The relative power of data
As we saw in part 1 of this article, data can create value by fulfilling the three roles held by money (a unit of measurement, a store of value, and legal tender). But it’s interesting to go further with the analogy by asking ourselves what gives money its power, and what allows it to fulfill these three functions in the best conditions? Indeed, not all currency is equal. Pokémon cards are units of measurement (EX, HP, etc.), a store of value, and they serve as phenomenally powerful legal tender on the playground. But in certain circumstances, we probably prefer dollars or euros to Pokémon cards. The same goes for data. How can we ensure that the data we collect and generate has a value closer to that of the dollar than of a Pokémon card?
Money’s strength is based on two key characteristics: confidence and liquidity. And the analogy with data works perfectly here as well. But unfortunately, confidence and liquidity are too often neglected, endangering so-called “data-driven digital strategies”.
First, let’s talk about confidence. The etymology of “fiduciary” and “confidence” reminds us of their shared origin, fides, meaning “faith” in Latin, whereas “credit” comes from credere, or “to believe”. If there’s no confidence in its legitimacy as legal tender, or in its ability to withstand the test of time, a currency’s value collapses. The most flagrant example of this was the hyperinflation in 1920s Germany; today, we see the pound subjected to Brexit-fueled anxiety. With regards to data, a lack of confidence (and thus a loss of value) can happen on several different levels:
- Confidence and trust in the data’s consistency and reliability. All too often, the exponential multiplication of analytics tools, the impossibility of measuring different platforms (web, mobile apps, offline) in a consistent way, a lack of certification, or simply mediocre-quality data collection and storage all make it difficult for decision-makers to trust the data they’re given. In order to make truly strategic, data-informed decisions, it’s essential to ensure the credibility and constancy of your numbers – their ability to convince depends on it. It’s unreasonable to expect to convince executive management using cobbled-together, non-exhaustive tools (that use sampling) and disparate, unverifiable, uncertified performance indicators.
- Customer confidence and trust. Before it belongs to the company collecting it, data first and foremost belongs to users of the service – the customers. It’s critical to maintain a fully trusting relationship with them, or else you risk them leaving the service. Respecting user privacy goes beyond just legal obligations (which should only get tighter, notably with the GDPR). It’s also an indispensable condition of the bond that links a company and its customer. Accessibility, transparency, security and appropriate usage must frame the use of customer data to ensure it remains exploitable and valuable in the long term.
- Confidence in technology vendors. The development of SaaS solutions and of cloud-based storage has generalized the usage of third-party analytics tools. It’s therefore fundamental to ensure that your technology vendors are not reusing your data in ways that demonetize it completely. A common example involves feeding DMPs, enabling the development of targeting algorithms, which are then potentially useful for the entire market (and therefore for your competitors as well), all while breaking the bond of trust with your users. In this case, your data’s value is creating an advantage for your service provider while depriving you of your competitive advantage. The most absurd example – and the most frequent – involves feeding your customer data to your main competitor, who will be able to use it to their advantage… at your expense. (Case in point: the grotesque situation of media groups using Google’s analytics or marketing intelligence tools. But I admit to probably having a biased view of the question.) Additionally, not only does this diminish your data’s power as legal tender – and transfer that power to your competitor – but your digital accounting becomes an open book to this competitor. And to top it all off? You multiply the risk taken related to user privacy. Fortunately, the European Commission via Margrethe Vestager (@vestager), as well as numerous reputable newspapers, are beginning to probe this sensitive question. These are problems of sovereignty that affect all companies, engulfing them in the end and exposing serious, high stakes on the political and social front.
Liquidity is the second characteristic of a strong money (and strong data).
Etymology illustrates the evolution of currencies whose power was initially restricted to limited trade and geographical areas. “Capital” is derived from capita, referring to the heads of livestock, whereas “pecuniary” stems from pecus (cattle), as herds of livestock were originally the main measure of wealth against which the value of goods was calibrated. Let’s just say that the risks of high frequency trading were limited back then. As money became lighter – going from metal coins to bank money to ultimately becoming dematerialized – it became even more powerful as a means of trade. Data has undergone the same evolution. The faster it can circulate, and in good conditions, the greater its value. If the tri-fold conditions of confidence mentioned above (via reliability and security, notably with regards to privacy) can be ensured, data will gain value when obtained and exchanged quickly, in a non-altered and completely secure way. In concrete terms, to guarantee the liquidity of data, it’s necessary to:
- Ensure clear pathways between data collection and diverse possible end uses. APIs therefore play a fundamental role and are just as important as a tool’s processing and calculation capabilities, which are often too focused on.
- Avoid being closed into proprietary systems. The main leading systems naturally try to coerce their customers into closed ecosystems by promising greater fluidity, but with confines. It’s preferable to therefore opt for systems that are as open as possible. A currency whose usage is limited to the playground is not very powerful, no matter how big the playground is… Additionally – and this might seem a paradox – these closed systems are much more dangerous regarding Internet user privacy, as they multiply the risks of questionable cross-referencing of data. For anyone who knows the world of data, it’s clear that today, Google possesses a scarily private view of all Internet users on the planet (perhaps excepting users in China and Russia…).
- Give end users interfaces that are understandable and easy to work with. Data democratization is happening, and the progress in this domain has been amazing. But there is still work to be done to ensure efficient connections between tools for data collection, visualization and exploitation. This is often the chink in the armor of many tools – superb data visualization interfaces with data that is insufficiently reliable or consistent.
In conclusion, data can surely serve as the currency of the digital world, but it must be treated as such: We must be able to place confidence in it and guarantee its liquidity, consistency and longevity. We must also take into account its three monetary functions and not overlook its descriptive nature, at the risk of making its other functions counterproductive or even destructive.
Finally, let’s not forget that manufacturing money has always been a royal prerogative: Those who control the issuing and circulation of money also possess a vital power. Data governance is thus a major sovereignty issue. Outside of your company, it’s crucial to not give your external service providers (especially the Googles, Apples, Facebooks and Amazons of the digital world) unbridled rights to this wellspring of value. And within your company, those who control data access should naturally take on more strategic positions.