RECRUITMENT will disconnect from your location [2021 trends]

The interesting part about WIRED 2021 trends is that they click into each other, reinforce each other much more than was usual in the previous years. That is also reason why teleworking norm, introduced (somewhat harshly) by pandemic lockdowns, has one more side effect: Recruitment will disregard your location.

This trend completely relates to my experience of last months. Once your LinkedIn profile gets some (thousands) visitors’ traffic per month, it is normal to receive few offers every now and then.  What stunned  me, though, how many of them were from locations completely unrelated to even continent I dwell on now. (Including one from F_____, social media company. No, not the Fwitter) The argument went “You can start completely remotely and later we decide if you want to move here”. And it all makes hack of the sense. I spent less than 10% of 2020 in my office. Thus, the 90% of my year could have been contracted equally easy for Kuala Lumpur, Sydney or Montevideo as it was for Berlin.

But carefully, that coin comes with two sides! For besides, you can work for your dream companies which reside in countries you would never move to, this trend also means your competition gets much fiercer. When all the sudden your location becomes back-seat to your skills or experience, you compete with, quite literally, anybody on earth (having computer access). So you better be one of the best ones or you might not qualify for next round of the hiring game. There is still time to think about it. Or to take benefit of fact you are in top tier in your area.

Ultimately this will lead, most likely, also to erecting of new “digital work only VISA”, where you will be allowed to work in (e.g. Shengen) zone, but would not gain permanent residency or even travel permit into area per se. See how we are converging to state repositioning again? Yes, terrific governments have much to win in next years.

 

 

We agree to PAY to be FREE OF ADVERTS [2021 trends]

Observing the user trends, experts suggest that world’s love affair with free online services might be coming to its end. Even the most naïve users grasp the idea that free-for-me means that provider of the service has to live out of advertising (or selling user data), both annoying enough to take few bucks out of wallet to silence it.

There are also benefits on provider’s side to dump the ad-based model and go with “just pay for this, please” alternative. In order to dwell on the advertising model, companies need to invest a lot in setting, maintaining (and defending against data privacy regulators) tracking of the users. If that accounts for significant part of your cost-base, dropping altogether brings the needed break-even price of service much lower. So maybe you try?

Few quarters back we have seen already rise of the newsletters and online publishing platforms that strive to deliver high-quality, ad-free, paid content. Even web-search can become paid, to ensure you really get impartial info (and are spared from revealing what you have been searching for). If this comes from companies like Neeva, launched by Sridhar Ramaswamy, former SVP of Google Ads, you should watch the trend closely. Free services build our habits to have the info (for free). Now we finally mentally cracked through hurdle of throwing euro here and there on having those services “ourway”. If your business lives off advertisement-fees or your user acquisition stems heavy from advertisement, mind the ad-free gap, please!

 

 

 

STORY-telling moves to PHONES [2021 trends]

Pointing out that having mobile optimized content feels like suggestion from 5-10 years ago. Yes, in all the areas where customer was proactively trying to get something (think E-commerce or just News), content has been adjusted to be (almost) mobile-first. But hold-on, how about content that was telling stories and/or trying to teach something?

Pick Fairy tale or Crime story. Now try to reach back in your memories: How did you learn the story first place? Yes, when it comes to stories and narratives, the dominant media are still literature, cinema or television. All of them trying to catch their teeth on mobile, but – honestly – hardly mobile-first experience. That is just about to change.

Text stories, fiction and other story-telling is moving from “static content to view” into “interactive content you can shape”. Apps like Episode or Choices that offer exactly that kind of content are gaining daily users by millions ! But next step-up in the industry is only just about to happen. German studio Everbyte is preparing interactive thriller series Duskwood for mobile rendering only. Moreover, Electric Noir Studios already released Dead Man’s Phone crime series, where the spectator actually takes active role of the detective investigating the murders through victims’ smartphones, even including Zoom calls to lead interrogation of potential villains (played by yet other users).

Interestingly this entertainment segment seems to be skewed more into female audience, who happen to be power users of these apps more often than their male counterparts. Thus, it might be promising marketing vehicle of future, as well. Mobiles hunger to grab our lives one piece at time. Will storytelling become mobile-first, same way we google things out of phone on party? Maybe. 2021 will tell more.

