The Titanic Teaches us About Data Assets and Reflexivity

The Titanic Teaches us About Data Assets and Reflexivity

Click here to learn more about author Reuben Vandeventer.

I rarely start out sentences with “It’s sort of like the sinking of the Titanic,” … but for this topic, I’ll make an exception. The point I want to make is that from a data quality perspective, what actually sunk the famous vessel was not so much the iceberg, but rather Captain Edward Smith’s management preferences and reliance on incomplete data — and the effect of reflexivity.

In this way, Captain Smith is not entirely unlike the CEOs of many publicly traded organizations today. The difference is instead of mishandling data about icebergs, they may be mishandling a variety of key data assets and organizational metrics. The bottom line is that, like the good captain, they’re not effectively managing risk.

In Smith’s case, his main responsibility was to cross the Atlantic without sinking. The CEOs’ responsibility, in contrast, is to report every 90 days on the state of their organizations’ financial performance. If there is any discrepancy between what is considered to be true and actual reality, they are held criminally responsible — and that is truly a sinking feeling.

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What could cause such discrepancies? After all, the CEO may perceive that the data and operational metrics they use to make decisions are sound, accurate, and trustworthy. But I learned another perspective firsthand over the course of more than ten years of working intimately with data used to make decisions about cash flow, reserve projections, and other key decisions. I learned that perception about data is rarely the exact truth. As with most things, perception about an organization’s data is the reality we gladly accept — but sometimes it is not the same as actual reality.

In fact, history books are full of times when this dynamic played out on macro scales — creating asset bubbles in everything from the 16-century international tulip market to the real estate bubble of the previous decade. In each of these cases, disaster was preceded by blissful exuberance. In addition, perceptions became increasingly disconnected from reality, such that the perceived truth became the market value, despite the much lower intrinsic value.

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Many people have written about this phenomenon of diverging perceptions, but none more comprehensively than famed hedge fund manager George Soros. In fact, he built much of his management and investment philosophy on the certainty that the influence of reflexivity can and will cause perceptions to deviate from reality (and when it does, chaos is sure to follow).

I propose that the same dynamic occurs when data is not managed as professionally as financial assets. Here’s why. Each community of data users naturally sees the data through their own lens. For example, users in the business units focus on their process and activities that directly support the Profit & Loss, balance sheet, and cash flow. IT staff, meanwhile, tend to focus on the tools, systems, code, and technologies that they either find interesting or must support. The list goes on. As these groups work with each other around shared data, they create feedback loops — perspectives on the data that tend to self-reinforce the prevailing view.;

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