Where are the tout­ed rev­enues com­ing from Big Data?

Has that label only become a catchy new adver­tis­ing slo­gan for com­pa­nies to show­case their sup­pos­ed­ly inno­v­a­tive pow­er? How much do com­pa­nies real­ly earn or save with data? How do the earn­ings rate in rela­tion to the expens­es for data pro­tec­tion (GDPR), infor­ma­tion secu­ri­ty as well as for the inevitable IT-infrastructure?

In her Duet inter­view with Richard Heil­er Martínez, cor­po­rate finance spe­cial­ist, Dr Cal­daro­la, author of the recent book Big Data and Law, dis­cuss­es the bot­tom line on the cor­po­rate earn­ings from Big Data.

The Sta­tista sta­tis­tics¹ show that Big Data rev­enue in Ger­many amounts to €6.4 bil­lion in 2018. Does this rev­enue lev­el jus­ti­fy the famous state­ment “data is the new fuel of the 21^st century”?

Richard Heil­er Martínez: I would not pay too much atten­tion to the 2018 rev­enue fig­ure of €6.4bn, with regard to Ger­many, not even to the US$40.8bn which sup­pos­ed­ly rep­re­sents the world­wide rev­enue derived from Big Data in 2018. Those rev­enue fig­ures pri­mar­i­ly com­prise pro­ceeds out of data sales or data usage rights col­lect­ed by search engines (for real estate, jobs, etc.) big dis­trib­u­tors and social media firms, which there­upon sell their col­lect­ed data to ser­vice providers and manufacturers.

Thus, what is not includ­ed in those num­bers are Big Data rev­enues direct­ly applied by the data col­lec­tors to their own sales or even to the stream­lin­ing of their inter­nal process­es, the lat­ter of which may pro­vide impor­tant cost sav­ings, numbers/figures which do not show up in any sta­tis­tic, not even in the company’s PyG under any spe­cif­ic head­ing. Any oth­er expla­na­tion could hard­ly account for the imbal­ance shown in your intro­duc­to­ry chart between rev­enue (€6.4bn) and loss (€102bn). For this rea­son, the pub­lished rev­enue fig­ure seems insignif­i­cant com­pared to what it may actu­al­ly be and what it may become in the very near future.

Anoth­er way of apprais­ing Big Data growth is by look­ing at the vol­umes of data col­lect­ed. Back in 2018, the total data vol­ume col­lect­ed world­wide stood at 33 Zettabytes (high­est in Asia, fol­lowed by North Amer­i­ca and then West­ern Europe). Many data ana­lysts cau­tious­ly pre­dict that this data col­lec­tion vol­ume could rise to a lev­el of 175 Zettabytes by the end of 2025.

It is not only cor­po­ra­tions col­lect­ing Big Data, but also gov­ern­ments gath­er­ing every kind of data on their sub­jects. The expres­sion “data, the new fuel of the 21^st cen­tu­ry” should per­haps not only be under­stood by look­ing at rev­enue fig­ures or data vol­umes. Big Data is a gener­ic term for defin­ing a grad­ual but quick process, which may com­plete­ly change and rev­o­lu­tion­ize our way of life, our way of pro­duc­tion, com­mu­ni­ca­tion, polit­i­cal sys­tem and will even­tu­al­ly affect every aspect of our pri­vate life. Though we are still at the very begin­ning of this process it will quick­ly become omnipresent. Those fore­bod­ings are also illus­trat­ed by many charts where the future rev­enue and col­lect­ed data vol­umes exclu­sive­ly point to an upwards trend, with annu­al world­wide growth vol­umes of approx­i­mate­ly US$10bn and 40 to 50 zettabytes respectively.

In the com­ing years, those growth rates will not show a lin­ear but more of an expo­nen­tial pat­tern. The rea­son for this devel­op­ment is sim­ple: It is sus­tained by the grow­ing dig­i­tal­iza­tion of our dai­ly lives and habits. The two main cat­a­lysts for fuelling the growth of Big Data col­lec­tion and usage in the dig­i­tal era we are cur­rent­ly liv­ing in are the “update­abil­i­ty” and the “con­nec­tiv­i­ty” with which the data is col­lect­ed, stored, updat­ed and moved around. Those two fea­tures, which did not exist in our for­mer ana­logue era, will be respon­si­ble for the expo­nen­tial growth rates of Big Data in the years to come.