Let me make here one more personal note. Even though this trend takes story-telling in a bit narrower sense, the idea to transform my MightyData blog has been bubbling in my head for some time. Nudged by few other things, I decided to give it a try and format 2021 blogs into shorter (few paragraphs) read-bites. If you noticed, the 2021 trends are actually first attempt on move in that direction. (previous years’ trends have been monolithic blogs). If you are regular user of, in few months’ time I would shop for your feedback on if this feels more natural or the contrary. But until then, I keep it short. So, mic out, here.

 

 

 

CONSPIRACIES take refuge into ALT-TECH [2021 trends]

The fact that conspiracy theories have been gaining more and more traction is equally obvious as the COVID was main topic of 2020. Actually, those two topics have been reigniting each other heavily (with peek for me being internet discussion suggesting that new COVID vaccine will be administered through 5G towers and they need to be destroyed).

As if consequences of these gibberish non-sense itself were not troubling enough, there is another dangerous trend to spot. The ever-increasing heat of info-war is now potentially to marry other mega trend into explosive and deadly mixture.

You may or may not have come across the term Alt-tech. Sparing you with too much of the details, Alternative-Tech scene (or Alt-tech) is movement that tries to create alternatives to digital Goliaths of Google and Facebook type. The underlying motivation behind building alternatives to digital mega services is to “bring back freedom to internet” (read as addressing whatever injustice the big players had done to internet life in their rise to dominance). Free speech and anit-censorship is most often cited propeller of the movement. The argument goes that you can’t really access if Google search is returning the right thing if there is no real alternative to, ehm do you hear me saying, “googling” first place.  One of the typical “comparing banners” is attached here:

[Disclaimer: Author if this blog does not subscribe to Alt-tech movement, this article is just to point out its mere existence]

The dangerous part of the story is that Alt-tech can serve as refuge for the conspiracy and fake news scene. While it is – by design – less (or not at all) regulated, with everybody pretending rom mind his/her own business. It is also less prone on protecting the identity of its users (= we might not even know who is really behind that content). And that feels exactly as environment suited for conspiracy movements. No matter that some of the pro-Trumpian, anti-vaccination, 5G-abolition or COVID-denial groups started to self-organize in this media. With less oversight these messages mushroom faster than in (to some extent) fact checking main steam. As a result, alt-tech is both likely to get poisoned by conspiracies and give enough oxygen for their social media fires. Admittedly, a bit scary dot at the end of our 2021 trends overview.

 

 

What KIND of COVID TEST would you CHOOSE to take?

You may be surprised by this question. Because most of us have at most a choice between whether to take the test or not. (Some of them still have bad luck in this as well.) And the idea that at the testing point they will place several different boxes in front of you and offer you a choice resembles more of a street gamble scene with three cups and a ball under one of them. But close your eyes for a moment and try to imagine that you could really choose: By what criteria would you choose the test? Fastest? What’s the least painful?

I think most of us would choose the most accurate test possible. But that’s exactly the trap of the debate. As you will learn soon, each test has by its very nature 4 metrics of “quality”. So if you say you want a test with 99% “measurement quality”, without a deeper insight into matter, you can end up with 4 completely different tests that each are 99% “accurate”. (In addition, each time you repeatedly test the same person, you will get a completely different positive / negative share of among the tests). Therefore, this blog explains which of the 4 metrics will be most important to you and how high the metric value should be. The blog also explains why I solve this quality dilemma on a daily basis, though I don’t work with COVID tests at all. But let’s save that matter until the very end of this text.

10 yearsBefore I fulfill the above-mentioned promise of initiating you into testing accuracy, please allow me two short, personal notes. I have had this blog in progress for several weeks by now, but this week’s statement by the Slovak government that it wants to test the entire Slovak population (by antigen tests) has pushed me to finish it quickly. I believe that the information from blog(s like this) will be important for the discourse of the coming days (and one’s decision on whether to take part or not in this population test voluntarily). The second personal point is that today it is exactly 10 years since I started writing blogs! Unfortunately, there was no cake with candles. But as you can see, I celebrated blogging anniversary with, ehm, blog work. I can’t promise to keep myself blogging for another 10 years. But I’ll do my very best to make this (295th) blog, as interesting and inspiring a read, as more than half a million unique views of my previous blogs were. Now back to the tests.

