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  • Writer's pictureAnantaya Pornwichianwong

How to become a data-driven Organization



Transforming into a data-driven organization has become a necessity for all organizations in an age where data is invaluable and is a life-and-death factor that decides business profit and loss. But before we get to know those steps, let's see what does it really mean to be a data-driven organization?


What most people think of a data-driven organization is often associated with cutting-edge data analysis systems and dashboards with real-time access to data and the use of AI and machine learning as the main tools.


However, that is just a part of being a data-driven organization. The true meaning of being a data-driven organization is that all employees acknowledge the importance of data, embrace the data-driven culture, and know how to use it efficiently. The data usage policy is applied across the organization. The data is accessible by all teams, and not limited to the data analyst only. The most important quality of being a data-driven organization is that every person in the organization works on a data-based basis, whether it is finding answers or making decisions. They must draw their conclusion by having accurate data backing up.


Being a data-driven organization is not just the application of many cutting-edge data technologies. The concept of data-driven must be deeply rooted in the culture and embraced across the organization. Data must be utilized by every team in every process of their operations.


If you are one of those organizations that haven't started transforming into being data-driven yet, because you still don't know how to begin, or if you feel that your organization or team hasn't really embraced the culture of data, today, Sertis would like to introduce 5 easy steps to transforming your organization into a truly data-driven one. Start today. It is never too late to be data-driven.



1. Design the appropriate key metrics


Defining appropriate performance indicators that are aligned with the main goals of the organization help guide employees on what to do, which key responsibilities they should invest time in, and how to use the data on hand for maximum efficiency.


Having comprehensive and accessible data on hand is great, but having too many KPIs or disconnected goals cause employees to get lost and not know which data to use. Setting clear, actionable, appropriate amounts of goals and KPIs will encourage employees to use data more efficiently and eventually enable organizations to transform to be truly data-driven.


2. Create a data-sharing culture in the organization


Sometimes there may be situations where each team works separately and keeps their data in silos without exchanging data or updating progress with other teams. A data-driven organization should create a culture of collaboration and exchange of data. Also, data democratization should be applied to make employees feel confident and comfortable accessing the data they need without obstacles.



3. Encourage cooperation from all parties


To successfully transform into a data-driven organization requires collaboration from all teams, not just the team that is responsible for the data. One of the best practices is to hold meetings to provide updates for each team on the changes at different stages. Explain to each team what their goals are, which phases they are in, how the transformation affects their work, and what has changed in their daily tasks. We should initiate the meeting and encourage people to ask questions openly to create cooperation and transparency in the transformation.


4. Connect scattered data into one place


The next step in transforming into a fully data-driven organization is organizing data and connecting data scattered throughout the organization to be centralized in one place. In one organization, there are various teams, e.g., a marketing team, a sales team, or an IT team, with different working styles and with their own data format and storage. Despite these differences, in the same organization with the same ultimate goal, those data will definitely be linked. But the problem is that these data are often disconnected and located in scattered places, which is why we cannot see the whole picture and the real answer in the data.


The data-driven transformation includes gathering all the data from all teams in the organization and organizing, transforming, and storing them in one, centralized storage. In this step, we need to use the pipeline that allows us to prepare and organize our data automatically. The process starts with data mapping to create a unified map of data from different sources, data integration to connect data from multiple sources, and data cleaning to ensure consistency and accuracy. Data normalization and quality assurance are also needed to monitor future inputting and storing of data to avoid errors.



5. Implement an accessible and efficient data analytics platform


Sometimes employees may not be able to interpret and analyze data on their own and understand what data wants to convey, and how they should proceed based on the data. In addition to having a centralized database, the organization must have a data analytics platform to help accurately and comprehensively analyze data with a dashboard that is easy to understand and accessible to every team.


Furthermore, data visualization comes into play by displaying the results in the form of graphs or charts in a real-time dashboard that employees can access anywhere, anytime. This is the heart of data utilization. It helps us easily and clearly see what the data is conveying, see which direction the strategy should be placed, and make informed decisions. This will allow organizations to make use of the data and transform itself into a truly data-driven one.


Start with us at Sertis. We are Thailand's leading data solutions provider, with a team of experts from various fields working together to create customized solutions for clients, tailored to their unique business problems. Start from building a data infrastructure from scratch with data preparation solutions to building a platform that automatically manages and analyzes data with data processing solutions, and building dashboards that show real-time results with data analytics and data visualization platforms. Besides, let's unlock the full potential of intelligent and automated data analytics with AI and machine learning solutions. We are here to provide you with a consultation at every step to truly transform your organization into a data-driven one.


Learn more about solutions from Sertis: https://www.sertiscorp.com/services

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