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Once viewed as a byproduct of operations, data is now one of the supreme drivers of business value. The volumes of data generated are continuously growing at a rapid pace across structured, semi-structured, and unstructured data types that businesses are now able to store and need to analyze.

Those organizations that are not able to manage the complexity of the collection and analysis of the data may suffer consequences that can range from missed opportunities to the incur of higher costs, the difficulty meeting the growing regulatory requirements on data, and, ultimately, considerable exposure to competition. For this reason, in the latest years companies have been increasingly recognizing the urgency of improving data management to support their business objectives and avoid suffering the previously mentioned problems.

As for data management, companies (351 CDOs interviewed in 14 industries all over the world) have been prioritizing different objectives, the 4 main ones are the following:

1. Improving data management quality and processing (48%), that represents the key to enabling growth-oriented efforts
2. Increasing the adoption of cloud platforms (43%)
3. Enhancing data analytics (43%)
4. Expanding the application of Machine Learning (42%)

The last three mentioned, if met, will provide data teams with additional capacity, power, scale to quickly tap new sales and service opportunities and support new data product development. They also help work towards improving operational efficiency.

Concluding, data management-related strategy should be aligned with each organization’s business objectives. In fact, according to Don Vu, chief data officer of Northwestern Mutual, alignment of data and business strategy has become much tighter at many companies as Chief Data Officers have exerted their influence, and data responsibilities is distributed within all the organizational departments.