4 success metrics

When we deliberate how well things works, we usually think in terms of % reliability. If we find out that something works at 90% (or more) percent, we usually stress down. It doesn’t occur to us that we should seek any other metrics of success. We simply expect it to turn out well in roughly 9/10 cases.

Therefore, the revelation that there are some other measures of success of a product or service, and even that there are 4 of those metrics, might seem like fate’s irony or pointless meticulousness. This confusion in our head arises from fact we do not look at things strictly in factual basis. Often, we forget that the very real state of something we aim to study may not be known; and we try to guess the real state out of someone’s observation. Such situations are common in our lives: think you and classmates playing in a school yard. Some of you broke a window and a class teacher comes to solve this window issue. 4 possible scenarios could occur: You didn’t break the window, but you still got rebuked by the teacher; you broke the window and were rebuked justifiably, but equally the possibility is that you broke the window and unfairly escape reprimand, or you did not break the window and was not rebuked. So if someone (in our example, a class teacher) tries to solve the case of a broken window, suddenly she has several goals to deliver: to reveal the real culprit, not to blame other children, but to make it clear that this is unacceptable to repeat again, …

No less of confusion it is even in science, when measuring or testing things. This is also evidenced by the fact that the scientists themselves named the method of solving such situations as the Confusion Matrix. Its simplest form looks like this:

In principle, it is a 2-by-2 chart (the wiseacres would say that it can be more than 2-by-2, but let’s not meddle it here). One dimension is the real state of affairs (he broke the window, he really has COVID, he really murdered, …) and the other dimension is what the test / observation / estimate said about the state (he was reprimanded, the result of the COVID test, the court found person guilty …). Combinations of these two dimensions create 4 possible states:

True Positive (TP) = a person to whom the test correctly estimated that a given phenomenon actually occurred to him (eg justly convicted)

False Positive (FP) = a person who is actually negative but the test falsely accused him of being positive (eg falsely accused innocent)

True Negative (TN) = A person who has been correctly estimated by a test to be truly negative in a given phenomenon (eg, justly acquitted)

False Negative (FN) = Wrongly marked as negative = a person who is actually positive, but the test did not reveal it and claims to be negative. (eg wrongfully released real offender)

By the nature of the matter, of course, we don’t mind TN and TP, because they marked things correctly. The fields of FN and FP are confusing the matter. However, for the correct assessment of the “quality of the test”, mutual relations among the 4 possible outcomes are also important. As result the following 4 metrics arise to enable complete assessment of the situation:

Overall accuracy =  the ratio of those for whom the test guessed their true state correctly, thus = TP + TN / (FP+FN+TP+TN)

Sensitivity = (Recall ) = Detection rate for those whose test really should have revealed the phenomenon = TP / (TP + FN). With 100% sensitivity, the test revealed everyone who was tested and was really positive. At 50% sensitivity, the test “forgot” to mark every second truly positive.

Specificity =  Rate of correct marking of negative in those being with negative test result = TN / (TN + FP). With 50% specificity of the test, half of the negatives are erroneously marked as positive.

Predictive power of positive test = (Precision ) = Probability that the person is positive, if the test said so = TP / (TP + FP).

(The little secret of more informed is that there are actually more than 4 metrics, but the other (not mentioned here) metrics can be derived from most common (and here mentioned) 4 ones)

How to chose the proper test?

So what? Do you already have your favorite of the 4 metrics listed? If you think it is enough to have a high overall accuracy, you are dangerously wrong. Try the following example: You have 2 lie detectors, both of which are 90% successful in overall. However, detector A has the remaining 10% on top of the successful readings in the FP box and detector B has them in the FN box. In terms of overall success, you should not care about what you want to be examined on. However, the essential difference between A and B is: Whenever detector A is unsure, it will identify you as guilty, while B whenever it gets unsure will label you as innocent. So what? Still don’t care which one to take?

The whole selection matter gets complicated by the fact that different social processes/decisions require an emphasis on different metrics of success. With the broken window mentioned, the class teacher will probably primarily aims that this act does not go unpunished. (for moral reasons) Therefore, if the children deny the responsibility each and they try to cover each other, then teacher will (threaten to) punish all involved. In doing so, she is guided by maximizing the Sensitivity even at the cost of a low Predictive power of the positive. In other words, we prefer a few unwarranted reprimands over leaving anyone unpunished for a broken window.

