Is data the cheap­est asset available?

The phrase “data- the fuel of the 21^st cen­tu­ry” has often been bandied about and has become a catchy slo­gan for the dawn of the dig­i­tal rev­o­lu­tion. A huge amount of data is being gen­er­at­ed, col­lect­ed, and processed every sec­ond with every sin­gle click. But what is the data even worth? Who is pay­ing for such data and who receives remu­ner­a­tion? Or has data even become a “cur­ren­cy” for ser­vices per­ceived to be “free of charge”? 

In her Duet Inter­view with Dr Andreas Zech­mann, a spe­cial­ist in cor­po­rate finance, Dr Cal­daro­la, author of Big Data and Law, dis­cuss­es the val­u­a­tion of data and its cur­rent and future mar­ket price.

With the rise of the Inter­net of Things and the incor­po­ra­tion of sen­sors in objects, com­pa­nies are in a posi­tion to col­lect more and more data. Con­se­quent­ly, the amount of data is increas­ing. Back in 2018, the total data vol­ume col­lect­ed world­wide was about 33 zettabytes. Many data ana­lysts cau­tious­ly pre­dict that this data vol­ume may rise to a lev­el of 175zb by the end of 2025. So, one could say that there is an inter­est, to put it mild­ly, in data. Is data per­ceived as an asset col­lect­ed from data sub­jects and/or com­pa­nies? If so, is that asset being iden­ti­fied in account­ing regulations?

Dr Andreas Zech­mann: Due to dig­i­tal­i­sa­tion, the role of data has changed in both the pri­vate and eco­nom­ic life of human beings since data has per­me­at­ed all areas of life and industry.

You men­tioned the devel­op­ment of the world­wide data vol­ume. In my opin­ion, this trend shows the increas­ing impact of data on all of us.

The added-val­ue chain of com­pa­nies and their result­ing busi­ness suc­cess depend more and more on data. This is not only true for mod­ern dig­i­tal busi­ness mod­els, but also applies to tra­di­tion­al areas, such as, for exam­ple, infra­struc­ture com­pa­nies. I would even go so far as to say that data has become a strate­gic suc­cess fac­tor for companies.

To answer your ques­tion whether data is today per­ceived as an asset, I unfor­tu­nate­ly have to reply in the neg­a­tive: No, not to the degree that it should be. There is a strong imbal­ance, when look­ing at data as an asset. Why is that so? The answer lies in the nature of data.

When we speak of dig­i­tal data, we have to remem­ber that data has no phys­i­cal sub­stance which in turn means that data is intan­gi­ble. Data rep­re­sents infor­ma­tion on objects and sub­jects – for exam­ple, cus­tomers, ven­dors, mate­ri­als, machines etc. and fol­lows a life cycle (col­lec­tion – use – dele­tion). The ques­tion of how well data rep­re­sents infor­ma­tion on objects and sub­jects can be answered by look­ing at the qual­i­ty of its data.

The dis­cus­sion con­cern­ing the sta­tus of data as an asset is dom­i­nat­ed by the future prospects of cus­tomer and con­sumer data, because I think com­pa­nies are well aware that their cus­tomer and con­sumer data are undoubt­ed­ly assets, on which their future mon­e­tary suc­cess depends. Trade secrets, such as recipes like the for­mu­la for Coca-Cola, or pro­duc­tion meth­ods to cre­ate drugs, are per­ceived in the same way. But, when it comes to cor­po­rate data oth­er than cus­tomer data or trade secrets, my opin­ion is that com­pa­nies, for exam­ple, do not con­sid­er inven­to­ry data in their enter­prise resource plan­ning sys­tem as an (intan­gi­ble) asset – despite the inven­to­ry itself being con­sid­ered as an (tan­gi­ble) asset. I believe that the per­cep­tion of data as an intan­gi­ble asset is more pro­nounced in dig­i­tal indus­tries than in tra­di­tion­al (pro­duc­tion) indus­tries. It will be excit­ing to observe whether data is per­ceived in the same way as pro­duc­tion halls, machines and facil­i­ties in the years to come.

I def­i­nite­ly still need to answer your ques­tion as to whether the cur­rent account­ing rules per­ceive data as an asset and, once again, I must reply in the neg­a­tive. The rea­son is a his­tor­i­cal one, since cur­rent account­ing reg­u­la­tions were estab­lished in the ear­ly 20^th cen­tu­ry when there was a strong empha­sis on tan­gi­ble assets, such as machines or prop­er­ties, and intan­gi­ble but “trace­able” assets, like licens­es, rights, con­ces­sions and bonds. The con­cept of data, as we know it now, was not yet con­ceived of with­in struc­tures which had evolved much before the dig­i­tal revolution.