Big Data will grad­u­al­ly seep into all our dai­ly lives. It may per­haps take anoth­er 10 to 20 years for this omnipres­ence to become per­cep­ti­ble. Nev­er­the­less, this is a self-accel­er­at­ing and self-engen­der­ing process which will pro­duce ever greater quan­tum leaps in improv­ing the con­trol sys­tems over the con­sumer and/or cit­i­zens and, final­ly, over all of us. Think of what it may become in 100 years. The lat­ter may seem like a very long-time span for a human mind yet, in evo­lu­tion­ary terms, this is just a split sec­ond. As soon as Big Data includes the realm of biotech­nol­o­gy, then its pow­er over us can be seen as vir­tu­al­ly absolute.

The enti­ties – whether cor­po­ra­tions or gov­ern­ments – know­ing how to best gath­er, store, analyse and use the Big Data of peo­ple will then be in a posi­tion to know people’s pref­er­ences, their dreams, their polit­i­cal con­vic­tions, their predilec­tion etc. They will, there­fore, know which car, which music, which med­ical treat­ment or even which polit­i­cal par­ty will best suit them. The dan­gers inher­ent to such a process are obvi­ous: Peo­ple will even­tu­al­ly hand over the “steer­ing wheel” of their lives to a small group of the soci­ety that con­trols gath­er­ing, admin­is­ter­ing and using the Big Data col­lect­ed on them. The lat­ter is iden­ti­cal to hand­ing over pow­er, influ­ence and mon­ey to a small part of society.

A quote when it comes to Big Data is from one of my favourite writ­ers, Yuval Noah Hariri, 21 Lessons of the 21^st Century

 

“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.”

Yuval Noah Hariri

For this rea­son, it is fair to state that with­in the next few years Big Data may cer­tain­ly be deserv­ing of its def­i­n­i­tion as the “fuel of the 21^st cen­tu­ry”, not only because of the rev­enues, but because of its all-encom­pass­ing con­trol over us. How­ev­er, at the moment, it may still be some­what dif­fi­cult to iden­ti­fy which por­tion of an enterprise’s total rev­enue may be ascribed to its use of Big Data.

Aldous Huxley’s Brave New World of the 1930s may even­tu­al­ly become true. Now is the time for soci­ety to reflect on what they want to do with the new tech­no­log­i­cal pos­si­bil­i­ties as well as where the legal – and per­haps also finan­cial and com­pet­i­tive – bar­ri­ers should be estab­lished to pro­tect the free­dom of indi­vid­u­als to avoid dan­ger­ous devel­op­ments with­in our mar­kets and gov­ern­ments. This dis­cus­sion can­not be avoid­ed, nor sim­ply placed in the hands of a small group of busi­ness lob­by­ists, nor hand­ed over to some gov­ern­men­tal agen­cies, and most cer­tain­ly can­not be left to some ran­dom sequence of devel­op­ment. This must be an open dis­cus­sion involv­ing all ele­ments of society.

Some sort of com­pro­mise between what is pos­si­ble and what should be allowed must be found. One aspect of such a com­pro­mise rep­re­sents the afore­men­tioned indi­vid­ual free­dom requir­ing a cer­tain lev­el of pro­tec­tion where­as the oth­er side of this bal­anc­ing act is rep­re­sent­ed by the will­ing­ness of our com­pa­nies to devel­op the skills need­ed for col­lect­ing and using Big Data with­in a rea­son­able legal frame­work. If we put too much empha­sis on pro­tect­ing the indi­vid­ual free­dom of peo­ple, the skills relat­ed to Big Data might end up in coun­tries and for­eign cor­po­ra­tions with more lax reg­u­la­tions and even­tu­al­ly push­ing our own cor­po­ra­tions out of this market.

As always, the dif­fi­cul­ty lies in find­ing the gold­en mean between the two extremes.

Which projects gen­er­ate this rev­enue? Which com­pa­nies pro­duce these rev­enues? If Big Data is the future to lucra­tive tak­ings, how are gov­ern­ments able to allo­cate their nation­al bud­get if data only par­tial­ly appears as rev­enue in finan­cial reporting?