On the contrary, Sensitivity is often the most important consideration in medicine (undetected internal bleeding is worse than incorrect suspicion of it), but for tests that lead to surgery, chemotherapy or other irreversible procedures, Precision is also very important. Having an unnecessarily amputated limb or a torn tooth is also not a top notch health care.

On the contrary, the presumption of innocence in our justice system is a pure focus on Specificity even at the cost of low Sensitivity. In other words, 10 acquitted criminals rather than 1 unjustly convicted. How painful to accept this is has surely experienced any democratic community.

To elicit correct decision, it is necessary to say what happens to testing if, some of test quality metric(s) are weak. If a decision-making process has a low rate of Positive Predictive Measure, it means that many people have been falsely identified as positive and this will significantly undermine the credibility of such a process (people will not complain if they are mistakenly declared innocent, but will revolt if many marked guilty are innocent, matter-of-factly). On the other hand, low sensitivity means that if something is to happen as a consequence of a positive test (eg treatment), many people will not get that, even if they deserve/need it. Thus, the costs and consequences of undetected cases kick-in. This might mean also as tragic things as unnecessary deaths in healthcare, or more preventable infections. Low Specificity, in turn, leads to unnecessary exposure to the consequences of a positive test, whether in the form of unfair imprisonment, unnecessary treatment, and stress for people who are labeled as (sometimes even terminally) ill, though they are super healthy. What is more, it might also lead to unnecessary financial waste (for example, when granting discounts or deciding to whom to send a offer letter with costly sample item). Finally, the low overall accuracy is bad in itself and says that you probably have the wrong test, first place.

What to take out of it for COVID testing

The development of the COVID pandemic has so far brought 3 basic types of COVID tests to the table. They differ not only in their testing approach, but also, unfortunately, in which success metrics they emphasize. But it is not the negligence or malice of their creators. Simply given tests are intended for different situations, where this or that metric of success plays a unique(ly important) role. For your basic orientation, I compiled a table with 3 basic types and their success metrics:

A cursory glance at the table shows that the overall best accuracy is achieved by PCR test and their Antigenic cousins (selected for mass SR testing) have the worst scores. To stay on the correct terms, it must be said that antigenic tests are the only tests with which such a extensive population testing can be physically performed. It would take more than a month to evaluate PCR tests for the whole country (even with the effort of all forces and foreign help) and cost would mount to at least 10 times more than Antigen-variant. Antibody tests would be cheaper and more feasible than PCR, but their primary goal is to confirm the course of COVID disease in suspects who have been infected for at least 2-3 weeks (which is not exactly a tool to isolate and prevent the spread of the virus). Given the possibilities of the government, it cannot be concluded that they chose antigenic tests (in reality, there was no real, feasible option). However, mass testing in Slovakia with this tool would mislead about 80,000 households as to whether or not they have COVID. Almost 50,000 of them would have the virus and be reassured that they don’t and they can do everything the old way, after all, they had a negative test. If you live in an 8-storey block of flats, on average at least one family in your gate would be quarantined undeservedly. Whether you should join this government mass testing action (if you have a choice, first place), I will leave to your discretion. So far, the risks of participating in such a test have been little pointed out (eg waiting in line with potentially infected people, traveling to the testing site, …), but their real impact will depend on how the whole event is logistically organized. Up to now we have only heard that “it will be like elections” on the logistics account. Well, if all this is to make impact, it remains to be hoped at least for elections other European Parliament vote (where Slovakia has about 20% turnout). When deciding whether or not to go, I especially wish you calm head and a bit of common sense. I hope this blog also gave you some more food for thought. If you still have 2 minutes more, the next paragraph depicts how interestingly I come into contact with above stated 4 metrics of success at my work.

 

What does it all have to do with my job

For regular readers of themightydata.com, I bring a few more lines about what are the most important conclusions from Confusion Matrix for our work with data. Majority of models predicting behavior have the nature of (binary) classifiers = indicating whether something is this or its opposite. However, that means that classifier essentially resemble (COVID) tests. Hence, the above 4 metrics of success also come into play when deciding which prediction model to deploy in the final production. Most beginners make the mistake of looking only at Accuracy metric. This is probably due to the fact that it is the default metric in many model evaluation statistical packages. Those slightly more advanced recognize that in reality picking the right production model is more a fight of Precision versus Recall. Why so? Models are usually quite confident in apparently positive and apparently negative individuals. Their issue remains where to lean in the middle unclear opinion waters (do you still remember lie detectors A and B?). However, what often confuses even the advanced analysts (don’t worry, after all it’s a Confusion Matrix :), that in some models Recall is more important than Precision. Have some doubts?

