AI

Is Your AI Project About Customer Experience or About Business Decisions?

Many organizations are investing in artificial intelligence (AI) initiatives these days. However, many are also lumping all of the uses of AI into the same program. This is a terrible idea because AI technologies are being used for two very different business outcomes. AI success relies on a clear focus on business outcomes rather than […]

Algorithms and Regulations: Tips for Success

Cathy O’Neill wrote an interesting piece on regulating automated decision making recently. I am not going to argue about whether use of algorithms should or should not be regulated because I think it is inevitable that they will be. The question is how companies should respond to these regulatory efforts as they are rolled out […]

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.

Tips for Successful Data Science Implementation in Insurance

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 implementation. These three challenges – getting business buy in, attracting talent, and strategic alignment are exactly […]

International Institute for Analytics 2019 Predictions – Some Thoughts

Several of this year’s International Institute for Analytics predictions point towards a DecisionsFirst decision management approach.

DecisionsFirst Analytics in Forbes

Joe Decosmo, CAO of Enova Decisions and someone we know from our work at the International Institute for Analytics wrote a nice piece in Forbes today – Why You Should Take A Decision-First Approach To Analytics. Joe makes some great points in his post and leads off with a shout out to the Decision Management Manifesto. Like […]

Don’t bite off more AI than you can trust

Many, most, companies are actively considering using AI in their business, but few are making much progress. Some of this is due to a poorly defined approach. Some is due to confusion as to what AI means – mixing conversational AI (a user experience technology) with decision-making AI (an extension of predictive analytics and machine […]

Adopt Decision Modeling for DecisionsFirst Analytic Success

Add decision modeling and a DecisionsFirst approach to analytics to this established AI Solution Decomposition Process to make it more effective.

Don’t Use Executable Decision Models – Part 4

This is the final part in my series on why we don’t recommend using executable decision models. Part 1 discussed the problem of additional model technical complexity required for executable models, resulting in business users disengagement. Part 2 detailed the challenges of reuse and maintenance with an executable model, and Part 3 outlined how executable […]

How to Succeed with AI – New Leading Practice Brief

To succeed with AI, focus on decisions, not a separate initiative. As companies invest in AI technologies, it is clear a technology-led approach does not work. To get business value from AI, companies should focus AI efforts on improving business decisions. A recent survey of executives adopting Artificial Intelligence (AI) provides critical context for companies […]