Big Data will affect every­thing and every­one and will lead to a con­cen­tra­tion of indus­tri­al and eco­nom­ic pow­er. The big dis­trib­u­tors, media com­pa­nies and man­u­fac­tur­ers are already gath­er­ing all types of mea­sur­able data. Every “click” on the inter­net and all forms of con­sumer behav­iour are already being amassed and run through algo­rithms with one over­ar­ch­ing aim: Name­ly, to win and bind the client to their com­pa­ny, prod­uct or even polit­i­cal party.

Ora­cle, Microsoft, SAP, IBM, Ama­zon, Aliba­ba, Zalan­do, any search engine, Google, Face­book, LinkedIn, Tik­Tok and the like are the lead­ing com­pa­nies deal­ing in the col­lec­tion of data. Most of those com­pa­nies are head­quar­tered in the US and in Chi­na, where­as only SAP is head­quar­tered in Germany.

These com­pa­nies are rel­a­tive­ly young busi­ness­es. There­fore, it seems that the poten­tial for future rev­enue gen­er­a­tion, or, in oth­er words, the con­trol over the “well” to pump the fuel of the 21^st cen­tu­ry, is more like­ly to lie with those younger com­pa­nies. Old­er and more tra­di­tion­al com­pa­nies will have a hard time catch­ing up with these new trends and skills. In fact, it is not unlike­ly that many of these busi­ness­es might indeed dis­ap­pear dur­ing this era of Mod­ern Times and will per­haps regret that they are not watch­ing the famous and ever-pop­u­lar movie by Char­lie Chap­lin, but rather are being ful­ly exposed to the inex­orable and unfor­giv­ing laws of the market.

It is thus fair to assume that US and Chi­nese com­pa­nies will play a lead­ing role in the Big Data Mar­ket. Europe, unfor­tu­nate­ly, is like­ly to be rel­e­gat­ed to the sec­ond tier. This admis­sion is a painful one to make, espe­cial­ly if one feels Euro­pean with every last fibre of one’s being.

Europe’s only answer to this over­whelm­ing­ly Amer­i­can and Chi­nese Big Data dom­i­na­tion may well be to mere­ly levy a dig­i­tal tax which will be reg­u­lat­ed by the EU Com­mis­sion to help pay off some of the unsus­tain­able debt accu­mu­lat­ed by cer­tain governments.

Accord­ing to a study from Bitkom², the total loss due to IT sab­o­tage, espi­onage, theft and sim­i­lar amount in to €102.9bn in Ger­many alone. Accord­ing to that same study, the total amount spent on IT-secu­ri­ty in Ger­many amount­ed to €4.57bn in 2019. GDPR states in Arti­cle 83 that the fine due to a breach of the data pro­tec­tion law may cost a com­pa­ny up to 4% of its world­wide turnover. The­o­ret­i­cal­ly, when apply­ing this max­i­mum fine lev­el to the Ger­man GDP³, this would result in a the­o­ret­i­cal max­i­mum expo­sure lev­el of €137.42bn (com­pare Germany’s 2019 GDP which amount­ed to €3435.74bn) which core­lates quite nice­ly to the actu­al loss of €102bn⁴, as men­tioned above. On the basis of those fig­ures, do you think that the IT secu­ri­ty effort under­tak­en in Ger­many has been suf­fi­cient, or do you instead think that addi­tion­al resources should be made avail­able to pro­tect our IT sys­tems in Germany?

Invest­ments in data pro­tec­tion and IT secu­ri­ty have always been impor­tant and will become even more so – espe­cial­ly after the Gen­er­al Data Pro­tec­tion Reg­u­la­tion (GDPR) came into force, and the con­comi­tant high­er fines for data trans­gres­sions asso­ci­at­ed with it. Cor­po­ra­tions and gov­ern­ment agen­cies alike are increas­ing­ly exposed to hack­ers try­ing to ille­gal­ly acquire their sen­si­tive data.

My impres­sion is that our invest­ment in data secu­ri­ty is far too lit­tle, com­pared to what we should be doing. Just look­ing at the num­bers for Ger­many where the total IT secu­ri­ty invest­ment amount­ed to rough­ly. €4.6bn in 2019 while the loss suf­fered by IT secu­ri­ty leaks went beyond €100bn, shows that there is still much room for improvement.

With the aid of a sta­tis­ti­cal method, name­ly by using the cumu­la­tive prob­a­bil­i­ty func­tion of a Gauss­ian nor­mal dis­tri­b­u­tion, I have tried to illus­trate that the cur­rent Euro­pean invest­ment in IT secu­ri­ty is far too low.

