The Truth About The TruthThe Truth About The Truth

"A lie can run round the world before the truth has got its boots on." — James G. Watt

The difference between data, information, and the truth has never been so important, and, although these differences are easy to define, they're impressively hard to put into action. It's a problem that permeates our data-rich and information-poor society as never before, hooked as we are on real-time, 24X7 operations that span a global economy. Look at the Bush administrations' problems with intelligence and weapons of mass destruction (WMDs). Former CIA head George Tenet — effectively the CIO of the administration's intelligence line of business — fell on his sword by resigning just weeks before a Senate committee report surfaced that blamed Tenet's information processes for feeding the President misinformation about WMDs. Our country's involvement in the war in Iraq isn't an issue for this column, but suffice to say that an entire planet-full of actions have taken place based on information and analysis that have proven to be a lot less than accurate.

All this shows that a little kernel of truth is worth a whole lot more than reams and reams of information, however well reasoned or well intentioned they may be. So while there's no doubt that we have more and more information at our fingertips, does all that information mean we know more about the truth? Unfortunately, the answer — the truth about the truth — is as stubbornly elusive as ever. Meanwhile, the risk of using the wrong "truth" increases with every technological advance.

The False Truths

One reason the metatruth is so elusive is that it's rooted in a basic philosophical problem: The more you process information, the further you get from the truth. Knowing the truth about things that take place in front of your very eyes — where you're the real-time analyst, observer, and recorder — is relatively easy. If you're colorblind, for example, you might think an object is gray and not green. You may not rival Sherlock Holmes in your powers of observation, but all things being equal, what you can see with your own two eyes is generally truth enough for most of us.

But the moment an analyst relies on information that's dated or has been processed in some way, the truth becomes highly interpretive. Do you have complete information? Is it from a reliable source? Is the data timely? Do you understand how the data and metadata are stored and are intended to be interpreted? Are the correlations and assumptions that you're making about related data valid? Once the analyst is no longer watching and observing events in real time, these questions become harder to answer with confidence. Without an unequivocal yes to each question, the absolute truth can only be guessed with some hopefully reasonable degree of accuracy. And when it comes to the complex interactions that take place in business or government, there's no possibility that the important issues can ever be known by simple observation. Hard issues often require analyzing things that happened a long time ago in distant lands. Which means that the truth becomes a hoped-for conclusion, not a given. Strike one against the truth.

The second reason that the truth is hard to know is a result of our human frailties. We often crave the truth so badly that we're all too willing to believe what we're told, regardless of how honest the source is or believable the facts are. And once we've latched on to a perceived truth, its aura of authenticity and the sycophantic nature of groupthink make it self-perpetuating. This is what happens with groupthink, management by committee, and other such evils of the modern world. Which is a major reason why consultants such as myself can actually make an honest living: More often than not my job is to show how a decision, strategy, or basic assumption that is fundamentally wrong has been distorted into something resembling the truth. Once the truth about the "truth" is known, the process of disentangling the viral nature of falsehood and the search for the real truth can get underway. This happens all day, every day, in every company, even my own. Strike two.

The increasing automation of business processes — using the enterprise software we all love to hate — can take the time/distance problem and the self-perpetuating nature of perceived truth and create a runaway train effect that can take a little untruth and turn it into a major operational disaster. The infamous case of Nike's supply chain software misdirecting shipments around the world forced Nike not only to take a major write-down but also suffer more than $2.5 billion in lost market capitalization. All because a single set of wrong assumptions — about where $100 million in finished goods had to end up in Nike's global supply chain — were treated as the truth when they couldn't have been farther off base. Strike three. You're out.

Ripple Effects

What makes this more scary is that many companies are building an IT world full of Web services that could take an untruth from one company and send it flying in real time across an entire supply chain, creating a network effect of bad data and bad processes that could do a lot of damage to a lot of innocent companies before anyone found out, if indeed they ever did. Imagine if you were a logistics partner or supplier to Nike taking in automatic demand and shipment data from your number one partner and planning your business processes accordingly. Imagine 20 companies, or 200, doing the same: factories in Asia, shipping companies across the Pacific, distributors and retailers in the United States, all marching in lockstep to the same bad data. The ripple effect could turn into a tsunami before anyone could stop it.

It turns out that in our rush to put information to work, we forgot to put in place the formal mechanisms that can legitimately question our initial assumptions and keep the runaway truth train from heading down the wrong track. And as companies make use of external Web services over which they have little or no control, the garbage-in/garbage-out problem becomes even scarier. A bad external service — a logistics tracker, a foreign exchange calculator, or a credit authorization system — could send your company down the road to lost revenues and lost customers, and you wouldn't even know it until it was too late.

So before you're left wondering what happened to the WMDs or your partner's last shipment, start questioning your initial assumptions. Then worry about how those assumptions get perpetuated, unchallenged, throughout your increasingly automated IT systems. And then worry about how hard it will be to fix the problems once the runaway train has left the station. The truth about the truth is that it's just as hard to know as ever before. And while that hasn't stopped us from running with what little truth we think we possess, it should at least give us pause before we send those boots to Bali instead of Baltimore.

We need to address these problems now, before it's too late to do anything except watch the real truth — not the one we think we know — unfold before our eyes.

Joshua Greenbaum is a principal at Enterprise Applications Consulting. He researches enterprise apps and e-business.