Only just over one in ten (13%) big businesses are delivering on their data strategy, with most laggards citing ongoing struggles with implementing machine learning and artificial intelligence as the biggest barrier to more informed decisions.
That is the stark conclusion of a new report by MIT Technology Review Insights and Databricks, based on a survey of 351 chief data officers at organisations with sales of $1bn (£720m) or more in annual revenue, including Total, Estée Lauder , McDonald’s, and L’Oréal.
Among the findings was that only a select group of “high achievers” – that will be the 13% then – delivered measurable business results across the enterprise. This group succeeded by paying attention to the foundations of sound data management and architecture, which enabled them to “democratise” data and derive value from AI and machine learning technologies, according to the report.
Every CDO interviewed for the study highlighted the importance to democratising analytics and machine learning capabilities to enable everyone on the business to make more informed business decisions, a factor they said was crucial for a strong data culture.
The respondents also advocated embracing open source standards and data formats.
However, what remains the most significant challenge is the lack of a centralised unit to store and discover machine learning models, 55% of executives said, although 50% are currently evaluating or actively implementing new, potentially cloud-based data platforms.
Organisations’ top data priorities over the next two years fall into three areas: improving data management; enhancing data analytics and machine learning; and expanding the use of all types of enterprise data, including streaming and unstructured data.
Report editor Francesca Fanshawe said: “There are many models an enterprise can adopt, but ultimately the aim should be to create a data architecture that’s simple, flexible, and well-governed.
“Managing data is highly complex and can be a real challenge for organisations. But creating the right architecture is the first step in a huge business transformation.”
Earlier this week, a Gartner report blamed a lack of alignment between AI and machine learning with customer acquisition and retention goals for an ongoing struggle to deliver personalised experiences to customers.
The survey revealed that only 17% of firms are using AI/ML broadly across the marketing function.
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