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We have barely tapped the power of AI to improve the lives of people who are excluded from many of society’s benefits.

Scott Thurm recently wrote a piece in the WSJ Marketplace section - Now, It's Business By Data, but Numbers Still Can't Tell Future. He talked about the growing trend of trying to run companies more analytically, more "by the numbers", and the success some of those companies have had with this approach including those profiled in Tom Davenport's book "Competing on Analytics" (reviewed here). He quoted Robert Sutton (one of the authors of Hard Facts, Dangerous Half-Truths And Total Nonsense, reviewed here) who contrasted running a business by the numbers with running it based on "faith, fear, superstition and mindless imitation"! However, Scott then goes on to identify two key risks inherent in an analytic or data-driven approach. Change upsets the basis for the analysis Too much focus on analysis stifles the creativity needed for innovation and tomorrow's growth These are both good points and made me think about enterprise decision management(EDM) in this context. Now Tom Davenport talked about the need to make "quick, accurate decisions on an...

Guillermo Kopp over at Tower Group wrote this piece - Top 10 Trends in Financial Services: New Approaches in a Changing World (subscription required). It is an interesting paper, though I hope he will write some follow-up pieces as there are some really interesting areas that are dealt with very quickly! Anyway, to quote from the summary, two main themes seem to me to require enterprise decision management (EDM) for an effective response: TowerGroup has found that, for both retail and wholesale interactions, consumer preferences will influence the financial services agenda. To improve delivery channels, products, and services, FSIs are embarking on a creative race for competitive differentiation and giving priority to strategic technology initiatives. So consumer-driven banks offering creative differentiation across multiple channels through complex sets of products and services. All in a heavily regulated world where you need to get a return on compliance and where enterprise fraud management and enterprise risk management are critical....

I just finished reading Dr David Ullman's new book, "Making Robust Decisions". The book is a discussion of the challenges of making complex decisions, especially those with alternatives and uncertainty, and a methodology/software platform for approaching these kinds of decisions. It's a quick read with some great advice for anyone trying to make decisions, even if they don't want to adopt a more formal methodology. The sections on uncertainty, weighting of criteria and belief maps were particularly interesting. A couple of things stood out from an EDM perspective: There was a great list of questions about a decision that could be applied to a decision you were automating as easily as they can be to a more manual one: Which is the best alternative? What is the risk that our decision will not turn out as we expect? Do we know enough to make a good decision yet? Is there buy-in for the decision? What do we need to do next to feel confident about our decision, within the scope of our limited resources? David also had a great definition of the phrase...

This book has been a hot topic recently. I first heard about it at InterACT where Larry Rosenberger used it as part of his discussion on the future of analytics. The book is an easy read and full of wonderful stories and vignettes that illustrate Malcolm's points. Essentially the book is about how people make rapid decisions, often before consciously processing the available data, and the good and bad consequences of this. We are all familiar with some of the negative consequences - racial stereotyping for instance - but Malcolm discuses some of the positive ways this impacts effective decision-making. Using a relatively small case of characters and some richly described stories he leads us through an understanding of how rapid cognition works, why it is different from how we analyze things and how it can be more or less effective that any approaches to problem solving. I particularly enjoyed the stores about people who had trained their snap judgments so that they could make quick and accurate assessments of situations while not being distracted by misplaced...

I saw an interesting article in CIO Insight the other day: Health IT Must Target Fraud, Group Says. The report - from the Foundation of Research and Education (FORE) of the American Health Information Management Association (AHIMA) - says that it is essential that fraud management programs be built into the new National Health Information Network (NHIN) to significantly reduce health care fraud losses. The report calls for interoperable Electronic Health Records as a major enabler - integrated data being no less important for healthcare than it is for CRM - and goes on to say that major strides can be made in reducing health care fraud by applying advanced analytics like those used so  successfully in the financial services industry.  The best results will be driven by both prospective and retrospective approaches, the report said, and made a fairly dramatic prediction of the value:“By 2007, healthcare payer organizations that adopt automated systems for fraud and abuse detection will see a return on investment of at least 5 to 1,”The report was...