Do You Treat Data As Asset Or Liability?

“Be in the buzz” is a very strong and applied business strategy; understanding where the value is, it can be a different story.

When dealing with “hyping” technologies (for few years Business Intelligence, then Big Data, now Deep Learning, AI and Robotics, blockchain and smart contracts to mention some) usually the consulting offering is set around tools and devices, with a pitch about explaining to customers how powerful this new generation is and how they can help “reducing operating costs or improve accuracy”. Nothing “wrong,” or well, for me, this is “right” like it would be to focus on the image of yourself on the glass of the window… while you should be looking outside.

In other words, the focus of the consulting offering should be on making the customer aware (if not) that data is an asset, not a liability, and helping them treating as such.

What does that mean?

We live times when “data is gold,” and we are in a “gold rush”; times when there is no value in storing, but there is more and more value in using data (“data lakes” equals to “dark data” and before you will realize they will be useless).

In any business, the challenge and the opportunity is in leveraging data that your equipment, your employees and your customers generate during your business cycle (intentionally stressing “yours”):

more exclusive is the content of your data, the faster it needs to generate value for you and the entire market.

So, who will succeed?

Who will be able to build “ ecosystems” in their business sectors, creating value from each transaction.


Because your “unfair advantage” today is in the position, you have to monetize the sense you make from data that you own (or you are able to access). This does not depend on the market, and it applies to all:


Google, Amazon, Facebook, credit card companies are simply applying the same paradigm: they own or access enough data to supply a self-improving loop (aka deep learning), creating more trained bots (aka AI) and differentiating devices and algorithms.

Few more iteration and this will shift the data market to the next level in a trustful, controlled, but decentralized way where every “data contributor” will get a stake.

If you are wondering what the next level would be, think about you owning a service platform (empowered by blockchain and smart contracts) where smaller businesses in your sector, who cannot leverage their own data (too small, too expensive), will use services and predictive tools, paying them in crypto tokens defined by you, unlocking learning paradigms that could not even be scoped by means of conventional approaches.

This will lead to an “ aggregate learning era “ when each “technician” (human or not) on every “shop-floor” will be powered with thousands of years of experience. Quite a change in our lives!


Disclaimer: Views or opinions represented in this article are personal and belong solely to the article writer and do not represent those of people, institutions or organizations that the writer may or may not be associated with in professional or personal capacity, unless explicitly stated.


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