Premise and The Hurdles Big Data Will Face With Economics

Premise is a fascinating new company that aims to disrupt how macroeconomic data is collected. Individual companies are using every conceivable aspect of consumer data to predict their own sales. Why can't this same insight be used to measure the economy and revolutionize economic indicators?

There is a reason Big Data started out in the collection and analysis of the data within individual companies. A huge component of the value of information is access. Within a company, this variable is taken out of the equation. All the data is proprietary to the company and everyone within the company is working towards a common goal.

The value of information about the economy depends on the information everyone else has, and this value expresses itself in a few unique ways.

The first and relatively simple way this expresses itself is the value of exclusive information. It's clear to anyone working on Wall Street how valuable having an information edge is. This drives researchers to search for more and more esoteric datasets to try to tease out a relationship no one has ever thought of. As a relationship becomes more known, its value quickly drops to zero as stock prices or any other market being watched already has this information baked into it.

There is a related converse dynamic to this value of uniqueness that comes into play once data becomes widely known. People use information to make decisions. Once information is "out there," its value increases the more people use it. This is because multiple actors are all making decisions that affect each other.

Think of a specific industry as an example. If you're an automotive company and have information that no other automotive company has access to, you can use that as an information edge. This edge pretty much disappears the minute one other company learns of it.

At this point the second dynamic takes precedence. If 10% of the industry is using a certain piece of information, there's not too much of an incentive to use that information. On the other hand, if 95% of an industry is using a certain piece of information, the 5% who aren't are at a distinct disadvantage, and if you're a new entrant or analyzing the industry from the outside, you're going to want this information too.

Economic data responds to these dynamics in some weird ways. Headline indicators are venerated as describing the pulse of the economy, and maintain their momentum through their own heavy use. GDP is a deeply flawed measure of the economy. There are some alternatives out there, and there is more and more data every day that will allow us to create better measures of the economy, but GDP is still the agreed upon standard and continues to be because of inertia.

A company like Premise can take advantage of these dynamics in two ways. The first is to simply create indicators that compete with the standard indices we now have available. If Premise creates a few "rockstar" economic indicators, it will have a stable business as long as there exists an economy to be measured.

This isn't truly unleashing the power of big data into the economy. In my opinion this would be an upsetting outcome: using all of that power to simply create a new static status quo in how we measure the economy.

I see true success coming in a second path: the creation of a platform where anyone can create their own indicators. Instead of using a headline CPI number that is created using certain statistical methods from the Bureau of Labor Statistics, these methods would be available to anyone using the platform.

With this platform in place, the dynamics that now allow certain data to become stodgy and out of touch will start leading towards innovation. All the platform will have to do is link to already existing economic data.

How will this process play out? A headline indicator like CPI has a gravitational pull that makes it a benchmark of the economy. However, if a user is able to make a few tweaks to that CPI data using its atomized components, they will gain the benefits of BOTH dynamics. Their measurement is close enough to CPI to benefit from its wide use, but different enough to create an informational edge. Instead of crystallizing into a series of discrete indicators that never change despite the changing economy, the dynamics will now be incentivizing the discovery of new and unique indicators.

Our understanding of the economy as a whole will be revolutionized, and we'll all be making smarter decisions. People will be encouraged to have a deeper understanding of the economy, instead of relying on measures of the economy that are used simply because everyone uses them.

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