In addi­tion, the Inter­na­tion­al Finan­cial Report­ing Stan­dards (IFRS), that came into effect much lat­er, name­ly, in the ear­ly 21^st cen­tu­ry, bal­anced intan­gi­ble goods only as intan­gi­ble assets when a com­pa­ny could prove that the asset would pro­vide a future eco­nom­ic ben­e­fit stem­ming from its use. And that is the crit­i­cal point as far as the top­ic of data is con­cerned: to eval­u­ate and quan­ti­fy pro­duc­tion and acqui­si­tion costs. Con­se­quent­ly, a com­pa­ny’s data is not viewed as an intan­gi­ble asset either because its future eco­nom­ic ben­e­fits can­not be proved or because the mon­e­tary pro­duc­tion cost of self-gen­er­at­ed data can­not be quan­ti­fied, as is the case of com­put­er-gen­er­at­ed mass data, e.g., cre­at­ed by the use of sen­sors. I think can is rel­a­tive because it is sim­ply not done in practice.

In my PhD dis­ser­ta­tion, I con­sid­ered how to assess the val­ue of data gen­er­at­ed by a com­pa­ny in order to ren­der it into a con­crete asset for the com­pa­ny in ques­tion. My main argu­ment was that only data that is actu­al­ly used by the rel­e­vant com­pa­ny and is of high data qual­i­ty and pro­vides a pos­i­tive val­ue propo­si­tion for the com­pa­ny at the end of the added-val­ue chain, can thus be said to have a finan­cial value.

This then sets the stage for data becom­ing intan­gi­ble fixed assets which can be bal­anced and depre­ci­at­ed just like oth­er (tan­gi­ble) assets. I delib­er­ate­ly refer to “self-gen­er­at­ed” data because acquired data has a pur­chase price.

The mere pres­ence of data does not auto­mat­i­cal­ly ensure its finan­cial worth. Only data that is found to be of some use in the future can meet the cri­te­ria of being a data asset and be worth some­thing. A good exam­ple would be data con­cern­ing a cus­tomer who hasn’t pur­chased any­thing for 10 years, where the invoice address is incor­rect, or where the last pur­chased prod­uct is already out­dat­ed. I think this thought is con­sis­tent with the IFRS because, from the company’s point of view, this data will most like­ly not gen­er­ate any future mon­e­tary ben­e­fits; per­haps we can com­pare such data to per­ish­able goods from the food industry.

My opin­ion is:

 

“The mere pres­ence of data does not insure their finan­cial val­ue. Only data, which are in some way and at some time found to be use­ful, ful­fill the require­ments of being data assets and thus can be said to be worth some­thing, finan­cial­ly speaking.”

Dr Andreas Zechmann

In order to define data as an asset in accor­dance with account­ing reg­u­la­tions, data needs to have a mar­ket val­ue. How is or how can data (be) eval­u­at­ed and do com­pa­nies’ con­trol­ling depart­ments active­ly val­u­ate and mon­e­ta­rize the data? Is the process either tied to obtain­ing addi­tion­al prof­its or to cost savings?

As men­tioned ear­li­er, the acqui­si­tion or pro­duc­tion costs are rel­e­vant for the finan­cial val­ue of an intan­gi­ble asset. That means that the val­u­a­tion either results from the price that has been paid when the good was pur­chased or the cost that accrued when the good was man­u­fac­tured, for exam­ple, per­son­nel costs involved.

Let us con­sid­er soft­ware as an exam­ple and the ratio­nale behind this pro­ce­dure becomes clear: either it is the price of soft­ware when pur­chased or the cost for the pro­gram­ming of in-house gen­er­at­ed soft­ware; such things can be quan­ti­fied because the pro­gram­ming start­ed and end­ed at a cer­tain point.

The dis­cus­sion becomes more dif­fi­cult when data is involved: The eas­i­est and most objec­tive data val­ue would be the mar­ket price of a non-monop­oly mar­ket with sev­er­al sup­pli­ers. This would be fea­si­ble for cus­tomer and con­sumer data since such mar­kets exist, so that pur­chased cus­tomer data could be val­ued in line with the pur­chase price, as with any oth­er tan­gi­ble good and, of course, could depre­ci­ate over its life cycle. One could even eval­u­ate cus­tomer data in accor­dance with a poten­tial pur­chase price that a third per­son would have paid (so-called “mar­ket test”).

