Why the CIA was right about data

What if mission-critical data was quite literally flowing through your air conditioning vent?

A 2021 study by Harvard University found a negative link between the brain power of office workers and indoor air quality. When the air was bad, employees were sleepier, took longer to respond, answered fewer questions correctly and needed more help to focus.

By improving indoor air quality, other Harvard researchers showed that companies can add up to 10% more productivity among their staff, equating to about 41c per hour, per employee.

That’s serious money. And it usually goes untapped because companies don’t realise that even an air-conditioning unit can produce real data that can improve performance.

Of course, not all data is useful. It all depends on the questions you ask the data. So, in that sense, the Harvard study is a bit misleading.

The problem is that it began with a clear premise that indoor air quality might affect staff productivity. The researchers weren’t looking for a correlation. They knew it was there and wanted to measure the size of its impact. The researchers were just lucky that airflow is a relatively easy thing to turn into data.

Usually, the things that are most important for a business are notoriously hard to get any data on. Every company can measure their indoor air quality, but what would be the point? Most data is useless without some way to find correlations between it all.

The true value of data isn’t in having it – no matter how large the data set. Value can only be unlocked once a human thinks of good questions to ask the data.

The clever people at CIA understood this better than anyone else.

The intelligence agency knew universities like Harvard were full of studies and excellent data. Their libraries stored decades of potentially valuable insights. So, CIA set up an experiment to engage with selected academics who would analyse a handful of its high-level classified intelligence questions.

CIA was curious to know what sort of information existed in “open-source” databases that it might be missing.

The rules of the experiment were simple: the intelligence questions could not be repeated outside the group (revealing to adversaries what CIA doesn’t know can be just as damaging as revealing what it does know) and the academics could only use open-source data. Playing James Bond to steal information from “closed” sources was not allowed.

The academics went away and dutifully pulled together comprehensive analyses and after a few months returned their results. Once CIA read the reports, the agency immediately classified the documents citing national security risks. No one ever saw them again, including the academics who wrote the reports.

It’s important to reiterate here that the information that spooked the spooks was entirely free. Like the indoor air of an office space, the data was flowing across public computers, bookshelves and databases without any restrictions.

Even today, all that data used by those academics in the experiment remains available to the public. And yet that open-source data was useless until people with questions began to look for connections in the noise. That’s when the data magically transformed into powerful knowledge.

So what is the takeout here for companies?

Gathering data is always a good idea for any business. However, not all data is equal. You should understand the potential business case, value of each opportunity and the costs and risks that exist with capturing a specific data set. 

Just measuring airflow in a building, for example, isn’t all that useful. But it becomes valuable when you realise that indoor environmental quality data is an intangible asset that can enhance social value (‘S’ of ESG) and help a company decarbonise (‘E’ of ESG).

These efforts make companies more investible, reduce risk and enhance compliance with GRI and other international sustainability standards. Buildings that use indoor environmental quality data as an asset can also achieve important certifications, which results in higher rent per square foot, higher occupancy/tenant demand and an increase in the capital value of the building by 7% to 10%.

In effect, data is just like any other asset and should be assessed based on how it can be utilised and the value it will deliver. And this means not just looking internally for utilisation opportunities, but also at how you might be able to drive value through licensing or sale. That data set that holds no value to you just might be the key to unlocking a whole new revenue stream for another company, potentially making it a lot more valuable to you (if you understand how to leverage it). 

Data is one of those weird intangible assets that only becomes valuable when you know the questions to ask and how to assess its value. Do you know what data is most valuable to your company? Are you asking the right questions?

Until you have a strategy for your data, then it’s just an air-conditioning unit humming away in the background.