Machine Learning

The Basics of Operationalizing Your Investment in Machine Learning

by James Taylor, CEO Decision Management Solutions “Enterprises waste time and money on unactionable analytics.1” This quote from Forrester succinctly states why machine learning (ML) projects often never progress beyond the pilot stage—a common form of “purgatory” and a topic I presented recently at this year’s Machine Learning Week. Why many ML projects disappoint ML […]

Make Your Investment in Analytic Technology Pay Off With Decision Requirements Modeling

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 these wonderful tools at your disposal, have you stepped back and assessed whether they have truly provided value and […]

Avoid a Shipwreck by Incorporating Business Rules Into Your AI Decision-Making Projects

by James Taylor CEO, Decision Management Solutions In a previous blog, we introduced you to the Mayflower 400 autonomous ship, the first autonomous seafaring vessel in the world, developed by ProMare in partnership with IBM and other organizations. One of the big takeaways from the Mayflower project that can be applied to business is the […]

Why So Many Data Science Projects Fail to Deliver

by James Taylor, CEO, Decision Management Solutions If you are working in data science, you may be frustrated with the progress and ROI of your data science and artificial intelligence projects. The struggle is real, and you’re certainly not alone. Recent research conducted by the Alliance Manchester Business School at the University of Manchester and Ivey […]

James Taylor on IBM ExpertTV

Recently James Taylor, CEO of Decision Management Solutions, was featured on the IBM ExpertTV series “Two Questions About Automation.” Here’s a run down of the segment and the questions he answered. Host David Jenness asked James, “Why are companies struggling with AI and ML?” According to James, there are three main root causes. The first […]

Top Three Items for Your 2021 To-Do List

Our world looks very different today than it did nine months ago, and so does your business. As one of the most turbulent years in recent history comes to a close, it’s critical in these uncertain times to prepare for the future. With the pandemic still in full play and economic uncertainty across nearly every […]

Learn How Machine Learning Can Deliver True Business Value

Sign up for our 2021 Machine Learning Week workshop by James Taylor, CEO, Decision Management Solutions Enterprises today are eager to apply machine learning to improve their operations. But how do they ensure that it truly serves their business operations in the most optimal way? After all, the end goal is to achieve better business […]

Machine Learning BACKWARDS – A Conversation with Eric Siegel

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 “Predictive Analytics“. You can also check out Eric’s new Coursera class. This […]

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 content and recommendations and is well worth your time and money.  It follows on from previous […]

Technology Transformation Antipatterns and how they derail decisioning success

Sven Blumberg, Thomas Delaet, and Kartikeya Swami of McKinsey Digital published a great paper recently – Ten ‘antipatterns’ that are derailing technology transformations. Technology has a crucial role in enabling this faster and more flexible approach. In our experience, however, technology does not get sufficient attention on the executive agenda. This is a serious flaw […]