But what hap­pens with oth­er data that is typ­i­cal­ly self-gen­er­at­ed by the com­pa­ny and not acquired from a mar­ket, such as screws of a plant man­u­fac­tur­er? For self-gen­er­at­ed data a mar­ket test is not applic­a­ble, so that we must find alter­na­tive ways of deter­min­ing a finan­cial data val­ue. One pos­si­bil­i­ty is to quan­ti­fy the costs in the process used by a com­pa­ny to col­lect and main­tain the data in question.

But, at this point we leave the realm of objec­tive val­u­a­tion and enter into sub­jec­tive val­u­a­tion with the result that there is no plau­si­ble mon­e­tary val­ue for that data. It is obvi­ous that, for exam­ple, “cus­tomer base” data sets can be appraised based on their cost by dis­sect­ing the col­lec­tion process of a data set. For exam­ple, how many fields are includ­ed in a cus­tomer data set? How much time is need­ed to fill in these fields? How much is the hourly rate for the employ­ee in charge of fill­ing in the cus­tomer data? I would like to add this thought: if we have obtained a cost-based val­u­a­tion in this way, we still don’t have a con­tin­u­ous­ly increas­ing finan­cial asset just by col­lect­ing data; mean­ing that, even if a data set is copied a mil­lion times, the finan­cial val­ue of the data set and its copies would not increase by a fac­tor of a mil­lion. On the con­trary, it remains con­stant. In my opin­ion, cost-based finan­cial val­u­a­tion is only par­tial­ly applic­a­ble for data.

Con­se­quent­ly, if a mar­ket-price-based val­u­a­tion of data does not seem to be suit­able, the com­pa­ny should then, in my opin­ion, attach a val­ue that is in line with the advan­tages aris­ing from the data use. Sim­ply stat­ed, data that is often used and that there­fore sub­stan­tial­ly con­tributes to the added val­ue has a high­er worth than data that is not or only used sporadically.

In my PhD the­sis, I com­pared dif­fer­ent val­u­a­tion con­cepts and I came to the con­clu­sion that the finan­cial val­ue of data should arise out of a use-based val­u­a­tion approach con­sid­er­ing the rev­enues that a com­pa­ny could earn and the invest­ments that a com­pa­ny could save on through effi­cient process­es. Use-based means in this con­text that a com­pa­ny focuss­es explic­it­ly on the use of data in select­ed busi­ness process­es, e.g., the role of cus­tomer address data in an invoic­ing process of a com­pa­ny. High-qual­i­ty data has greater poten­tial to be used and be prof­itable through its effi­cien­cy than low­er qual­i­ty data. It must be admit­ted, how­ev­er, that data val­ue derived in this way is sub­jec­tive and not com­pre­hen­sive because of the spe­cif­ic process being focussed on. By look­ing at finan­cial data val­ues in this way, we have the advan­tage of the val­ue now being strong­ly linked to its use and thus being sep­a­rat­ed from the dis­cus­sion that mere­ly col­lect­ing data results in an intan­gi­ble asset because of accru­ing pro­duc­tion costs.

I would like to add that assess­ing the finan­cial data val­ue is not a means to an end. Val­u­a­tion is only a first step lead­ing to post-pro­cess­ing activ­i­ties. All meth­ods for eval­u­at­ing data should sup­port any post-pro­cess­ing val­u­a­tion pur­pose. At the moment, data val­u­a­tion has­n’t real­ly become com­mon in the finan­cial com­mu­ni­ty which is cur­rent­ly oper­at­ing accord­ing to tra­di­tion­al finan­cial Key Per­for­mance Indi­ca­tors. There are a num­ber of rea­sons for this, includ­ing, for exam­ple, the impor­tance of account­ing in cap­i­tal mar­ket communication.

Per­son­al data stems from data sub­jects and non-per­son­al data from objects owned by a pro­pri­etor or a group there­of. How­ev­er, only com­pa­nies are col­lect­ing data – whether of a per­son­al or an imper­son­al nature. They are invest­ing in infra­struc­ture for col­lect­ing and pro­cess­ing data and they are using the data of oth­ers for their inter­nal and exter­nal pur­pos­es. Is there any mon­e­tary exchange going on between the “data-own­er”, on the one hand, and the data-col­lec­tor and data-exploiter, on the oth­er. After all, we are famil­iar with trade of this nature for oth­er raw mate­ri­als that com­pa­nies purchase.

Your com­par­i­son between data and raw mate­r­i­al for busi­ness process­es is, in my opin­ion, very apt. Data has devel­oped from sim­ply being a raw mate­r­i­al to becom­ing an enabler of process­es and, from there, devel­op­ing into an enabler of prod­ucts and ser­vices and, even beyond that, to data as a prod­uct. This is a new dimen­sion which does not exist for tra­di­tion­al tan­gi­ble raw materials.

This devel­op­ment leads to an increas­ing­ly large debt imbal­ance with regard to mon­e­tary com­pen­sa­tion between data col­lec­tor, data own­er and data exploiter. In my view, when we omit social media plat­forms, where pri­vate per­sons offer their data free of charge, and there is a strong diver­gence among these three roles, then the prob­lem does not real­ly arise in a cor­po­rate con­text. Here the com­pa­nies them­selves occu­py, in my opin­ion, all three roles, so that the prob­lem of finan­cial com­pen­sa­tion does not arise. Nev­er­the­less, with regard to social plat­forms, such as, for exam­ple, Face­book, the data own­er / data sub­ject could be com­pen­sat­ed finan­cial­ly, even if we are only talk­ing about tri­fling amounts.

Basi­cal­ly, when dis­cussing data, the chal­lenge is that data can eas­i­ly be copied with­out accru­ing addi­tion­al costs. There­fore, deter­min­ing data con­trol is more dif­fi­cult than is the case for tan­gi­ble goods that can be secured (secure in the sense of not let­ting third par­ties into a ware­house) and can­not be copied. An essen­tial fea­ture of tan­gi­ble assets is their short­age: they are “valu­able” because they are not acces­si­ble to every­one and are some­how scarce. If one looks, for exam­ple, at freely acces­si­ble data, such as “open data”, the ques­tion aris­es as to who, if any­one, owns such data. To be sure, this type of data has a data sub­ject, but it still rep­re­sents, in my opin­ion, a free asset avail­able to all and belong­ing to no one. There­fore, I am not sur­prised that there is no mon­e­tary com­pen­sa­tion being dis­trib­uted among the dif­fer­ent roles.

Per­haps an exam­ple will make my answer clear: A pho­tog­ra­ph­er tak­ing a prizewin­ning pho­to of the Mat­ter­horn in Switzer­land does not pay the Can­ton of Wal­lis com­pen­sa­tion for the rev­enues he makes because his pho­to has been includ­ed in a com­mer­cial pho­to cal­en­dar. Every­body could take such a pho­to if s/he wants to. I view the inter­net in the same way: A com­pa­ny mar­kets data which every­one has access to. Every­body could do the same thing, but only a few actu­al­ly do, there­by earn­ing mon­ey with its usage.

Assum­ing that data has a val­ue attached to it, what are the actu­al mar­ket prices for data? Do spe­cial cat­e­gories and respec­tive mon­e­tary ranges exist? Are they sta­ble or do they increase over time? Can you pro­vide some examples?

I think the top­ic whether data is trad­ed on mar­kets is only rel­e­vant for data, for which suf­fi­cient prospec­tive buy­ers exist, such as, for exam­ple, for cus­tomer and con­sumer data. In my opin­ion, the going mar­ket prices for cus­tomer data sets offered by large infor­ma­tion ser­vice providers are in the range between € 0.5 and € 2.0, to name one exam­ple. But let me give you a coun­terex­am­ple with respect to our mar­ket dis­cus­sion: Only a few prospec­tive buy­ers exist for data relat­ed to load-bear­ing strength of con­struc­tions. Con­se­quent­ly, this data is unlike­ly to be sold or pur­chased. How­ev­er, for rail­way com­pa­nies this data is cru­cial for main­tain­ing their sys­tems and, there­fore, for their added val­ue chain. No train would move if infor­ma­tion from con­struc­tion data were miss­ing. My point here is that the dis­cus­sion on mar­ket price of data is only part of the whole dis­course con­cern­ing finan­cial data valuation.

