- Junta Nakai has spent his career on Wall Street and in financial technology.
- In this op-ed, Nakai argues that the common refrain that “data is the new oil” is inaccurate.
- While data has potential to drive revenue growth and cut costs, most companies don’t have the expertise to get real value from it, he says.
“Data is the oil of the 21st century” is commonly quoted in corporate America today.
These eight words embody the excitement and promise that data has the power to redefine commerce as we know it.
It’s catchy, but inaccurate. It does a great disservice to oil.
Data has the potential to drive revenues, cut costs and increase profits. But the vast majority of companies don’t have infrastructure or expertise to derive value from it.
Today, the reality is data is nowhere near oil.
Oil vs. Data
Oil has revolutionized commerce in the 20th century. Regardless of your feeling about the geopolitical and environmental impact of oil, it’s indisputable that it touches every aspect of our modern lives. The pipes that deliver you the water you drink, the soccer jerseys you sweat in, and the very roads you drive on are all made from oil.
The most profitable company in earth isn’t Apple or Microsoft. It’s Saudi Aramco (by a wide margin).
One reason why oil is held as the standard-bearer is because of the efficiency in how it is used. When a barrel of crude oil is extracted from the ground, every drop of it is used.
According for the U.S. Energy Information Administration, a 42 gallon barrel of crude oil produces 19 gallons of gasoline, nine gallons of diesel, four gallons of jet fuel and 13 gallons of other fuel products.
An astute reader will point out that the sums of the products are greater than 42 gallons. That’s because of something called the Processing Gain. A barrel of crude gets separated into roughly 45 gallons of usable fuels. 42 becomes a 45. Put another way, output is greater than input by about 7%.
Data is the complete opposite of oil
Modern enterprises only use 0.5% of the data that they posses according to IDC. Input is far greater than output.
7% gain vs 99.5% loss.
If data was truly as valuable as oil today, we would be using far more than 0.5% of it.
Several characteristics of data when compared to oil make data even more difficult to handle.
- Finite vs Infinite. Self explanatory.
- Linear vs non-linear. Demand for oil is expected to grow only 1.2% per annum to 2040 (OPEC). Data generation expected to grow 61% per annum to 2025 (IDC).
- Local vs Universal. Building rigs, pipelines and refineries are limited to oil companies. On the other hand, every single company has data and needs to figure out how to extract, clean and use it.
The low efficiency of data, its infinite supply and its rapid growth presents massive challenges to modern corporations. It’s not that data is not as valuable as oil, it’s that the infrastructure to deal are so complex that only the select few like Facebook and Netflix know how to manage and use it effectively.
Data is universal while oil is local
Over the last century, oil companies have relentlessly innovated and invested to transform crude oil. Complex pipelines and tankers bring oil to refineries. These refineries separate crude into various usable products that are used to many everything from tires to medicine. Refineries are massive industrial complexes that cost billions of dollars to make and tremendous expertise to operated.
Dealing with data is a similarly complex issue. Using the same refinery analogy, you can see how much more difficult it becomes when your input is growing 61% per annum. Not to mention that unlike crude oil, data comes in vastly different forms (structured, unstructured, batch, streaming, etc).
With oil, its processes are the exclusive domain of oil companies. But with data, every company in the world has to architect their own process. This is precisely why there is such a big gap between the companies who can manage it and the vast majority who cannot.
Technological innovations are bridging the oil-data gap
Luckily, companies today have a choice. They can continue to go out and build massively complicated refineries for data, hire tons of people at great expense, and keep investing in adding capacity of the refinery year in and year out to try to handle it (a task becoming more challenging because Moore’s law is dead and computing power doesn’t grow like to used to).
Or they can leverage the cloud and big data compute engines like Apache Spark to store and process the data. There are also Unified Analytics Platforms that make this modern data architects available to all companies, even to those without deep technical expertise. Together, They enable companies to outsource the refinery and processing of data and instead focus on the usable outputs and do advanced things like machine learning.
More and more companies are choosing the latter route. There is a reason why the two biggest companies in the world are public cloud vendors and why many of the fastest growing companies are big data, AI, and analytics startups that augment cloud computing.
Data can redefine commerce with the right tools and priorities
Even in sectors that were historically adverse to cloud adoption, things are rapidly changing. Banks were initially hesitant to adopt the public cloud. They had spent hundreds of billions of dollars investing in and operating their own data refineries in the form of on-premise data centers.
Conventional wisdom held that the efforts, costs and risks of moving to the public cloud wasn’t worth it for banks. But Jamie Dimon of JPMorgan Chase, the sector’s de facto leader, recently wrote that: “On the importance of the cloud and artificial intelligence, we are all in.”
“The combined power of virtually unlimited computing strength, AI applied to almost anything and the ability to use vast sets of data and rapidly change applications is extraordinary – we have only begun to take advantage of the opportunities for the company and for our customers”.
Data isn’t oil. At least not yet.
But rapidly innovating and expanding infrastructures as well as changing CEO mindsets are enabling it to get closer to oil. One day soon, companies will get as much out of data as they do from oil. And it will re-define commerce as we know it.
Junta Nakai is the industry leader for Financial Services at aartificial intelligence company Databricks. Prior to that he was the Global Head of Business Development at Selerity, a financial technology firm providing AI solutions for capital markets. Junta started his career at Goldman Sachs, where he spent 14 years in the securities division and served most recently as the Head of Asia Pacific sales for the Americas in the equities division.
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