While the necessity to embed AI into the business is clear, the road to get there isn’t. One question many data science leaders wrestle with is how to organize data science teams to achieve the greatest impact.
In our conversations with nearly a dozen industry leaders building model-driven businesses, we found that there’s no one-size-fits-all answer. But there are a set of practices that leaders use to successfully:
Ultimately, these leaders demonstrate that regardless of how you organize data science, you need a strategy for scale and a path to get there quickly. Those lacking one will fall behind and likely struggle to deliver business impact.
In this report, we break down best practices across all three areas (discipline, process, technology) that these leaders of high-performing global data science teams shared with us. Whether you’re early in your journey or well underway and seeking to strengthen the impact of existing efforts, their insights can help you chart the right course for your organization.