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Data is unanimously considered to be the fuel of the modern economy. It has the virtue of being in a state of constant growth, and in theory, enables an increasingly clear understanding of the subject it depicts. Nobody seems to doubt this bottomless source of value for users, companies and governments. Take any adjective (smart, big, small, open, actionable), place it before “data”, and you’ve got the start of a successful business plan. But let’s be pragmatic and consider the value of data with regards to money – the ultimate store of value. Can data really be compared to money? And if it can, how can we ensure its strength, integrity and liquidity?

Let’s go back to the basics (and to Wikipedia). Aristotle defined money as serving these three purposes:

• A medium of exchange (or legal tender)
• A unit of measurement
• A store of value

How can data fulfil these three monetary functions?

Legal tender is the most sought-after function of data. Why? In the words of Gordon Gekko, “It’s all about bucks, kid. The rest is conversation.” In the strictest sense, data’s power as legal tender is rather limited, excluding the companies who directly sell the data collected via their platforms – these are mostly companies offering free services or content with a view to monetise via advertising.

But if we consider data as legal tender in a broader sense, it can clearly affect the net results of many companies by enabling them to increase sales or reduce costs. Without a doubt, a data-driven company will see productivity gains, but only if it implements analytics projects via a strategy that tightly links data processing and the company’s business KPIs. There are a great number of efficient examples: Data can enable complementary sales (cross-selling and upselling), better targeting and therefore better ROI on ad investments, better resource allocation (stock, production, etc.), better marketing targeting in general, and many more examples.

The often-heard term “actionable data” refers to data’s capacity to directly improve a company’s effectiveness. However, due to an almost magical belief in the ROI of data-related projects, we often overlook the fact that data has no intrinsic value of its own. When data is collected just because it’s “collectable” (and you never know, they say data is the new oil, after all), it is nothing but a cost center, and inversely reduces the legal tender (in other words, the cash) available to companies.

This function refers to the descriptive aspect of money and applies very well to data in all its forms. Without money – and without data – it’s impossible to evaluate relative values and make intelligent business decisions. Money makes it possible to compare, to go beyond the subjective, by providing a common reference point. Money makes it possible to compare diverse and dissimilar elements, and put them into perspective. Data can and must play the exact same role. This function is perhaps less exciting, but it’s nonetheless critical. There’s a tendency to seek data that’s systematically actionable and to look down upon data that’s only descriptive, or for simple reporting purposes. But we must be wary of this tendency to want to run before being able to walk – it’s the most likely way to trip and fall. We must first ensure that our data correctly depicts the reality upon which we’re supposed to act.

How can you optimise (step 2) that which not been correctly measured first (step 1)? How can you manage and determine your digital strategy if you don’t have a standard, consistent measurement of your digital performance? How can you enhance the value of your website or mobile application if you don’t have an accurate and detailed view of your audience and users?

“Accountant” may not be considered the sexiest job of the 21^st century – unlike the “data scientist” profession – but no company would dream of foregoing meticulous accounting. Many data-related professions will appear and disappear in the coming years, whereas data accountants – professionals capable of ensuring that data reliably and consistently measures that which it is supposed to depict – will have a long life ahead.

In this era where digital is tipping the balance, where each person seeks to understand what the future holds for his or her industry, it’s critical to bring order and certainty to the measurement of our actions (and let’s not count too much on the Internet giants to be concerned with rigor and transparency here). Quality data (and quality money) possess this precious ability to describe a value, make this value comparable, and in doing so, certify this value.

This third function of money refers to its capacity to transmit spending power over time – a standard of deferred payment. This function is debatable when we’re dealing with data. Some data expires very quickly, whereas other data gains value over time if it has been correctly collected and stored. To ensure this value over time, data quality is absolutely essential (but much too often neglected – read further below). Above all, questions of data security and ownership are key. Web giants like Facebook, Amazon, Apple, and Google in particular have understood the immense store of value that customer data represents, notably from a marketing point of view. They impose terms and conditions on their free services (meant for individuals or companies) so they can help themselves to this store of value. It shouldn’t go unnoticed that the valuation of digital “unicorns”, intended to predict their ability to generate capital over time, is based less on their actual revenues and more on the quality of the customer data they’re able to collect.

This model has proven fruitful for the giants of the web; it’s also a major underpinning of the supposed potential of the Internet of Things, to which information collection is central. But in exchange for a free or very low-cost service, a good number of companies abandon the store of value to be found in their customer knowledge, and in doing so, put themselves in danger in the medium term. We thus find ourselves in a rather absurd situation: In order to successfully navigate the digital shift today, companies are feeding their competitors of tomorrow. (Or even their competitors today, if we consider, for example, the troubling and growing dependence of media groups on Google and Facebook).

Data can therefore effectively occupy the role of money in the digital economy, under certain conditions:

• When aligned with business strategy, data will be even more efficient as legal tender.
• To guarantee its role as a unit of measurement, data must be approached with quality and consistency in mind.
• Data represents a store of value, provided it remains in the possession of those who produce it (companies or individuals), and provided it is not intercepted by other parties who manipulate it to make it immediately “actionable” for their own gain.

Lastly, we must ensure that this currency, stemming from our data capital, is powerful and trustworthy. Confidence and liquidity play a crucial role here – we’ll examine these aspects in part 2 of this article.