What do Jeopardy! and Nate Silver have in common? For different demographics, they have become pop culture representatives of the Big Data revolution meant to transform our individual lives and society as a whole. First, IBM’s Watson computer convincingly dispatched its human opponents in a Jeopardy! champions match. The victory was then triumphantly promoted by the technology vendors specializing in the storage and analysis of vast data sets, and the technology press predictably dubbed it a “new era” for large-scale structured and unstructured data. Nate Silver’s data laden and accurate 2012 Presidential forecasts made him a media star, while demonstrating a powerful real-life application for the implementation of big data.

Watson and Silver’s victories certainly made the public aware of how far our ability to store, access, and analyze vast amounts of data has come across the past 10 years. [But] I have a deep, nagging concern about a central fact that all this hype seems to be missing. At the highest level, it’s hard to escape the simple fact that the global financial crisis had its roots in the most data-rich, technology intensive sector of the economy.

As we surpass the five year mark of the global financial crisis, headlines continue to remind us that America and its banks are still grappling with the direct fallout from the behavior that caused it.

The financial services sector has been a voracious consumer of the technologies that create, store, transmit and – most importantly, analyze – data of all types. An average portfolio manager, risk manager, trader or executive has more information and tools at his or her disposal than the commanders of the Apollo missions to the moon. Moreover, this spending is and was intensely concentrated at the largest institutions, including some who suffered catastrophic or near catastrophic losses.

Of course, it would be absurd to suggest that advanced analytics caused the financial crisis. Properly deployed, storage, manipulation, and assessment technologies can track, assess and help humans visualize and understand potential risks in ways unthinkable even 10 years ago.

That said, I am a believer that big data – no matter how comprehensive or well-analyzed – needs to be complemented by big judgment. If anything, technology investments should be thought of in much the same way as financial leverage – big data and big analytics will merely amplify the effects of human decisions, sometimes to an unimaginable scale. This is great news if those decisions are timely, sound, and properly motivated – and potentially catastrophic if not.

Even as companies deploy Watsons (or Nate Silvers) of their very own, they’d be well advised to ask four critical questions.

1. Where does human judgment intersect the flow of data and information through my company? If human judgment and analysis is merely the “final step” in a decision making process, companies will base important decisions on flawed inputs or analytic constructs.

2. How do I synthesize experience? Either due to high turnover in roles, or an imminent retirement wave, most industries lack the tactile feel for important buyer and economic dynamics that provide an important counterweight to rigid analytic outputs.

3. How do I cultivate the critical thinking skills necessary to challenge and interpret analyse? Watson, which was perfectly optimized to win at Jeopardy!, would have gotten creamed if the game shifted to Wheel of Fortune or Mah-jongg halfway through. In commercial and public settings, the “game” can shift suddenly and without warning, and decision systems may rapidly lose relevance.

4. Finally, how do I ensure that my corporate compensation systems and culture facilitate dialogue and dissent? Great decisions are seldom the result of great data alone. They emerge through a processes defined by challenges, contributions and second-guesses that shape a uniquely valuable interpretation of data. Too many corporate cultures suppress or deter questioning or the chasing of a stray fact.

The global financial crisis showed all too plainly what can happen when rich data and analytics collide with gaps or lapses in judgment. Businesses everywhere need to ensure that their processes and human capabilities keep pace with the big data firepower that they are importing or we’re likely to see similar crises emerge in other industries, and soon.