Well, imagine a model that tries to predict the churn of clients to offer them some small relief and persuade them to stay with our customers. For such a model, it is much more dangerous if it does not identify some actually departing clients rather than if it undeservedly labels some satisfied clients as churners. Therefore, optimizing the model for Recall is much more important here than taking care for Precision. On the other side of the coin, if we do an X-sell campaign where we send a free product sample, good Precision may be more important than Recall. If the campaign is successful (a large percentage of contacted purchases), we will easily get the budget to extend into next round that campaign (which will also address those (wrongly) marked as less likely to buy). But if we (due to low Precision) in first wave of campaign rather send an unnecessarily large volume of product samples (in attempt to capture everyone), the campaign will be immediately in red numbers, considered a loser and spared of chance to correct for that.

That is reason why I have to regularly decide in my work which of the 4 success metrics we will optimize for. So, similarly as with COVID tests, we strive to choose the greatest good, or at least the least evil. This can only be done, of course, only if you inspect all the Confusion matrix metrics for every prediction model; which I would strongly like to encourage you to. On top of it, comparing FP, TP, FN and TN groups can also provide hints on how to improve the model itself. But that’s something for separate blog post next time. Thanks for reading that far and make smart choices of (not only) WHICH COVID TEST would you take! Stay Healthy!

 

 

KNIHY, ktoré ma NAJVIAC POSUNULI v 2020

Ľudia, čo ma poznajú dlhšie, vedia, že na označenie knihomoľ sa nemôžem príliš urážať. Čítam naozaj rád (a pomerne veľa). Avšak len tí najbližší vedia, že si dávam každoročne predsavzatie prečítať za rok viac ako 10 000 strán kníh (nad rámec iných zdrojov ako časopisy, blogy či novinové články.) Za posledných 11 rokov sa mi nepodarilo tento záväzok splniť iba raz. Tohto roku sa mi darí podozrivo dobre (musím si zaklopať), zhltol som už 32 kníh. Aj keď čitateľský výsledok zachraňovala najmä letná dovolenka. Počas prvej vlny Korony totiž séria COVID článkov (s viac ako 30 000 slov) tu na Mocnedata blogu pohltila celú moju energiu. A tak knihy boli ten prepotrebný recharge.

Knihy, ktoré si kupujem, starostlivo vyberám. Vďaka tomu tie príjemné prekvapenia výrazne predbiehajú sklamania. Kníh však stále vychádza (na svete) veľa a tak nájsť tie skutočné poklady naozaj vyžaduje určité úsilie. Rozhodol som sa preto podeliť s Vami o to najlepšie, čo postretlo mňa zatiaľ v roku 2020. (Na oddych čítam aj knihy, ktoré sa vecne do okruhu MocneData tém nehodia, zhrniem tu však iba tie, ktoré predpokladám, že by mohli byť inšpiratívne aj pre čitateľov MocneData.sk portálu):

Competing In The Age of AI

Zameranie: Dáta, Dátová Analytika, Biznis

Kníh o algoritmoch Umelej inteligencie a ich aplikovaní nájdete neúrekom. Ako to už býva, ako náhle je nejaká téma super populárna, mnoho autorov sa chce zviesť na vlne. To je dôvod, že väčšinu AI kníh, ktoré dnes dostanem do rúk, po preštudovaní obsahu (a začítaní sa do pár kapitol) sklamane vrátim naspäť do police kníhkupectva. Šliapnuť vedľa nie je aktuálne vôbec ťažké. Táto kniha ma však, naopak, úplne pohltila. Doručí totiž presne to, čo sľubuje jej nadpis. Systematický návod, ako zaviesť AI do akejkoľvek firmy či organizácie. Vysvetľuje princípy, ktorých sa držať, ponúka checklisty aspektov, na ktoré netreba zabudnúť. Nenájdete tu žiadne floskule alebo helikoptérové rady. Aj dielčie kroky sú jasne štrukturované a hneď na začiatku naozaj uvidíte, kde sú hlavnné miesta pre zasadenie AI riešení vo vašej konkrétnej firme. Text je navyše tak písaný, že sa nebudete vedieť dočkať dalšej kapitoly, aby ste pochopili, čo má byť tým ďalším kúskom mozaiky. Na základe inšpirácií z tejto knihy som napísal pre top manažment našej firmy plán AI inovácií na ďalšie roky.

