Organizations that prioritize data-driven activities and strategies often reap the rewards of their maturity. Data management maturity, DataOps maturity, geography, company size, and other variables can all influence how a company behaves in data-related pursuits. In general, both higher data management maturity and higher DataOps maturity tend to be linked to higher reported rates of success or adoption in other data-driven activities, for example, 75% of those with more mature DataOps practices report having a chief data officer, versus only 54% of those with less mature DataOps practices.
Systematic data management investment and effort are associated with outsized returns on data-driven initiatives. As digital maturity increases, often so do indications of success in data-driven activities. However, the relationship is not perfectly linear. Organizations that report a “proficient” (but not yet exceptional) level of data management maturity often dip in reported confidence and performance, likely because they are mature enough to be aware of their goals and challenges but may be grappling with the IT complexity resulting from their efforts. This temporary “hump” emphasizes the need to consistently pursue further maturity and data operationalization to move past the awkward adolescent phase.
DataOps responsibilities are typically distributed. DataOps is often characterized by an “all hands on deck” approach involving stakeholders across data and IT functions, and sometimes other business units. Beyond core data and IT groups, 59% of respondents report involvement of business/data analysts as well. The frequent involvement of individual contributor roles, such as analysts, suggest a collaborative or even “crowdsources” element to DataOps practices in many organizations regardless of their data management or DataOps maturity, though organizations with “developing” data management maturity tend to have slightly lower participation from these specific roles.
