Join Decision Management Solutions and IBM on October 20th for a technical deep dive into the innovative Mayflower Project. Learn how to harness AI and ML algorithms to positively impact your business outcomes. This webinar will show you how. During this session,...
Like many enterprises, you’ve likely made a hefty investment in analytic technology—from interactive dashboards and advanced visualization tools to data mining, predictive analytics, machine learning (ML), and artificial intelligence (AI). But, now that you have all...
By Gagan Saxena, VP Solutions and a Principal Consultant, Decision Management Solutions Decision modeling can be a “good-enough” representation of business problems, providing adequate information for automating decisions. And even if there may be a good reason...
Eric Siegel and I had a great discussion about doing Machine Learning BACKWARDS recently - you can watch the recording below or on our YouTube Channel. Eric, if you don't know, is the founder of Predictive Analytics World, a leading consultant, and author of...
Mike Gualtieri and Boris Evelson of Forrester recently published a great new paper Introducing AI-Powered, Human-Controlled Digital Decisioning Platforms (subscription or payment required) and you should get access to this paper and read it now. It's got some great...
Everyone it seems wants to be an analytic enterprise. But what does it mean to be an analytic enterprise? An analytic enterprise applies analytics deeply and broadly. It uses analytics to solve its most critical run-the-business problems. It uses increasingly advanced...
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...
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 Machine...
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 wrote...
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...
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...
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 barrier for companies that find it hard to accept that not all analytics initiatives succeed.
Nancy Casbarro and Deb Zawisa of Novarico recently published a new paper on Data Science in Insurance: Expansion and Key Issues subscription required) that was summarized in this nice little article on Dig-in 3 challenges facing insurers in data science...
Matt Josefowticz wrote a great piece recently - Technology May be the Answer for Insurers, but What Was the Question? In this he argues that there are only three levers of value in insurance: 1. Sell More 2. Manage Risk Better (aka underwriting and...
We do a lot of decision management projects, helping clients adopt the technologies and approaches they need to succeed with digital decisioning and decision automation. One of the key technologies for these types of projects is a Business Rules Management System...