In a world that is home to a growing shadow banking sector, banks are trying to find ways to compete. By offering managers decision support, giving them the technology to evaluate risk on a large scale, organizations can arrive at credit insights whose effects are felt throughout the credit
There are complex challenges that a data scientist might face in statistically modeling real-time decision-support scenarios in fast-moving athletic competitions. Each sport needs to be modeled on its own terms. A within-game decision-support predictive model for one sport cannot be applied
Business is all about placing bets on the future, having confidence that the odds are in your favor. You want to be confident that the consumer demand you anticipate will in fact materialize. You require trustworthy data to support your forecast that the product you’re developing will address a
Putting a dollar value on data is a very tricky endeavor. Data is only as valuable as the business outcomes it makes possible, though the data itself is usually not the only factor responsible for those outcomes. Doug Laney of Gartner provides a good discussion here of the challenges in attaching a
Predictive analytics encompasses a variety of statistical techniques from modeling, machine learning, data mining and others that analyze current and historical facts to make predictions about future events. In business, predictive models exploit patterns found in historical and transactional data
Customers want their experiences to flow smoothly all the way downstream to happy outcomes. And you want that too, of course, as long as their personal outcomes sync up with your business’ outcomes: retention, sales, profits and so on.
Customer experience professionals are everywhere these days, or
“Next best action” is a hot focus area in customer-facing business processes, especially marketing, sales and service. But it has just as great a potential in back-end business processes, and, in fact, ensures that many companies operate smoothly.
Next best action, in the broadest perspective, is
With its 300 nationwide department stores, Dillard's created a huge volume of logistical and customer data. Needing a business intelligence solution to organize and process this massive data and enable better business decisions, Dillard's turned to IBM's Smart 7600 System. This analytics