In June 1999, when Carlos Ghosn was parachuted by Renault to a little known (outside Asia) car manufacturer named Nissan, his reputation should have preceeded him. Maybe the Japanese board of directors underestimated the „Le Cost Killer“ nickname he earned at Renault during the previous 3 years – or maybe they thought that one of the most inner-oriented markets in the world would reform his views. The above simply did not happen. Instead, Ghosn went on to massively reduce Nissan‘s expenses, especially its huge Selling, General and Administration (SG&A) by 20% in only 1 year. He went on for the next decades, making the Renault-Nissan alliance one of the top car sellers on Earth (it climbed to no.1 in H1 2017).
Contrast this SG&A story with General Electric‘s one: between 2013 (SG&A expenses = 21,08 Bln USD) and 2017 (21,48 Bln.), there is barely any reduction in absolute terms. Continue reading “Simplicient Controlling 2 – To Reduce or Not… Your SG&A Expenses” »
As any business book worm could notice, there is no shortage of career advice books being published. According to our own doitinvest.com rough estimations, at least 200 titles are heavily pushed towards the English speaking exec-suite “wanna be’s”. Naturally, with so much noise, one normal reader does not stand a chance to read even 10% of these.
Therefore the questions is – what makes “8 Steps to High Performance – Focus on What You Can Change” a book worth reading?
If you ask me, first is the author – Marc Effron. He is not only a relatively well known talent consultant, but also a refreshingly direct person. Marc Effron does not pretend he is reinventing the career management- instead, he states he relies on the old-fashioned approach of synthesizing significantly tested HR theories into easy to follow steps to improving one’s career. Continue reading “Book Review – “8 Steps to High Performance: Focus On What You Can Change (Ignore the Rest)” by Marc Effron” »
Machine learning and artificial intelligence are becoming really hot topics. Take Europe companies, for example – it is enough to through in the discussion the “digitalization” and the “machine learning” topics and you will get the CEO’s attention. But as in most mini-industrial revolutions, the devil hides into the details. And the very same companies that push for transforming themselves are having a difficult time to perform the transformation itself. This is because of multiple reasons – not the smallest being a certain lack of knowledge ramp up during the current revolution.
“Human + Machine: Reimagining Work in the Age of AI” takes an interesting middle ground approach to the topic. On one hand, it lays down quickly the rules governing this brave new volatile world – data agility. Continue reading ““Human + Machine: Reimagining Work in the Age of AI” – book by Paul Daugherty and H. James Wilson (book review)” »
„Entering StartUpLand” is for sure a different animal in the Harvard Business Review library. The same goes with the author himself (Jeffrey Bussgang), a relatively experienced venture capitalist who got his hands greased with new ventures’ oily details – as well as with the theoretical side. The book has a strong practical side – it is not only full of practical cases, but performs a deep dive into the mechanisms and safeguards of the world’s riskiest ventures.
“Entering StartUpLand” dissects a typical start-up through its functional anatomy. Continue reading “„Entering StartUpLand“ By Jeffrey Busgang – A Book Review” »
Artificial intelligence came (no doubt)3 years ago to stay. It started as a corporate craze for big data and last year moved to machine learning. These 2018 days AI goes in production via prediction (my 20 copyright cents please). Ajay Agraval, Joshua Gans and Avi Goldfarb, Toronto based professors, are well placed to write about this, as most of the tech companies spearheading the AI commercialization (led by the Big Tech 4 – Amazon, Google, Microsoft and IBM) are NAM based.
So what is “Prediction Machines” about? Without spoiling the book’s well documented contact, we can simply just underline that AI becomes a long powerful digitalization tool, but not any longer as a facilitator (as was until last year). Agraval forecasts that machines will eliminate uncertainty, thus reducing the market friction forces, thus reducing production and transaction costs. Continue reading “Book Review – “Prediction Machines – The Simple Economics of Artificial Intelligence”” »
Admit it, you have done this at least once: you were lured by the special offer / freebie / like into signing up for a newsletter… then you forgot about it. Or you installed an IOS/Android/Windows app which asked you for permissions to share with the Martians your accurate location, food prefferences or place of birth.
The personal data requests have become so ubiquitous, that now it is very hard to trace where it lands. It is then perfectly understandable why EU is seeking to make the various companies responsible for minimal safeguards of such personal data.
If you read the law (or the highlights), you would realize most of the requestgs are quite reasonable – and still theoretical. Fortunately for the consumer (and burdening for the companies), the burden of safeguarding and cleaning up the unnecessary data falls on the collectors. Continue reading “Multinational Glitches in the Implementation of GDPR” »