It's time to drop the spreadsheets full of guesstimates and management intuition...
The comprehensive data collection and real-time analysis that goes into weather reports should apply across the wider corporate world, says Mark Kobayashi-Hillary.
Something is causing illness in 19.5 million Americans every year. It's not drugs or alcohol. It's not even junk food or food poisoning.
In fact, it's water. Plain old tap water. Imagine if that many people were falling ill from some other source, such as an environmental disaster, or perhaps even an oil spill? Consider how much money would be thrown at preventing the issue. But water quality seems to slip under the radar.
I was at the IBM blogger day in New York last week and talked to a customer of IBM, John Cronin, director of the Beacon Institute. The Beacon Institute is a not-for-profit research organisation focused on rivers and estuaries. Cronin has been actively engaged in this research for more than 35 years.
I wouldn't usually be talking about rivers but there is an interesting aspect to Cronin's work with IBM. It relates to predictive technologies, which we're probably most familiar with in the form of the weather report.
Computing power and data sampling
When you listen to the weather on the news or read it on your phone, you probably rarely consider the computing power and data sampling that went into its creation.
And here is Cronin's bugbear. The technology industry can do large-scale data collection and the data analytics business is now extremely advanced. So why can't we do the same for pollution in water?
The Beacon Institute is working with IBM on data collection and analysis in the Hudson River - a showcase project that is highlighting just what can be discovered by applying the same principles behind weather reports to large water courses.
It's not a matter of life or death in the USA. Although many Americans are struck down with illness through tap water, the lives of millions of people in poorer nations can depend on knowing where water pollution exists and how to avoid it.
Large-scale data collections
And there is a clear application to modern businesses from...