Link: https://www.amazon.com/dp/1633697622/

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Astrophysics for People in a Hurry

Zameranie : Vesmír

Ak sa hrá futbalový zápas, tak v hľadisku je každý elitným trénerom a futbalovým expertom. A keď sa začne disktuovať o vesmíre, každý sa kasá vedomosťami z čias, keď Pluto ešte bolo (mylne) považované za planétu. Darmo, rychlokurz geniality sa v astrofyzike robí naozaj ťažko. NeiL de Grasse Tyson sa však k tomu priblížil tak blízko, ako to ide. Ako už samotný podtitul naznačuje, rozhodol sa totiž napísať knihu o vesmíre pre ľudí, ktorí nemajú čas (si skôr trpezlivosť) prelúskať sa buchlami, vzorcami či záplavou vedeckých článkov. A urobil to naozaj bravúrne. Kniha je písaná tak, že neodradí od dočítania ani úplneho laika (ktorého fyzika mátala už v škole.) Navyše, posunie vašu mieru poznania vesmíru o toľko ďalej, že nepohoríte ani na prvom rande s astrofyzičkou/-fyzikom. Naozaj jedna z tých kníh, čo stojí za hriech. Vyšla dokonca aj v slovenčine, tak prikladám link na obe jazykové mutácie

Link [EN]: https://www.amazon.com/dp/0393609391

Link [SK]: https://www.martinus.sk/?uItem=275877

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Dark Data

Zameranie: Dáta, Dátová Analytika

Nie, toto nie je kniha o cyberzločine, či mapovaní Tmavej enmergie či Tmavej hmoty. Nie je to ani kniha o čiernej mágií. Aj keď vlastne možno …

Dátová analytika je neraz tak trochu aj mágiou. David J. Hand však komunite dátových analytikov (a s dátami pracujúcich ľudí) urobil veľkú službu. Systematicky totiž zhrnul 15 rôznych dôvodov, pre ktoré nemáme dáta kompletné či dostupné pre analýzu. (Čoho dôsledkom je legendárny GIGO efekt.) Tá podstatnejšia časť posolstva, ktorú sa aj ja snažím často vysvetliť (hlavne) začínajúcim dátovým analytikom, je: Za koľko z tých 15 dôvodov si môžeme ako dátoví analytici sami? Knihu možno poňať aj ako kuchárku toho, čo by ste v dátovej analýze nemali opomenúť a čoho sa naopak vystríhať. Čo si vážim na autorovi najviac, je fakt, že na každý z 15 možných dôvodov (,kde dátová práca “zakopáva”) autor ponúka aj jasné návrhy riešenia (či prevencie). Jednovetová recenzia tejto knihy by znela: Povinné čítanie pre tých, čo za živia prácou s dátami, inšpirácia pre kohokoľvek, kto nechce podľahnúť (neodbornej, či účelovej) manipulácii s faktami.

Link: https://www.amazon.com/dp/069118237X/

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Enjoying It, Candy Crush and Capitalism

Zameranie : Životný štýl, Filozofia

Neviem, ako sa to podarilo, ale tohto roku som mal šťastnú ruku na prekvapivo veľa zaujímavých filozofických kníh. (Možno starnem.) Aby bolo hneď na úvod jasné, filozofické traktáty znášam podobne dobre ako väčšina populácie. Teda tak po 5 stranu. Potom zväčša pregúlim očami a  kniha sa prepadá v čítacom poradovníku. Alfie Brown ma však svojou knihou upútal. Nielen tým, že ju spravil znesiteľne krátku, ale najmä tým, že si vybral tému, nad ktorou som už aj ja premýšľal. Je súčasná Netlix vlna a Hranie hier na mobile len zabíjanie času? (nad ktorým my, knihomoli, môžeme pohrdovačne predniesť svoje “Pchá!”) Alebo ide o legitímne a zmysluplné trávenie voľného času, ktoré zostáva generačne nepochopené? Argumentačne a filozoficky podložená rozprava o tejto téme ma nielen vtiahla do čítania tak, že som si nevšimol, ako ďaleko som za 5tou stranou. Objasnila mi aj postoje niektorých ľudí z môjho okolia. Možno mi budete po prečítaní nadávať, ale fakt by som vám to odporúčil si prečítať. Autor navyše napísal aj ďalšie podobné dielo na trochu inú tému, ktoré je na mojom reading liste ešte do konca roka. Tak prípajam link aj k tomu druhému dielu.

