EDITOR’ S QUESTION centralised data science team, with its broad view of the organisation’ s challenges, is more likely to spot these opportunities and adapt solutions from one domain to another. For example, an algorithm that proves successful in optimising marketing campaigns could be adapted to improve inventory management or streamline production processes elsewhere in the business.
• Champions for analytics maturity
Finally, a centralised data science function is best positioned to drive the overall analytic maturity of the organisation. This function can standardise governance, best practices and drive the change management processes, ensuring that data-driven decision-making becomes core to company culture.
Getting on the right side of change
The shift from classic BI to a centralised data science function is not just a structural change; it is a crucial strategy for companies looking to stay ahead of competition that’ s increasingly data-driven.
By centralising data science and enforcing a charter for BI to independently solve key problems of the organisation, companies can tackle complex, crossfunctional problems more effectively, foster talent development, create inter-departmental synergies and drive a culture of continuous improvement and innovation. This evolution sets world-class companies apart from the rest and there’ s no reason your company can’ t unlock the same opportunities. p
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