On the basis of the Ger­man aggre­gate num­bers for 2019, the result – in no way sur­pris­ing – shows that the total invest­ment in IT secu­ri­ty should have been at least three times high­er than the amount actu­al­ly spent in order to obtain a rea­son­able, yet still imper­fect, secu­ri­ty environment.

While this is a very rough and pure­ly sta­tis­ti­cal esti­mate which does not con­sid­er any qual­i­ta­tive ele­ments con­cern­ing the actu­al expen­di­ture of the funds, such spend­ing analy­sis should ide­al­ly be a bot­tom-up analy­sis of qual­i­ta­tive ele­ments, such as train­ing IT spe­cial­ists as well as list­ing the best ways to cre­ate smart IT devices and soft­ware pro­grams to pro­tect the IT infra­struc­ture of the cor­po­ra­tions and coun­tries in ques­tion. The sum of all those pro­tec­tive mea­sures would give us a valid number.

Cur­rent­ly, with lit­tle data avail­able to us, it is not easy to secure an appro­pri­ate lev­el of pro­tec­tion. Most com­pa­nies do not even reg­is­ter their IT secu­ri­ty expen­di­tures under a spe­cif­ic rubric. This means they do not even know how much they have actu­al­ly spent in pro­tect­ing one of their most valu­able assets: their data. Cor­po­rate senior man­age­ment should be made aware of the sig­nif­i­cance of their IT secu­ri­ty and should thus make cer­tain that the nec­es­sary inter­nal account­ing and con­trol­ling pro­ce­dures have been duly imple­ment­ed in order to be able to iden­ti­fy what amounts have been spent on what type of IT pro­tec­tion and what gaps and short­com­ings still need to be covered.

Besides, in the very near future, our infra­struc­ture, includ­ing the sup­ply of basic needs, such as water and elec­tric­i­ty and even our struc­tures for traf­fic con­trol and sim­i­lar infra­struc­ture sys­tems, will grad­u­al­ly become depen­dent on “intel­li­gent” devices aimed at opti­miz­ing the offer to the con­stant­ly fluc­tu­at­ing con­sumer demand. Imag­ine what would hap­pen if those sys­tems fell prey to hack­er attacks. They would be able to par­a­lyze a whole nation. Thus, as such inter­con­nect­ed “intel­li­gent” devices start sup­port­ing our most basic require­ments, peo­ple will become increas­ing­ly aware of the need to estab­lish appro­pri­ate IT shields to fend off the inher­ent dangers.

Thus, upgrad­ing our IT secu­ri­ty will become a con­stant require­ment. Unfor­tu­nate­ly, the pace with which cor­po­ra­tions and gov­ern­ment agen­cies upgrade their IT secu­ri­ty sys­tems gen­er­al­ly lags behind the speed with which smart hack­ers enhance their illic­it methods.

Have the sources of data already been ful­ly exploit­ed in order to dig up the data trea­sure? Can data already be giv­en the attribute of cash cows? How many invest­ments in data pro­tec­tion, cyber­se­cu­ri­ty, IT infra­struc­ture etc. need to be made and how many data need to be man­aged in order to become prof­itable? How long will it last to reach the laud­ed Big Data potential?

All poten­tial data sources are by no means being ful­ly exploit­ed at the moment. There are innu­mer­able dif­fer­ent data sources and data com­bi­na­tions. Much of the data need­ed to gain a com­plete and clear under­stand­ing of what a cor­po­ra­tion is look­ing for may not even have been col­lect­ed so far, due to legal and tech­ni­cal restric­tions. Fur­ther­more, the skills required to read, com­ple­ment and under­stand the data may dif­fer great­ly from one com­pa­ny to anoth­er. The same data may offer a com­pet­i­tive advan­tage to one com­pa­ny while being of absolute­ly no use to anoth­er one. Thus, we can affirm that Big Data is cer­tain­ly not a cash cow yet.

How­ev­er, the abil­i­ty to gath­er and use client data will soon be a skill which will be trans­formed from a “nice to have” to an absolute “must-have” abil­i­ty as far as com­pa­nies are con­cerned. Nobody will ask how much of the cor­po­rate total rev­enue was derived from the use of Big Data since the entire capac­i­ty of a busi­ness’s abil­i­ty to gen­er­ate rev­enue may soon depend upon its abil­i­ty to gath­er, read and employ cer­tain aspects of client data.