Link: https://www.amazon.com/dp/1785351559

Link na ďalšie dielo autora: https://www.amazon.com/dp/1509518037

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Cesta Na Ropnú Plošinu

Zameranie: Motivácia, Životný štýl

Ak by ste poznali Andreja, asi by ste nepochybovali, že jeho kniha na tento zoznam patrí. Ale keďže ho zrejme nepoznáte, skúsim vám priblížiť, prečo jeho kniha naozaj stojí za prečítanie.

Žijete ako chlapec na sídlisku na strednom Slovensku. Dopočuli ste sa, že v takom Nórsku by sa dali zarobiť skvelé peniaze. Tak si vygooglite nejakých Slovákov v Nórsku na Facebooku, “rozbijete prasiatko” a kúpite si letenku do Nórska. Vystúpite z lietadla a Nórsky sen sa môže začať …

… až na to, že váš Slovenský mobil nemá roaming, neviete po nórsky, nemáte vysokú školu, nikto vám neche dať prácu, prepleskli vás škandinávske ceny, nemáte nikoho blízkeho, vaše úspory sa okamžite rozplynuli a začínate mať povážlivé zdravotné problémy.

Nie, to nie je scénar B-čkového dobrodružného románu. To je skutočný príbeh Andreja Tichého. Ktorý sa, snáď mi to priateľu prepáčiš, dosť naivne vybral do Nórska. Hoci samotný príbeh (z ktorého nechcem vyzradiť najpikantnejšie scény) by bol hodný filmového námetu, táto kniha má  oveľa silnejší odkaz. Ukazuje na to, ako naozaj chcieť niečo dosiahnuť. Ako sa nezlomiť a na čo všetko sa pripraviť. Ale hlavne ako nakoniec uspieť a splniť si (v podstate nereálny) sen. A ako pochopiť, že to je len prvý stupienok v dlhom kariernom a rodinnom živote.

Nie, nechajte sa oklamať šibalským názvom knihy. Toto nie je cestopis, ani návod, ako sa dostať na ropnú plošinu. Toto je energetická vzpruha, ako dosiahnuť svoje sny. Navyše vzpruha, pri ktorej sa zasmejte aj si zahíkate.

Link: https://www.martinus.sk/?uItem=292194

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Never Split The Difference

Zameranie : Vyjednávanie, Biznis stratégia

Iste ste sa už ocitli v situácii, kde išlo o veľa. Hádka s partnerom, požiadavka o zvýšenie platu, obchodné rokovanie alebo dieťa, ktoré sa nevie vspratať do kože. A keď si spätne prehrávate tú situáciu, hlava sa nestačí čudovať, čo to ústa hovoria. Kde hľadať radu, aby sme si to nabudúce (prinajmenšom) sami nekazili?

Hľadať rady o vyjednávaní možno u rôznych profesií. Niektorí vám odporúčajú hrať neústupných tvrďasov. Iní vás nasmerujú k tomu “aby ste dohodu s oponentom smerovali niekam doprostred rozpätia”. Čo si však o optimálne stratégií vzjednávania myslí Policajný vyjednávač, ktorý rieši rukojemnické drámy a únosy? Má ponúknuť protistrane zabitie polovice rukojemníkov výmenou za to, že sa útočník vzdá?

