analytics

We do a lot of work in insurance and we seem many companies spend heavily automating their claims process. Their intent is to improve their loss ratio – both by reducing losses due to fraud or bad claims and by reducing processing costs. But it often doesn’t make much difference because they are focused on [...]

I was talking to a customer the other day about a particular decisioning problem they have. There’s an operational decision that they take several thousand times a year. Not a transactional one but a pretty high volume one. Sometimes these decisions have a large financial impact but often they have a smaller one. Today the [...]

Over the years, Decision Management Solutions has helped many leading insurance businesses modernize. We’ve helped them radically improve their claims handling, driving high rates of straight through processing with less fraud and less waste. We’ve helped them improve their top line sales numbers with automated cross-sell/up-sell, Next Best Offer or Next Best Action systems. We’ve worked with [...]

I am super-excited to announce that an article I have been working on with Michael Ross has just been published on Harvard Business Review – Managing AI Decision-Making Tools The nature of micro-decisions requires some level of automation, particularly for real-time and higher-volume decisions. Automation is enabled by algorithms (the rules, predictions, constraints, and logic [...]

It’s been a while since I did a product review on the blog, but I recently caught up with the team at Zoot and thought a blog post was in order. Zoot, for those of you who don’t know them, deliver capabilities and services for automated decisioning across the customer credit lifecycle. They’ve been at [...]

Bart de Langhe and Stefano Puntoni recently published a great article in the MIT Sloan Management Review called “Leading With Decision-Driven Data Analytics.” In contrast to so much of the literature that focuses first on data, they focus on decision-making. In fact they go so far as to say that: “Leaders need to make sure [...]

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 [...]

COVID-19 is driving a new normal in which resources must be allocated and managed more dynamically.

Some of our old friends at Gartner have just published some great research on Decision Management. Specifically they have extended their work on Decision Management Suites (blogged about here) and focused on How to Choose Your Best-Fit Decision Management Suite Vendor [Gartner subscription or modest fee]. As they say in the intro: Decision management suites [...]

Craig Bedell – an insurance industry luminary and old friend – published a great article last week on Carrier Management – The Insanity of Analytics in Insurance (NOW FREE – no membership required). Despite an abundance of optimism over analytics, AI and more, the insurance industry still has challenges realizing the potential benefits of these [...]

Cassie Kozyrkov – Head of Decision Intelligence at Google- has a great piece on 12 Steps to Applied AI. As usual she’s got lots of great tips. I don’t have anything to add to her more technical steps but I want to add some commentary on Step 0 and Step 1. Let’s start with her [...]

The Decision Management team at Gartner (Rob Dunie , Roy Schulte, Derek Miers , Pieter den Hamer , Paul Vincent , Marc Kerremans and Erick Brethenoux ) have recently published a new paper entitled “Should Your Project Use a Decision Management Suite?” [Gartner subscription required]. It’s a great paper and I strongly recommend it if you have access. The quotes below [...]

Digital Decisioning: Using Decision Management to Deliver Business Value from AI There is an artificial intelligence (AI) revolution underway in enterprises across the globe as companies continue to adopt predictive analytics, machine learning and other AI across their businesses. This revolution puts managers and executives under enormous pressure to use AI to run their businesses more effectively. How do they do this? Will people lose their jobs?  Most [...]

Like many of you I am awash in digital photos and have been trying to find a good way to manage them. For various reasons I picked Amazon Photos. One of the key benefits was the family vault – a way to let several people upload photos to a shared space. Of course, another reason [...]

Frontline Solvers has been in business for over 25 years and focused on democratizing analytics for the last five years. They identify themselves as an alternative to analytic complexity with a focus on leveraging broadly held Excel skills and a large base of trained students. They offer several products for predictive and prescriptive analytics and [...]

Cassie Kozyrkov, the Chief Decision Intelligence Engineer at Google wrote an article recently titled  Is your AI project a nonstarter in which she identified 22 check list items for a candidate AI project. It’s a great article and you should definitely read it. In particular you should note the quote at the top: Don’t waste [...]

I blogged last week about IBM’s AI approach and one piece was still under NDA – new capabilities around trust and transparency. These capabilities were announced today. As part of trying to address the challenges of AI, IBM has added a trust and transparency layer to its ladder of AI capabilities (described here). They see [...]

Seth Dobrin wrapped things up to discuss some go to market strategies and client successes. The IBM Data Science Elite Team is a team of experts that IBM offers to customers to help jump start data science and AI initiatives. Specifically they focus on helping new data scientists make the transition from college to corporate. [...]

Shadi Copty discussed one IDE and one runtime for AI and data science across the enterprise as part of IBM’s AI approach. Shadi identified three major trends that are impacting data science and ML: Diversity of skillsets and workflows with demand remaining high and new approaches like deep learning posing additional challenges. IBM: Visual productivity [...]