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New Survey Finds Model-Driven Culture Is Critical for Data Science Success

New Survey Finds Model-Driven Culture Is Critical for Data Science Success

While companies continue to realize the importance of data science and its ability to positively impact revenue, scaling it across an organization continues to be a challenge. A new survey released today reveals a new leading factor to success — creating a positive, model-driven business culture among employees. This insight is one of the findings from a survey of data and analytics professionals sponsored by Domino Data Lab, provider of the leading open enterprise data science management platform trusted by over 20% of the Fortune 100.

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Conducted by DataIQ, the leading membership-based forum for connecting, educating and supporting the data and analytics community, the survey curated a research panel of influential data and analytics professionals across a wide range of industry sectors and company sizes in the UK. Seniority ranged from senior managers and heads of department to global directors and chief officers.

The survey found that one in four businesses1 expect data science to impact topline revenue by more than 11 percent. However, the survey indicates a challenge with company culture, suggesting a positive, model-driven culture is difficult to build and still needs to be developed. 39 percent want a clearer definition of needs from stakeholders, 38 percent recognize the need to train business users in data science concepts, and 32 percent identify the need for a more positive relationship with stakeholders.

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“Many companies begin their data science journey by hiring a few data scientists, but overlook the importance of building a model-driven culture that aligns with business users and their needs,” said Nick Elprin, CEO of Domino Data Lab. “This survey highlights the impact that the lack of positive culture can have on identifying proper use cases, setting appropriate expectations, and ultimately delivering a measurable impact to the business. Understanding these challenges is important for companies at all stages of maturity so they can course correct and successfully scale data science operations across their organizations.”

Additionally, 40 percent of respondents indicate that weak understanding or support for data science in business is one of their biggest challenges. One out of three organizations (34%) indicate that conflict between data science and IT is one of their biggest challenges. Even companies that describe themselves at the “advanced” and “reaching maturity” levels in terms of their adoption of data science and analytics are not free of culture conflict. For both of these groups, half (52 percent and 50 percent of both groups respectively) indicate that conflict between data science and IT is their biggest challenge.

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