Data Maturity: what is it and how can you use it to your company's advantage?

What is data maturity?

Data maturity is defined as an organisation's ability to manage and use data throughout its operations effectively. A data mature organisation can collect, manage and analyse data to extract meaningful insights which help the business grow.

A popular example would be if a business is leveraging predictive and prescriptive analytics, a data-mature organisation is about to not only anticipate what will happen in the future but have a clear understanding of what actions to take. 

Across an organisation it can have many requirements, for example, it can predict which candidate will be the best fit for a new job opening or which suppliers are most suited for a particular product line of parts. 

How can you improve your data maturity?

There are many approaches organisations may decide to take in order to increase their data’s maturity. The most important aspect to consider when looking at the maturity of your data is data management.

In short, the better your data management is, the better your data maturity will be.

However, simply improving your data management is not an easy task, especially when working within larger corporations. It’s a process that needs to be broken down into smaller pieces, that add to the bigger picture. You can improve various aspects of your data management by adopting some of these common processes:

       2. Set clear objectives and goals – Define specific and measurable objectives for improving data maturity. Important for organisations to benchmark current maturity levels and acknowledge/action areas of improvement as the data maturity level progresses.

       3. Invest in technology – Evaluation and investment in modern data management technologies that support data storage, processing and analysis. This can include Data Warehouses, Data Lakes and advanced analytics tools. It is crucial to continuously invest in technology ensuring a competitive edge and long-term value for the organisation.

       4. Monitor and measure progress – Establish KPIs and regularly monitor progress in terms of the impact of data management initiatives. A key activity that all organisations should be doing is to know where the organisation has come from in terms of data maturity, and its current level and to know the requirements to get to this point.

       5. Document best practices – Ensure best practices are well documented across the business, this is very important as this provides the footprint for an organisation to ensure its data maturity has long-term sustainability.

"In order to take advantage of the potential value of AI and analytics, businesses need a good level of data maturity. This means: