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Often when talking about digital maturity, or in our case data maturity, it should be noted that comparable metrics between different companies, stakeholders, or ecosystem actors are lacking. It is not always appropriate to even make a comparison, but very often it would be useful to understand what other maturities we are dealing with. Needless to say, it can be difficult for digital pioneers and companies just starting their own data path to benefit from working in the same level of maturity with each other. However, different levels data maturity are not an obstacle to working together but considerably facilitate and speed up cooperation if the level is almost the same.

With a five-step digital maturity framework, it is good to superficially assess one’s own level and perhaps strategically determine key measures and actions to reach a higher level. There are clear differences in the steps of digital maturity, and by honestly looking at your own operations, it is also easier to assess the position of other key players on own industry and the position your company in relation to them. We will use digital maturity model to define data maturity in high level (picture below).

The lowest level in the meter is "Unaware" or "No maturity", which means that the company is at most discussing the possible utilization of data in a fragmented context. The second level, the "Conceptual", involves a situation where a company has identified the usefulness of data use, conducted market analyzes, acquired data expertise, and perhaps utilized data utilization at the management level as one of the strategic guidelines. The third and middle tier is “Defined,” where responsibilities for data making are named, priorities, and metrics are defined to reap business benefits. The second highest step is “Integrated,” which means that in a company, data utilization is integrated into key activities, it is managed on a regular basis, and expertise and resources are utilized throughout the organization. The highest level is "Transformed", which means pioneering and a top player in its field, for whom data is no longer just an opportunity but an integral part of almost everything to do. Data-based operations are involved in decision-making, processes, automation, sales and are naturally included in both speech and activities on daily-basis.

By weighing your own data maturity, you can also set the ambition level correctly. For example, if the data strategy has been in the films of the management team for several years but the maturity has not changed, it may be appropriate to weigh whether the right things are being done and whether we are doing it right.


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