What is Data Maturity, and why is it important?
Data Maturity is an essential concept for any organisation striving to become data-driven. It measures how effectively an organisation uses data to achieve its goals. But it’s about more than just the amount of data you have. It combines how you manage, interpret and apply data to generate valuable insights.
According to the Data Maturity Model described in the white paper “Improve Your Data Maturity Level from Starter to Expert,” there are five levels of data maturity. These range from Starters who are just beginning to collect and use data to Experts who use data to drive their business strategies.
The Role of Data Maturity in Business Intelligence
In the world of Business Intelligence, Data Maturity is critical. Data maturity can give your organisation a competitive advantage, allowing you to make faster and more informed decisions. It helps you spot patterns and trends, make your business processes more efficient, and comply with regulatory data management requirements.
How do you increase Data Maturity in your organisation?
Want to transform your organisation into a data-driven powerhouse? Here are a few steps you can follow:
1. Establish clear data goals and strategies.
It is essential to know what you want to achieve with your data. This will help you develop a focused data strategy that aligns with your business goals.
2. Invest in the right data tools.
Whether it’s data collection, storage, analysis or visualisation, the right tools can make all the difference in how effectively you use data.
3. Develop your staff’s data skills.
People are crucial to success in data-driven work. Invest in training and development to ensure your team has the skills to extract valuable insights from data.
4. Implement effective data governance.
Good data governance ensures your data is high quality, secure and reliable. This includes issues such as privacy, data quality and data security.
Data as part of the corporate culture
No matter how well the tools, skills and goals are set, if the team itself is not “with it,” slight improvement will be noticeable. This often starts with “feeding” the data sources. If customer data in a CRM system is consistently entered appropriately, correctly or incompletely, then only the employee who entered it will know precisely what is happening.
Often, the cause is more than just a lack of knowledge. Motivation can also play a role, especially if the extra effort is not considered valuable. If the people who have to deal with the data daily actively get to work with it, the added value of high data quality will soon become apparent. Therefore, it is also essential to involve management and all users of this data.
The Data Maturity Model
The Data Maturity Model (DMM) originates from the Capability Maturity Model, initially developed by the SEI (Software Engineering Institute). This is a sub-branch of the U.S. Department of Defense. To be allowed to create software for the Department of Defense, it was essential to know how likely it was that commitments made would be met and that projects would be delivered on time. By assessing how “mature” a company was in mainly defined areas, they could make a better choice on the subcontractors they hired.
The Path to Higher Data Maturity
Improving your data maturity is an ongoing process but a journey worth taking. By increasing your data maturity, your organisation can grow, innovate and foster a culture of data-driven decision-making. Want to take a deeper dive into how to increase your data maturity? Then check out the white paper “Improve Your Data Maturity Level from Starter to Expert.“
By paying attention to Data Maturity, you are taking an essential step toward becoming a more data-driven and successful organisation. Want to learn more about how your company can become more data-mature? Then contact our experts.