How impor­tant is Big Data for new inno­va­tions of the West­ern world – espe­cial­ly Ger­many? Are dis­rup­tive inno­va­tions nowa­days the cen­tral – if not the only – approach to rais­ing the GDP?

Yes, they are. Our devel­oped soci­eties are look­ing for a new type of dis­rup­tive inno­va­tion to keep on gen­er­at­ing growth for their respec­tive populations.

Dig­i­tal­iza­tion may pro­duce this dis­rup­tive effect. Para­dox­i­cal­ly, it may also be due to dig­i­tal­iza­tion that more peo­ple are put out of than into work. Fac­to­ries, stores and even trans­porta­tion may be able to oper­ate with few­er staff, turn­ing peo­ple into an irrel­e­vant mass pos­sess­ing only one sin­gle use: that of being a mere consumer.

Or will the reverse sce­nario come to pass: Will dig­i­tal­iza­tion require more peo­ple (to be sure, they will be high­ly spe­cial­ized and trained) to cre­ate, run and improve all this exu­ber­ant pletho­ra of IT infra­struc­ture? We will cer­tain­ly see the result with­in the next few years.

Anoth­er way of cre­at­ing a dis­rup­tive growth effect on the econ­o­my may come from the elec­tri­fi­ca­tion of var­i­ous means of trans­porta­tion or inte­grat­ing green hydro­gen in them which in turn leads us away from a com­bus­tion engine. This is cer­tain­ly anoth­er inter­est­ing top­ic to be dis­cussed in a fur­ther interview.

Until now, we have instead wit­nessed the Cen­tral Banks gen­er­at­ing mon­ey out of “thin air” in their attempt to keep the wheels of the econ­o­my turn­ing and to finance the myopic and irre­spon­si­ble deal­ing of many gov­ern­ments trapped in an unsus­tain­able debt. The lat­ter may serve as a pro­hib­i­tive imped­i­ment to the future of the next gen­er­a­tions as well as con­sum­ing the pen­sions of this gen­er­a­tion in the process. If those inven­tions do not make their appear­ance some­time soon, we will be fac­ing very dif­fi­cult and chal­leng­ing times indeed.

Richard, thank you for shar­ing your insights on Big Data and so amply con­tex­tu­al­iz­ing the now famous expres­sion “data is the fuel of the 21^st cen­tu­ry” by expand­ing and clar­i­fy­ing what actu­al rev­enues entail.

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

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¹ Dossier Big Data Sta­tista, Release Sta­tista 2020: https://​www​.sta​tista​.com/​s​t​u​d​y​/​1​4​6​3​4​/​b​i​g​-​d​a​t​a​-​s​t​a​t​i​s​t​a​-​d​o​s​s​i​er/
² Spi­onage, Sab­o­tage und Datendieb­stahl – Wirtschaftss­chutz in der ver­net­zten Welt Stu­di­en­bericht 2020”: https://​www​.bitkom​.org/​s​i​t​e​s​/​d​e​f​a​u​l​t​/​f​i​l​e​s​/​2​020 – 02/200211_bitkom_studie_wirtschaftsschutz_2020_final.pdf
³ Gross Domes­tic Prod­uct (GDP) in Ger­many from 1991 to 2019, Sta­tista 2020: https://​de​.sta​tista​.com/​s​t​a​t​i​s​t​i​k​/​d​a​t​e​n​/​s​t​u​d​i​e​/​1​2​5​1​/​u​m​f​r​a​g​e​/​e​n​t​w​i​c​k​l​u​n​g​-​d​e​s​-​b​r​u​t​t​o​i​n​l​a​n​d​s​p​r​o​d​u​k​t​s​-​s​e​i​t​-​d​e​m​-​j​a​h​r​-​1​9​91/
⁴ Mehr als 100 Mil­liar­den Euro Schaden durch Cyberkrim­i­nal­ität, 11. Novem­ber 2019 https://​indus​trie​.de/​i​t​-​s​i​c​h​e​r​h​e​i​t​/​1​0​0​-​m​i​l​l​i​a​r​d​e​n​-​e​u​r​o​-​s​c​h​a​d​e​n​-​c​y​b​e​r​k​r​i​m​i​n​a​l​i​t​a​et/

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