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Posts Tagged: Predictive Analytics
Triple Threat: A Trio of Decision Modeling Tales of Terror

Triple Threat: A Trio of Decision Modeling Tales of Terror

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...

Decide to Decide Digitally: New Forrester Research

Decide to Decide Digitally: New Forrester Research

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...

Three Steps to Boost Your Deployment Score

Three Steps to Boost Your Deployment Score

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...

Using Technology to Better Manage Risk in Insurance

Using Technology to Better Manage Risk in Insurance

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...

Using Technology to Grow Relationship Value in Insurance

Using Technology to Grow Relationship Value in Insurance

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...

What is an Acceptable Analytic Failure?

What is an Acceptable Analytic Failure?

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.

Using Technology to Add Value in Insurance

Using Technology to Add Value in Insurance

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...

Five Reasons to Fire Your Rules Consultant

Five Reasons to Fire Your Rules Consultant

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...

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