FEATURE
In addition, the developments of corporate strategy which depend on data are now guided by fragmented perceptions, politically convenient discourses or generic benchmarks, almost always detached from internal reality.
For this reason, the data management assessment should preferably be carried out at the beginning of the Data Management Program, serving as a basis for any structural decision, relevant investment or prioritisation of initiatives. The same reasoning applies to organisations that intend to advance in the use of Artificial Intelligence in a structured and sustainable way. There is no point in discussing AI, scaling models or automating decisions without a clear understanding of real maturity in data.
In addition, the assessment is not limited to the initial moment of the journey. Whenever the organisation needs an objective reading of its current situation, whether to review directions, correct deviations, redefine priorities or plan the evolution of the AI program and initiatives for the coming years, a new evaluation becomes not only recommended but necessary.
Data and AI programs are dynamic and the absence of periodic diagnoses turns strategic decisions into bets, especially in contexts of growth, Digital Transformation, regulatory changes or increased analytical complexity.
A serious assessment in data management is a structured process which confronts the reality
The data management assessment should be the natural starting point of this process.
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