How Businesses Benefit From Self-Service Analytics- Valutrics

CIOs and their tech teams could better support line-of-business units by enabling what’s called “self-service” data analytics, according to a recent survey from Alteryx and Harvard Business Review. The accompanying report, titled “The Untapped Power of Self-Service Data Analytics,” indicates that self-service analytics is helping analysts connect to and cleanse data from data warehouses, cloud apps and other sources in a repeatable manner, while paving the way for deeper and more quickly obtained insights. Through 2020, spending on self-service and related data tools will grow 2.5 times faster than spending on traditional data tools, according to industry research. Yet, overall adoption appears to be in the early stages, as the vast majority of survey respondents admit that they’re not particularly aware of these products. For now, they depend on the IT department or an internal data analytics group for analytics-based decision-making. By helping the business side adopt a “DIY” approach here, CIOs can boost the speed, ease-of-use and quality of their organization’s analytics efforts. “Business leaders are demanding more agile and flexible insight to speed and improve the decision-making process,” according to an introduction in the report written by Rick Schultz, senior vice president of marketing at Alteryx. “Today’s business environment is driving a change … in the supporting technology itself. Self-service data analytics is changing the way organizations are able to operate and make decisions.” Nearly 645 Harvard Business Review readers, many of them being professionals or managers in operations, sales/marketing and strategic planning, took part in the research.

Wide Deployment

60% of survey respondents use some form of data analytics to generate business decision-making insights, and more than four of five expect these tools to be “extremely” important to them in the next two years.

Departmental Dependency

62% said they typically rely on others, such as IT or a data analytics group within their organization, for decision-making analytics.

Underwhelming Effort

Only 19% are “very” or “extremely” satisfied with the their IT department/analytics group’s ability to compile information from inside or outside their organization, and the same percentage feel the same way about how quickly they can get this information. Meanwhile, just three of 10 are very or extremely satisfied with the quality of work on the part of the IT department/data analytics group.

Make-Do Deliverables, Part I

79% said ease-of-use in their analytics tools is either “very” or “extremely” important in their decision-making, but only 35% said their current solutions are “very good” or “excellent” at this.

Make-Do Deliverables, Part II

75% said the speed of their tools is very or extremely important in their decision-making, but just 32% said their current products are very good or excellent at this.

Tool Time: Negative Perspective

57% said they’re deploying data visualization products for analytics, but just 37% said they’re highly satisfied with these products.

Tool Time: Integration Issue

42% said they take advantage of data integration technology, but only 25% said they’re highly satisfied with the outcomes so far.

Tool Time: Improper Blend

39% said they’re using data prep/blending solutions, but only 29% are highly satisfied with these products.