With regard to finan­cial data val­ues, I would like to add that I have applied cost-based and usage-based approach­es for com­pa­nies. The cost-based approach gen­er­at­ed around 38 CHF for each mate­r­i­al mas­ter data at Swiss indus­tri­al com­pa­nies and between 11 and 30 CHF for each cus­tomer mas­ter data. When apply­ing the usage-based approach, the finan­cial val­ue amount­ed to about 36 CHF for cus­tomer data of a pow­er tool sup­pli­er and rough­ly 5 CHF for con­struc­tion data of a rail­way com­pa­ny for each data set. It is inter­est­ing to note that the val­ues for each data set quick­ly reach an asset val­ue in the range of dou­ble-dig­it mil­lions in cas­es of 100 000+ cus­tomer data sets. These are sig­nif­i­cant val­ues in the bal­ance sheet of an enterprise.

But com­ing to your ques­tion about price devel­op­ment, one must be clear about the fact that data is strong­ly con­nect­ed to its time­li­ness, mean­ing that obso­lete data, such as incor­rect infor­ma­tion about real objects, isn’t worth any­thing. Nobody would buy data that has “expired”. But I also believe that, as the data trade becomes more impor­tant, more mar­kets will grow, and the top­ic will receive more atten­tion, as dig­i­tal busi­ness mod­els become more essential.

Let me add the fol­low­ing thought with regard to the dis­tinc­tion between price and val­ue. The val­ue cor­re­sponds to the price only when the lat­ter cor­re­sponds to a mul­ti­tude of expec­ta­tions of the poten­tial buy­ers. If this is not the case, and, if only a few buy­ers exist, then the mar­ket price is one for a prod­uct offered on the mar­ket, but this val­ue is not a reli­able indi­ca­tor for an objec­tive mar­ket price.

Many dig­i­tal busi­ness mod­els work in the fol­low­ing way: a data sub­ject allows access and pro­cess­ing of his/her data and receives, in return, a “free” ser­vice. For exam­ple, a lot of peo­ple use “free” mes­sag­ing, email ser­vices or cloud space and, in return, let the provider use their data. Has data become a cur­ren­cy to “pay” for cer­tain ser­vices? Or is data the cheap­est, if not the smartest, “stolen” asset?

The idea that data is a stolen asset sim­ply mud­dies the water in terms of what the val­ue of data actu­al­ly is and what should be paid for it.

The fact is, data can be copied an unlim­it­ed num­ber of times if enough stor­age space is avail­able. Repro­duc­tion costs remain neg­li­gi­ble because capac­i­ties are so big.

If users pro­vide their data with­out remu­ner­a­tion and make use of a ser­vice at no charge to them­selves, an exchange has tak­en place, with the provider hav­ing got­ten the bet­ter deal since s/he can gen­er­ate rev­enues on his/her web­site through adver­tis­ing. In the strictest sense of the word, it is a fair “exchange” and not a theft. But if I go back to your ques­tion on data being the “smartest” stolen asset, then I have to agree that the user has most like­ly been enticed into pro­vid­ing his/her data at no charge for a “free” or dis­count­ed ser­vice. I assume the user is not aware of the fact that s/he has agreed to a barter trans­ac­tion or, if s/he is cog­nizant of the impli­ca­tions, that s/he has con­scious­ly accept­ed the deal.

An own­er of a mine usu­al­ly sells his/her raw mate­r­i­al or leas­es his/her mine to some­body so that the lease­hold­er can exploit the mine/raw mate­r­i­al. The own­er of a mine, there­fore, receives mon­ey either for the raw mate­r­i­al or for the lease. If we trans­fer this exam­ple to data, are data sub­jects receiv­ing mon­ey for their data? Or dif­fer­ent­ly put, should a data sub­ject con­scious­ly put a price on his/her data? Are there any busi­ness mod­els or cur­rent trends where data sub­jects can active­ly mon­e­ta­rize their data? Or do only com­pa­nies – data col­lec­tors – makes these sorts of com­mer­cial deals?

In my opin­ion, there is no con­scious data mon­e­ta­riza­tion tak­ing place on the part of data sub­jects / con­sumers / cus­tomers. We can­not even observe a trend lead­ing to any change in this sit­u­a­tion because our herd behav­iour always seems to be on the alert for free dis­pos­able inter­net-based ser­vices (e.g., mail­ing, YouTube), for which the provider earns adver­tise­ment revenues.

I could imag­ine con­sumers receiv­ing cred­it vouch­ers for tri­fling amounts for their data being fur­ther processed beyond the orig­i­nal trans­ac­tion. Also pos­si­ble is that con­sumers delib­er­ate­ly offer their data on plat­forms for mar­ket­ing and adver­tise­ment pur­pose, but also here we would still be talk­ing about pock­et change. In my opin­ion, data trade remains a bulk busi­ness where a huge amount of data is pur­chased with the knowl­edge that a cer­tain per­cent­age is use­less because it is obsolete.