Chriss Voss je absolútna svetová špička vo vyjednávaní s ozbrojenými útočníkmi a teroristami. A ako policajný vyjednávač vždy musí hrať na to, že on vyhrá všetko a terorista nedostane skoro nič. Preto je zaujímavý jeho pohľad na to, ako viesť vyjednávania tak, aby na vašej strane zostal celý jackpot. Ak vám to príde odpudivé (až nefér) pre bežný život, pozeráte sa na to rovnako ako ja, kým som knihu neotvoril. Verte mi však, kniha nie je návodom, ako druhú stranu ošklbať. Je to súbor rád (popísaných na konkrétnych prípadoch), ktoré vám umožnia ísť aj za 50:50 dohody. A pritom neuraziť ani nepodraziť oponenta. Popísané postupy sú však rovnako užitočnou obranou proti zdatným súperom, ak aj sami nechcete aktívne zatlačiť. Kúpa tejto knihy sa vám násobne vráti. Už na najbližšom hodnotiacom pohovore alebo hyisterickej scéne vašej ratolesti.

Link: https://www.amazon.com/dp/1847941494

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DIEŤA 44

Zameranie: Ruská história, Detektívka

Ako som písal v záhlaví tohto blogu, knihy krásnej literatúry do odporúčaní na tomto blogu zvyčajne nedávam. Pri tejto knihe však veľmi rád urobím veľkú výnimku.

Kniha Tom Roba Smitha ma fascinovala tým, že veľmi dlho (vyše sto strán) som nevedel odhanúť. aký žáner vlastne čítam. Chvíľu som mal pocit, že čítam historický román, či literatútu faktu o sociálnej situácii v povojnom Rusku. Alebo detektívku? Ak vám toto moje zmätenie príde nepochopiteľné, tak vedzte, že autor tak pútavo mieša tieto tri línie knihy, že je vám to vlastne úplne jedno. Chcete ďalšiu a ďalšiu stránku, nech je to ktorekoľvek z nich. Inými slovami kniha tak verne prepája opis spoločenskej situácie so životom postáv, až … až zrazu zistíte, dopekla, veď ono je to detektívka. Vrah sa začína nápadne podobať na niekoľko postáv. Začínate mať istotu, kto to asi je. Ale spoločenské zriadenie ho vlastne nechce vypátrať, tak ako bude spravodlivo potrestaný? Dieťa 44 (mimochodom prvý diel trilógie) je skvelá a pútavá kniha na jesený večer aj k opaľovaciemu krému na lehátko. Proste si to užite.

Link: https://www.martinus.sk/?uItem=50893

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Seeing Around Corners

Zameranie : Manažment, Biznis stratégia

Jadrom mnohých problémov  biznisu je, že sa na aktuálne dilemy nazerá metódami spred 20 a viac rokov. Rozhodnutia totiž robia ľudia, ktorí študovali v čase, keď dané témy boli horúcimi novinkami. Ako však dovidieť za horizont? Ako správne prečítať, čo bude IN v najbližších rokoch? Ale hlavne, ako inovovať skôr pomocou “calculated bets” ako cez “plug and pray” projekty.

Hoci Rita McGrath patrí (aj v mojej rozsiahlej knižnici) medzi neznámych autorov, rýchlo si získala moju priazeň tým, ako pragmaticky pomenúva slabé miesta biznisu a skutočné záplaty na tieto diery. Nebojí sa ísť proti mainstream prúdu, takže sa dozviete, že trhový podiel je zastaralá metrika, že skutočné inovatívne firmy sú tie, ktoré na to nepotrebujú zamestnancov alebo že Netflix dlho tápal v tom ako prejsť na predplatné. Nehľadá ikony ani hrdinov (ako je tak bežné pre Amerických biznis autorov). Naopak, servíruje dobre štruktúrované rady, ako systematicky inovovať, ale aj čo sú často opomínané úlohý lídrov v tomto procese, či ako nepodľahnúť tlakom okolia.

Je to hutné čítanie a pripravte sa na to, že budete odbiehať od knižky k poznámkovému bloku či klávesnici si zapísať podnetné nápady. Podctivé čítanie tejto knihy teda zaberie viac času, ako by jej  (inak štandardná) hrúbka naznačovala. Ak však vediete nejaký team alebo (spolu)zodpovedáte za stratégiu či smerovanie nejakej firmy, moje odporúčanie si s chuťou užijete.

Link: https://www.amazon.com/dp/0358022339/

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Ak ste členom komunity MocneData už dlhšie (mimochodom stať sa ním môžete bezplatne tu), tak viete, že svoje čitateľské odporúčania som dával aj po iné roky. Tu sú niektoré z nich:

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