July/Aug 2010

Forecasting is one of the most powerful and widely used tools by analytics professionals, and rightly so. It rests on a firm mathematical foundation. It’s taught in universities world over. And it’s extremely useful. Whether forecasting the number of people expected to buy newspapers or the demand for computers, good forecasts lead to better decisions.

• Andrew Boyd

Our forecasts never seem to be as accurate as we would like them to be – or need them to be. But why are forecasts wrong, and sometimes so terribly wrong? Forecasts fail to deliver the level of accuracy desired for at least four reasons.

• Michael Gilliland
• Udo Sglavo

We can forecast this: forecasting will continue to be in the news. The U.S. government gives the current unemployment figures, and then we hear pundits and news sources predict what those figures will be next quarter and next year. We read about the Congressional Budget Office’s projections [1] for the country’s deficits (see Figures 1 and 2) through 2019 while speakers and articles quote and then extol or deride the projections [2]. The CBO’s opening sentence, “Since the Congressional Budget Office last issued its baseline projections … the outlook for the budget deficit has deteriorated further,” gives one pause. The projections made just a few months earlier for what will happen in a decade were wrong and had to be updated. In other words, as more data comes in, the forecasts may change.

• Jack Yurkiewicz

Conversation around business analytics is becoming a boardroom discussion. With the abundance of data, information and content that enterprises have today, enhanced focus is on the discipline of business analytics to enable better business decision-making across the enterprise. This article provides a unique perspective on how companies should create an enterprise-wide approach to deploy analytics decision-making, as well as a summary of the journey that Hewlett Packard took in deploying analytics in a shared services model.

• Prithvijit Roy
• Arnab Chakraborty
• Sanjay Singh

On May 7, the most-watched stock market measurement in the world – the Dow Jones Industrial average – plunged nearly 1,000 points (almost 10 percent) in a matter of minutes. The size and speed of the drop shocked the financial world, but what was truly shocking was that weeks later, the best reason any Wall Street wonk could offer to explain the breathtaking roller-coaster ride (the Dow recovered most of what it lost within a half hour) was a “trading glitch” that triggered massive, computerized sell orders.

• Peter Horner