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6 Steps to Create a Company Data-Driven Culture

Data is the most valuable asset of a company. In recent years, the scale of data collection and analysis investment in all sectors shows the importance of data related business in the future. A recent report from the Economist Intelligence Unit (EIU) shows that:

  • Almost 60% of organisations are already generating revenue from their data and will continue to do so.
  • 83% say data are used to make existing products and services more profitable
  • Only one-third claim to be “very effective” about transparency with customers and how they use their data

Consequently, in order to fully exploit the data advantages, companies are restructuring and creating new positions for a more systematic use of data. This is particularly evident in the growing demand for so-called Data Scientists, who are able to transform data into actionable insight with business value.

Data specialists are indispensable for any business in the digital era. However, we should not centralize the entire data activities of an organization in the hands of a few experts. To reap the full benefits of data, everyone in the company should have the ability to access data and to include data in their daily business.

Data can democratize and multiply knowledge. They are useful for any industry, for any size of business and for employees at every level within an organization. To make all employees to explore their data regularly, however, goes beyond the provision of technology in accessing data; it is rather the efforts to create a data analysis culture in the company.

How to implement the transition to such data culture? You may try the following six basic steps.

1. Give employees access to the data

Creating a culture analysis begins with “empowerment”. Employees are empowered to explore data and answer their own questions. Earlier data analysis was only in the hands of a few specially trained staff. Now companies cannot afford to apply this expert model. CEO and senior management of a company should promote a corporate culture in which the employees themselves can access and use data.

2. Train the brain, not just the computer

To ensure all employees can use data, training is required in most cases. Some of these trainings can be done even through self-study tool; for example, case studies or online videos. Technical training which focuses primarily on dealing with tools and data analysis methods is the important step. However, the attitude and cultural changes are equally important. For example, the data culture can only be created through the development of critical thinking, analytic curiosity and knowledge in relevant areas.

3. Be positive about your concerns

For many managers, such degree of empowerment in their workforce may initially have big concerns, especially when it comes to sensitive data. Here the management teams in the organizations play a decisive role, and this team must lead the company from the mentality of the “need-to-know” principle to the data-driven culture; otherwise, the entire change process will be slowed down. It is therefore important to accept that there are concerns about how to deal with data, and then take steps to make this approach normality.

4. Look for curious and inquisitive

The structure of an analytical culture must also be accompanied by the ongoing recovery and development of talent. Data analytics skills play a key role in this process. But the data user is not necessarily required to have excellent knowledge of the latest technologies in data analytics. What is really important for anyone who works with data rely on only one property – critical thinking. It is therefore advisable to provide the analytical tools to employees to test and arouse their curiosity. Curiosity is independence and it constitutes an essential basis for a data culture.

5. Ignore the gut feeling

In a data-driven culture, employees should be motivated by using data to answer questions, and the company management must focus on data-driven answers initially. Instead of gathering views from middle management, senior executives must demand recommendations that are supported by data. Questions cannot be answered with the words “I think”. Each answer should be accomplished by applying relevant data.

6. Be patient (but not too patient)

The implementation of an analysis culture is a long-term process. Companies to take the first step in this direction until the next year, it will, however, regret that it has not started already.

Conclusion

To develop a real data-driven analysis culture, every aspect must be included of the organization – from the handling of data scientists through training and tools up to the hiring process.

The most important factor is that the data itself is democratized so that all users ask questions and data-based decisions. The outcome of a data-driven corporate culture development really depends on whether the management team of a company actually carries out their executive function to promote this cultural change.

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