive reports on whether:

Q1: What does the data say?
Q2: What happened in the past?

Some common actions that organizations at this maturity level take:

  • Data storage and storage
  • Data analysis
  • Data extraction, transformation, and loading (ETL)
  • Cloud and on-demand computing

An organization that is at this level of maturity still does not use data at a strategic level but uses data and their analysis at a tactical level.

Level of Recognition With Data

An organization that is at this level of maturity knows that data can be considered a strategic asset. In order to benefit and develop the strategic value of data, these organizations continue to invest in data and their analysis to move from answering “what” and “why” to reaching “insights” answers.

Q1: Why did our sales go down in the last three months of the year?
Q2: Why do less customers buy our products?
Q3: Why did person A do the work but person B did not?
Q4: At this level, the focus is on insight.

Data-Centric Level

A data-driven organization is realized when the organization has moved beyond the level of purely internal insight into “what happened” and “why it happened”. A data-driven organization has reached the question that well! Now that we have reached the above insights, what should we do with them?

This question is the driving force behind becoming data-driven. The organization uses data, analytics, and insights to answer the question, “What’s next?” combines with each other. This happens through the use of data at every level and every part of the organization. A data-driven organization believes in data as a strategic resource.

Challenges of Data-Driven Organization

After answering the question of what is a data-driven organization, we should be able to recognize the challenges ahead. Below are some of them.

Privacy Policy

The rise of data-driven organizations will ultimately create a more transparent world and increase trust between businesses and the marketplace. However, the risks of invasion of privacy, market manipulation and monopolies have dominated the news for some time. For this reason, data-driven organizations must have a deep knowledge of new laws such as GDPR to avoid severe fines and sanctions or even losing their license to operate.

Continuous Simplistic Thinking

While most companies agree that data should be at the heart of everything they do. The majority lack a comprehensive, enterprise-wide strategy and still keep information wired. In fact, for an organization to be data-driven, it must live by the principle that data sharing is a positive collective game.

Lack of Data Integrity

Most companies already have enough data to make informed decisions. But much of this information is mismanaged and misused. In other words, there is a clear need for better data management.

Having the Right Skills

According to a study by Gartner, companies are struggling to meet their data skills needs. This is more than just crunching numbers and fine art in data science. Finding people who understand the company and also have deep technical knowledge is not an easy task.

Identifying the Right Technology

Finally, due to the multitude of data-driven solutions, many companies today struggle to find the right one. Identifying the best technologies and successfully implementing them remains one of the most important challenges on the road to data-centric greatness.

Conclusion

After understanding the answer to the question of what is a data-driven organization, it is important that you can follow the basic principles and provide a data-driven environment with comprehensive data analysis for your organization. On the other hand, you need to update your business model based on data and provide methods for continuous optimization of your organization. In this way, you can use the full potential of your data.

Final Words

Hope you understand the topic completely. If you still have any questions write us in the comment section. we will answer you very soon. Do share with your friends if you like this. Thanks.

 

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