Many organizations still struggle to turn data into insights
While the majority of organizations understand the value of the information they collect and create, the majority still struggle with turning data into actionable insights.
That is the conclusion of a new study from Interana, which looks at the experiences that organizations are having with big data and analytics in 2017. The study revealed that 70 percent of organizations feel they do not get critical insights from their data or get data into the hands of the right individuals.
The study draws a distinction between an organization being data-driven, in which the organization lets its data guide the decision-making process, and data-informed, in which the organization allows data to act as a check on its intuition.
“The thing that separates great companies from the rest lies in how much of the thinking they do themselves and how much is left to the data,” the study explains.
The good news is that the vast majority of organizations do have an analytics program in place now, with the largest consumers of analytics being product management (cited by 20 percent), engineering and product development (cited by 20 percent) and marketing (cited by 16 percent). But analytics can be found in every department.
In a data-informed organization, business decisions involving data are most often made by marketing (cited by 65 percent), followed by the data analytics team (cited by 63 percent), software and product development (cited by 47 percent) and operations (cited by 47 percent).
Unfortunately, in a data-informed organization only two-thirds (62 percent) say that while everyone understands the important of data, only a select few employees are equipped with the right tools or knowledge to make data-informed decisions. As a result, 75 percent of respondents say that employees at their organization can answer simple analytics on their own but need help with more complex questions, while only seven percent say employees can answer complex questions on their own.
The study also asked respondents to rate analytics tools they use and any pain points associated with them. The most commonly mentioned were lack of flexibility (cited by 43 percent), slow query speeds (cited by 32 percent) complicated or difficult to use interface (cited by 30 percent), amount of coding required to use (cited by 30 percent) and cost (also cited by 30 percent).