As a new generation of business professionals embraces a new generation of technology, the line between people and their tools begins to blur. This shift comes as organizations become flatter and leaner and roles, context and responsibilities become intertwined. These changes have introduced faster and easier ways to bring information to users, in a context that makes it quicker to collaborate, assess and act. Today we see this in the prominent buying patterns for business intelligence and analytics software and an increased focus on the user experience. Almost two-thirds (63%) of participants in our benchmark research on next-generation business intelligence say that usability is the top purchase consideration for business intelligence software. In fact, usability is the driving factor in evaluating and selecting technology across all application and technology areas, according to our benchmark research.
The Personas that Matter the Most in Business Analytics
Topics: Big Data, Data Scientist, Sales Performance, Supply Chain Performance, IT Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, CIO, Customer & Contact Center, Data Management, Financial Performance, Information Applications, Information Management, Workforce Performance, Data
Actuate this week announced BIRT Analytics, and thereby puts itself firmly into supporting a range of business analytics needs from data discovery and visualization to a range of data mining and predictive capabilities that allows itself new avenues of growth. Actuate has long been a staple of large Business Intelligence deployments; in fact the company claims that ActuateOne delivers more insights to more people than all other BI applications combined. This is likely true, given that Actuate is embedded in major consumer applications across industries worldwide. This announcement builds and utilizes its advancements into big data that I already assessed last year that can help it further expand its technology value to business and IT.
Topics: Data Scientist, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, CIO, Financial Performance, Information Applications, Operational Intelligence, Data Discovery, commodity model, Quinterian
A study by the McKinsey Global Institute published earlier this year suggests a coming shortage of more than 140,000 workers with deep analytical skills and a shortage of more than 1.5 million data-literate managers. I’m not sure how the study defined these roles, but I’d guess that those with deep analytic skills are those folks building the complex models, and the data-literate managers are those executives, middle managers and analysts who interpret the results and use the models to help drive business decisions. In other words, businesses are facing two skills gaps – one related to those producing the analytics, the other related to those using them in some type of discovery or review purpose.
Topics: Big Data, Data Scientist, Predictive Analytics, Sales Performance, IT Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Operational Intelligence, Workforce Performance
Research Uncovers Keys to Using Predictive Analytics
As a technology, predictive analytics has existed for years, but adoption has not been widespread among businesses. In our recent benchmark research on business analytics among more than 2,600 organizations, predictive analytics ranked only 10th among technologies they use to generate analytics, and only one in eight of those companies use it. Predictive analytics has been costly to acquire, and while enterprises in a few vertical industries and specific lines of business have been willing to invest large sums in it, they constitute only a fraction of the organizations that could benefit from them. Ventana Research has just completed a benchmark research project to learn about how the organizations that have adopted predictive analytics are using it and to acquire real-world information about their levels of maturity, trends and best practices. In this post I want to share some of the key findings from our research.
Topics: Data Scientist, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, IT Performance, Business Analytics, Business Intelligence, Customer & Contact Center, Workforce Performance
