Enterprises back data science but don't have the skills and tools to make it work
Enterprises are overwhelmingly counting on data science as a key to their long-term success, but flawed investments in people, processes and tools are leading companies to fail in their best efforts to develop, deploy, monitor, and manage models.
New research from Domino Data Lab shows that while 71 percent of data executives say their company leadership expects revenue growth from their investment in data science, 48 percent say their company has not invested enough to meet those expectations.
And yet 82 percent of those polled say their employers have no trouble pouring money into investments that yield only short-term results. 68 percent report that it's difficult to get models into production to impact business decisions, and 37 percent say it's very to extremely difficult to do so.
Also 39 percent say a top obstacle to data science having a greater impact are the inconsistent standards and processes found throughout their organization.
Lack of skills and poor tools are a problem too, 48 percent of data executives complain of inadequate data skills among employees, or not being able to hire enough talent to scale data science in the first place (44 percent). While 37 percent of data science executives name outdated or inadequate tools to build and manage models as a key factor leading to reduced data science impact on the business.
"We found that while executives have enormous expectations for revenue growth from their investments in data science, they are not making investments in the right places to truly unleash the power of data science," says Nick Elprin, CEO and co-founder at Domino Data Lab. "To properly scale data science, companies need to invest in cohesive, sustainable processes to develop, deploy, monitor, and manage models at scale."
The report also introduces the Domino Data Lab Maturity Index: a framework for assessing an organization's data science maturity based on years of working closely with top performing companies.