Book Review – “The First Mile”, by Scott Anthony

The First MileA book about how to transform your innovation ideas into a working machine? Anytime! Especially when it comes from Harvard Business Review Press and it is packed with actionable advice and study cases.

“First Mile”s author (Scott Anthony) is not quite new to the innovation field. As a managing partner at Innosight (a small venture capital and consulting company from Singapore which generates 76,400 hits, quite  a lot for a discrete company), he has seen hundreds of such small companies starting and failing – or succeeding. And objective books by venture capitalists, written out of passion, are quite rare. So I braced myself for a potentially good read.

“The First Mile” is an entrepreneurship book mostly about creating, testing and starting the implementation of your business plan. It is a book oriented towards the first-time or maybe serial antrepreneurs, who want to do other mistakes than their predecessors. As a Harvard Business Review Press book, it has two main advantages: Read more

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    Big Data and Hadoop

    Accidentally I came over recently an Apache server technology for big data centralization and analysis. Hadoop is a mix and match technology, open source, which allows companies to write their own big data analytical tools in a quick and efficient manner.

    What puzzled me mostly was the adoption of this type of open-source solution. You would think that the serious developers (such as SAS, IBM or Pentaho) would be reluctant to adopt open-source solutions. After all, look at what happened with the Goldman Sachs flash trading code (if you have not read the book “Flashboys”, maybe it is time to give it a try :)). But no, they are embracing it! I do not know if this is because they want a continuously developeable solution, a community pooling benefit or just something off-the-shelves, but here we go. Big data tools are not only very lean, but also based on a global creativity streak. Isn’t this interesting?

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      Book Review – “Big Data @ Work” by Thomas Davenport

      It is quite rare that somebody admits they were wrong about a major trend in IT which was overseen in the past. Quite rare. Fortunately, Thomas Davenport is not that kind of person – on the contrary. In the preface of his new book (“Big Data At Work) published by Harvard Business Review Press, he actually admits that he initially dismissed the concept as being just another technology hype. And you can hardly blame him – there are many gurus or specialists or journalists who still think that the “big data” concept represents another form of selling clound and analytical services. Promoted, of course, by the big IT companies who happen to endorse the concept quite actively.

      From this perspective, Harvard Business Review Press has done some justice to the hype surrounding the concept. “Big Data at Work” was in a sense a long waited for book – people were maybe familliar with the concepts, but wanted maybe to know more about:

      – how big data is implemented and used by various companies (the famous “case study” approach patented by the Harvard Business Review (one of the biggest business case studies publishers in the world by the way); Read more

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        How To Compile a Top 10 Investing Books List

        Last night me and several investor friends had a long conversation about the best investing books ever. True, one can find on the market so many titles that it is almost overwhelming. Investment books can range from advice for beginners, technical trading books, Forex guides – to even excel-oriented investing books or guru’s promising you fortunes in exchange for a one hour a day.
        I would dare to say that the investment books market is so diverse that not even ten lifetimes would help you to digest all of them.
        Yet, most of the investor-oriented books have several features in common:
        – they have a limited theoretical background behind them (which means that once you mastered the main ideas, you will hardly read about new investing techniques in a new book);
        – investing books can be divided into technical/mathematical and behavioral. One without another is not possible;
        – they are “readable”, not arid and obscure financial compendiums.

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          New Deal Means A Sort of Old Liberal Keynesianism

          Yesterday I noticed an interesting trend on the financial investments blogs – many started to talk recently about a New Deal. Which is normal, don’t get me wrong – with stagflation and investments decimated in the US, with the BRIC markets trailing behind expectations and a sluggish Europe, things look hardly “rainbowy” for the global asset managers.
          Which of course gets the economic policy makers and thinkers worried. Especially in the US, the world’s powerhouse in economics 101. No wonder that famous and serious bloggers, such as Rortybomb, turned their attention to that. After all, what’s easier than taking an old wheel, polishing it and using it to restart a virtuous economic cycle?
          My short answer is – everything. The neo-liberal thinking pushed the US economy in this prolonged recession – by allowing the US government to throw billions of dollars into several sector’s arms which used them sub-optimally. Of course, all those blogs are against this policy. Or pro this policy with changes (big or small).
          Then, what’s the problem? Why do I argue for a new paradigm?
          It is very simple. It is called “behavioral finance”. And NLP. 2 in 1, crash course my friends:
          1. New Deal is an old paradigm Read more

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            Is Big Data Just Noise?

            Judging by the amount of information available on big data, I would say that paradoxically that the concept is poorly supported. More of a giant with feet of clay. Let us do for example a Google keyword analysis: “big data” search reveals 829,000,000 results in 0.44 secs. (which means that Google has spend some time about it). Apparently a lot.
            The problem reveals after you start browsing the pages. The first 10 pages of results show in all cases either definitions and white papers about big data (very vague and fluffy), either selling links. Virtually there was no value added info on the concept itself (except maybe for the Wikipedia article, which is showing some well structured info at the introduction level).
            And then we go. All resources which are published up to page 100 are consisting in what I call “meta-information”, information about information which reduces the meaning below a value-adding level. Actually, the more you read about big data over the web, the less you are likely to be convinced about the topic. I know this sound very semiotically or Foucault like, but my perception became a bit one of a frustrated librarian who cannot put the finger on the concept. Read more

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              (An Almost) Perfect Profile of a CEE CFO (2)

              As usually, when you start analyzing a topic, other collateral findings start to pop up. More recent articles, written by practitioners, shed a more enlightning picture on the CFOs’ hurdles in East Europe.

              First of all, most of these new articles show that CFO’s have been really abated and overwhelmed by the depth of the crisis. With the massive deleverage taking place in 2009-2011, markets are still suffering and CFO’s are still trying to find new sources of profitability. And if there was any reluctance of restructuring the finance departments during the initial years of the crisis, in 2014 the situation changed – restructurings are still taking place, with many companies still having finance (and others) hiring freezes – or even promotion freezes.

              This might make the CEE CFO’s more risk averse than ever, with an ever increasing amount of work on their desks. Read more

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