Data Capital - A future of bits not atoms

"More and more important assets in the economy are composed of bits instead of atoms"

- Erik Brynjolfsson, Director, MIT Initiative on the Digital Economy.

The digital economy might as well be called the data economy. Billion dollar businesses are running on data. Companies like Uber, Airbnb and Netflix are all trading in data. Facebook and Google rest their entire business models on it. However, this has led to an idea that any company making its money off data is primarily a tech company, and conversely, data generated by traditional businesses and brick-and-mortar operations do not have similar value. Nothing could be further from the truth.

You are in the Data Business

"I’m not in the hamburger business. My business, ladies and gentlemen, is real estate."

McDonalds may have sold 300 billion burgers, give or take a few, but founder Ray Kroc knew that his greatest asset wasn’t cheap fast food. The above quote by him is a great example of a businessman knowing where real value is, and this is something he said way back in 1974. The world has changed since then of course, but the principle of hidden assets hasn’t.

What most companies need to realise is that it doesn’t really matter what they do, they are all in the data business. Companies like Amazon plumb into the depths of the data they generate every day, Learning from consumer behaviour, delivery times, and a whole lot more and performing predictive analytics to serve customers. How many other companies mine and generate enormous amounts of data but throw it away? A lot.

Data Begets Data

Data is probably the only self-generating asset there is. Once put to work, data creates new data in the form of performance results, which can then be studied and fed back into the machine to create a cycle of refinement. Each cycle makes the data more relevant, more accurate and more valuable. Once this gets rolling, it’s very difficult for a newcomer to catch up to this cycle.

Data Needs To Be Recorded

If a tree falls in the forest, and there is no one to digitise and log it, did the tree really fall? This is not just a philosophical conundrum; it’s one of the key principles for the proper utilisation of data. Truth is, data is created by every activity, but unless it is recorded, it is lost. To prevent data assets from falling through these cracks, it is important to analyse and digitise key activities at all important touchpoints. It is also important to expand across the value chain in order to have access to more industry data.

She Who Controls the Platform, Controls the Data

In the world of data, the platform is king. Amazon created a platform that disrupted the entire retail industry, but any big retailer could have done it. Similarly, the taxi industry didn’t even realise it was in a platform war until Uber came along, and when it did, it was too late. In order to use data, companies need to capture data. And in order to capture data, they need to have a platform that is used by industry professionals. For every Uber, there are a hundred industries that don’t have a platform yet.

The opportunities are there.

From Big Data to Data Asset

The concept of big data posited data as a problem to be managed. It insinuated that data was big, unwieldy, a problem of scale. By recognising data as an asset, companies and specifically CEOs can turn the conversation from how to handle data, to how to capture more of it and use it best. And they need to as well, because the value of data will only increase. A 2011 survey of 180 large companies revealed that companies that focused on data-driven decision making performed 5-6 percent better than similar companies in similar conditions. It can have only grown.

From fleet tracking data produced by trucking companies, to flight data from airlines, from customer data by grocery chains to geographic data by earth-moving companies – all data can be used, not just internally to refine and improve performance, but also by third-party companies in tertiary industries. With the advent of AI, when deep learning becomes more automated and easier, this kind of data will be the engine that drives entire industries forward. It’s time to invest.