For this rea­son, the pro­fes­sion­al mon­e­tari­sa­tion of data will prob­a­bly remain in the B2B sec­tor, even if the data own­er / data sub­ject does not par­tic­i­pate in the rev­enues accrued.

Not only pri­vate com­pa­nies col­lect and process data. In some coun­tries, gov­ern­ments are also col­lect­ing and using data – and not just to ful­fil their ser­vices and their secu­ri­ty oblig­a­tions. Do gov­ern­ment also “pay” or should they be offer­ing some form of remu­ner­a­tion for data?

I imag­ine you are allud­ing to the Social Cred­it Sys­tem in Chi­na. The sys­tem serves, in my opin­ion, to mon­i­tor the pop­u­la­tion and to reward some peo­ple for loy­al behav­iour. This is a spe­cial case that works in a “micro­cosm” of a total­i­tar­i­an state, such as Chi­na. The Chi­nese gov­ern­ment does not wish to gen­er­ate rev­enue through the trade of data.

Oth­er­wise, I can­not think of any oth­er exam­ples where gov­ern­ments delib­er­ate­ly col­lect data to mon­e­tarise or trade data. In my view, gov­ern­men­tal activ­i­ties should focus on ser­vices, such as edu­ca­tion, safe­ty, infra­struc­ture, main­te­nance of pub­lic life as well as med­ical and san­i­ta­tion services.

Dur­ing the pan­dem­ic, we have expe­ri­enced in a pos­i­tive way how gov­ern­ments can become a sort of data octo­pus that spreads its ten­ta­cles and sucks up all the data it can find for a con­crete pur­pose, in this case, for the Coro­na-Warn­ing-App. My point is that even this exam­ple is based on cit­i­zens being will­ing to pro­vide their data, which they do par­tial­ly because they believe their data is in safe gov­ern­men­tal hands. I don’t think the Coro­na-Warn­ing-App would work if cit­i­zens thought gov­ern­ments gen­er­at­ed trade by using per­son­al data. A breach of trust between cit­i­zen and gov­ern­ment would put the sys­tem of vol­un­tary data pro­vi­sion at risk and lead to gov­ern­men­tal data trade no longer functioning.

My final thought on this mat­ter is that gov­ern­ments should not trade data so that the ques­tion of pay­ing data sub­jects nev­er even comes up.

Yuval Noah Harari stat­ed in 21 Lessons for the 21^st Cen­tu­ry that: “Big Data algo­rithms might cre­ate dig­i­tal dic­ta­tor­ships in which all pow­er is con­cen­trat­ed in the hands of a tiny elite while most peo­ple suf­fer not from exploita­tion, but from some­thing far worse – irrel­e­vance.” and “It is much hard­er to strug­gle against irrel­e­vance than against exploita­tion.” Should a data sub­ject, there­fore, start to mon­e­tarise his/her data in order to active­ly shape his/her par­tic­i­pa­tion in the dig­i­tal mar­ket and to fight against the exploita­tion and irrel­e­vance of his/her data?

The ques­tion seems, in my opin­ion, to be rather sen­sa­tion­al­ist. You stat­ed, first of all, that there was a mar­ket for data sub­jects to mon­e­tarise their data and, fur­ther­more, that data sub­jects have access to this mar­ket. In my view, this sit­u­a­tion does not hold true due to the nature of inter­net-based ser­vices, since they are formed in a huge radius involv­ing reg­is­tered users, vis­i­tors and clicks. I do not think data sub­jects can par­tic­i­pate in this bulk busi­ness- par­tic­u­lar­ly because data sub­jects prof­it from this mech­a­nism, for exam­ple, post­ing of What­sApp at no charge as opposed to pay­ing for tex­ting. The spir­it of the inter­net – name­ly speed, sim­plic­i­ty and flex­i­bil­i­ty (e.g., Uber)- has its price: name­ly, the end-user pro­vid­ing his/her data at no cost; on the plus side for the end-user: ser­vices pro­vid­ed at no charge. Mean­while, what does the provider get out of it? Pos­si­ble rev­enues from the data trade minus the cost for the ser­vice provided.

Dr Zech­mann, thank you for shar­ing your insights on the val­ue of data.

Thank you, Dr Cal­daro­la, and I look for­ward to read­ing your upcom­ing inter­views with rec­og­nized experts, delv­ing even deep­er into this fas­ci­nat­ing topic.