Urgency around adopting advanced and predictive analytics drops slightly
The importance placed by organizations on advanced and predictive analytics has slightly declined over the past two years, according to a new study from Dresden Advisory Services. Despite that, the technology still remains an important topic to the majority of firms.
Participants in the “Advanced and Predictive Analytics Market Study” expressed interest in a broad range of feature requirements, with “regression models, textbook statistic functions and clustering seen as the most important user features/functions,” the study says. “The greatest early adopters of advanced and predictive analytics within the organization are BI experts, business analysts and statisticians and data scientists.”
Information Management spoke with Howard Dresner, chief research officer at the research firm, about the study and its meaning for data professionals.
Information Management: What are the key findings of your study?
Howard Dresner: Advanced and predictive analytics tools tend to cater to data scientists, statisticians and analysts versus data professionals (e.g., IT). That said a significant feature set for APA tools revolves around data preparation. In particular set operations (joins, etc.) de-duping of data and complex filtering are few key features.
IM: How do this year's findings most differ from, or reinforce, key trends that you identified in your last report?
Dresner: APA remains an extremely important topic within our community of respondents. However, adoption is still limited (23 percent) and urgency appears to have decreased somewhat year-over-year.
IM: How widely are advanced and predictive analytics being used today, and how do organizations feel about the results they are getting with their deployments?
Dresner: Adoption of advanced and predictive analytics tools is small but growing with users tending towards professional statisticians, data scientists and business intelligence professionals. As for success, that’s unclear. However, organizations that have been successful with business intelligence are more likely to adopt APA than their less successful counterparts.
IM: What would organizations most like to be able to do with advanced and predictive analytics that they still can't quite do?
Dresner: The study doesn’t attempt to answer that question. However, I suspect that be able to predict future events with greater fidelity would be at the top of the list.
IM: How good or bad a job do organizations typically do at using advanced and predictive analytics to improve business decision-making?
Dresner: With 77 percent of organizations on the sidelines, I would say most aren’t doing a good job at all. For the 23 percent that have adopted, we don’t have specific data regarding success. However, I would suspect that it is similar to success with BI – which is around 33 percent for complete success and 50 percent for partial success.