tecosystems

Data and its Sharp Stick vs Intuition

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This debate between intuition and empiricism is as old as Plato, who thought that knowledge came from intuitive reasoning, and Aristotle, who preferred observation.” – David Leonhardt, “Making Health Care Better,” The New York Times

In the battle of intuition and data, data is winning. Things were not always thus. Time was, everyone admired the risk takers, the gamblers. The kind of leaders who shot from the hip, went with their gut and made sure you knew it.

These days, as the frustrated designers at Google can attest, even the smallest decisions are no longer made by what we feel, but what we know. A subtle, but tectonic shift. Catch Google’s Super Bowl ad? If not, you needn’t worry: it’s been up since November. Google declined to run something they thought people might like in favor of one they knew people did like, as Caroline McCarthy covers.

Whither the shoot from the hip, gambler-types? Well as it turns out, they were never much for gambling. If anything they tend towards the risk averse, advantaging data informed decisions over guesses every day of the week and twice on Sunday.

But we don’t need high powered software executives like Steve Mills to tell us that the tide is turning towards data driven or evidence based decision making. We can see it for ourselves, every day. An actual question from a reporter, received by me, yesterday: how can K-12 school districts use Business Intelligence to make better use of their data? Seriously, K-12. Higher education is one thing, but K-12?

As Erik Brynjolfsson, an MIT economist, told the Times’ Steve Lohr:

Now, the data is available so business can move toward evidence-based decision-making. This market is a huge opportunity.

Indeed. And on the buy side, that spells massive change for enterprises large and small. Consider baseball. Lots of people who read Michael Lewis’ bestselling Moneyball think it’s either a book about a singlestatistic, On Base Percentage, an indictment of traditional scouting practices, or both. In reality, it’s neither. As Chad Finn nicely articulates, it’s simply about “finding value and exploiting inefficiencies in the marketplace.” The kind of thing, frankly, that’s anything but exceptional in industries such as finance. But because the assets in baseball are also called people, and because the traditional baseball writers had no more interest in learning Statistics than they did Spanish, Moneyball was widely viewed as the encapsulation of a revelation.

That revelation, which to be sure predated Moneyball, has completely remade one of the most conservative verticals in the country’s history in less than a decade. These days, if your favorite club’s General Manager isn’t actively incorporating statistical analysis into his player evaluation and roster formation, there are two things you can be sure of. First, that you need a new general manager. Second, that you’ll get one, and probably soon. It used to be that would be General Managers needed to be ex-players. These days, you’d be better off being an ex-economist.

True, the eight billion dollar baseball industry pales next to the money in, say, healthcare. But that’s precisely why healthcare is fighting towards evidence based medicine. Well, the money and the fact that the outcomes – human lives – are slightly more important. You might have thought that medicine, as scientific a discipline as there is, would be inherently metrics driven. But you’d be wrong:

There is one important way in which medicine never quite adopted the scientific method. The explosion of medical research over the last century has produced a dizzying number of treatments for different ailments. For someone with heart disease, there is bypass surgery, stenting or simply drugs and behavior changes. For a man with early-stage prostate cancer, there is surgery, radiation, proton-beam therapy or so-called watchful waiting. To enter mainstream use, any such treatment typically needs to clear a high bar. It will be subject to randomized trials, statistical-significance tests, the peer-review process of academic journals and the scrutiny of government regulators. Yet once a treatment enters the mainstream — once we know whether it works in certain situations — science is largely left behind. The next questions — when to use it and on which patients — become matters of judgment, not measurement. The decision is, once again, left to a doctor’s informed intuition.

What happens when you extend measurement beyond the approval of a procedure or drug? Things like this:

James’s answer to such skepticism — and there is a lot of it, especially beyond Intermountain — is to show results. Intermountain has reduced the number of preterm deliveries, as well as the number of babies who must spend time in the neonatal-intensive-care unit. So-called adverse drug events, which include overdoses and allergic reactions, were cut in half in the mid-1990s. A protocol for dealing with one broad category of pneumonia cut its mortality rate by 40 percent over several years. The death rate for coronary-bypass surgery was cut to 1.5 percent, from the national average of about 3 percent. Medicare data on heart-failure and pneumonia patients show that Intermountain has significantly lower-than-average readmission rates. In all, James estimates that the changes have saved thousands of lives a year across Intermountain’s network. Outside experts consider that estimate to be fair.

Where else are we seeing data applied to questions we’re used to intuitively approaching? Maybe airline travel is your thing? Or how about politics? Fivethirtyeight.com, whom I’ve written up before, may or may not be “Politics Done Right” as they claim, but I can at least be sure their conclusions are based on actual data. No more talking heads, no pundits, no partisan claims, no spin: just the facts, ma’am.

To make all these data driven decisions, of course, we’re going to need the ability to frictionlessly collect or obtain quality data, from which to inform our own decisions, yes, but also those made by applications for us. Example:

But as both Steinberg, Friedberg and IBM’s Director of Strategy for its Venture Capital Group Drew Clark all said to me, the really interesting part about weather data will be how it will be used automatically in systems. Whether it’s home and commercial building energy management systems that can automatically take weather data into account, or a large retail chain that could automatically starts stocking up on weather-related goods, weather data can make processes more streamlined, and importantly, making energy consumption more efficient.

Add it up, and it means we needs better and cheaper storage, faster and more flexible databases, and a user interface that allows us to make sense of all of the above. Which is probably why the vendors we’re speaking with are hard at work on all of the above.

The revolution is here, and while it may or may not be televised, it’s sure as hell going to be analyzed. Because data – and its sharp stick, analytics – is winning.

Finally.

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  1. […] of Big Data and Eclipse Stephen O’Grady of Redmonk has written extensively on the rising importance of data, especially large amounts of data, in the IT industry.   Stephen is usually right about […]

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