by James Taylor | Jul 8, 2020 | Big Data, Business Intelligence, Decision Management, Machine Learning, Predictive Analytics
Some years ago we did some research on the landscape of analytics capabilities. The research looked at the increasingly broad portfolio of analytic capabilities available to enterprises – everything from traditional Business Intelligence (BI) capabilities like...
by James Taylor | Feb 26, 2020 | AI, Decision Automation, Decision Management, Decision Modeling, Machine Learning, Predictive Analytics
The International Institute for Analytics (I’m a faculty member) recently hosted me for a webinar on Digital Decisioning: Driving Business Value from Advanced Analytics, Machine Learning and AI. In the webinar I discussed the opportunities and challenges of...
by DMS Marketing | Dec 18, 2019 | AI, Decision Modeling, Machine Learning, Predictive Analytics
As we approach the end of the year, our friends over at the International Institute for Analytics (IIA) are re-tweeting some of their best content. One post in particular caught our eye – What’s Your Deployment Score? This is a great piece by Tom Davenport (who...
by James Taylor | Apr 23, 2019 | Business Intelligence, Business Re-Design, Business Rules, Insurance, Predictive Analytics
In February, we published a blog post on “Using Technology to Add Value in Insurance”. In that post, I referenced Matt Josefowticz’s article – Technology May be the Answer for Insurers, but What Was the Question?, in which he states there are only three levers of...
by James Taylor | Apr 15, 2019 | Business Intelligence, Decision Management, Digital Business, Insurance, Predictive Analytics
In February, we published a blog post on “Using Technology to Add Value in Insurance.” In that post, I referenced Matt Josefowticz’s recent article – Technology May be the Answer for Insurers, but What Was the Question?, in which he argues that there are only three...
by James Taylor | Apr 2, 2019 | AI, Business Intelligence, Decision Management, Machine Learning, Predictive Analytics, Strategy
Many speakers on predictive analytics, machine learning (ML) and AI talk about the need to allow data science teams to fail. Without failure, without a willingness to fail sometimes, it’s very hard to build a successful data science program. This is true and often a...
