Links for this week (weekly)

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  • “Le fondement du droit du travail classique c’est la subordination. Tout repose sur « l’autorité qui tombe d’en-haut », le management « à la petit chef ». Il existe donc aujourd’hui un décalage réel entre les règles actuelles du droit du travail et la réalité du terrain.”

    tags: remotework law worklifebalance

    • Selon l’INSEE, il y a 3 millions de travailleurs du savoir en France qui  travaillent le dimanche.
    • Le travail immatériel a deux qualités qui peuvent devenir absolument rédhibitoires : je peux travailler n’importe où, n’importe quand. Par ailleurs le travail intellectuel n’est jamais fini. Le travail immatériel s’exporte donc massivement vers la maison. Question du juriste : est-ce du travail commandé? Sans limite, c’est l’apparition des risques psychosociaux. Au bureau, on ne fait plus que réagir, communiquer, on ne travaille plus vraiment. Finalement  on avance concrètement sur les sujets « au calme, à la maison ».                                        Or, si on est à la maison, on est supposément disponible ; on ne dit pas « attends je travaille » à ses enfants, son conjoint. Sinon on crée un désastre familial, un désastre social.
  • This semester I am teaching the innovation half of a course on Entrepreneurship and Innovation at NYU’s new Center for Urban Science and Progress (CUSP). Teaching forces you to take a fresh look at the subjects you are covering, so I find myself revisiting questions I’ve long been thinking about: What is the essence of innovation in the digital economy and how does it differ from the industrial age innovation of the past two hundred years?”

    tags: digitaleconomy innovation cognitivecomputing cognition

    • The Industrial Revolution had a huge impact on all aspects of the economy and society.  It totally transformed the composition of labor.  In 1840, the vast majority of US jobs where in agriculture, with services accounting for roughly 20% of jobs.  Those figures have been drastically reversing since then.  According to 2009 statistics from the CIA World Factbook, only 0.7% of the US labor force is now involved in agriculture oriented jobs and roughly 20% work in the industrial sector.  The bulk of jobs, almost 80%, are in services, with 3/4 of those service jobs based on processing informati
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      The machines of the industrial age were primarily making up for our physical limitations – the steam engines that enhanced our physical power, the railroads and cars that helped us go faster, and the airplanes that gave us the ability to fly.  But now, digital technologies are making up for our cognitive limitations, augmenting our ability to solve tough problem and make complex decisions

    • innovation is “the most important force that makes our society wealthier.”  Innovation is critical to improving productivity, that is, to raise the output per worker, which in turn leads to a wealthier society and a higher standard of living for its people. 
    • Before 1800, it took centuries to double income per capita; between 1929 and 1957, US incomes doubled in only 28 years;  between 1957 and 1988, doubling took 31 years; the pessimistic view adopted here suggests that it may take almost a century for income per capita to double between 2007 and 2100.” 
    • “We wanted flying cars – instead we got 140 characters,” is how PayPal cofounder Peter Thiel succinctly described his belief that we are no longer solving big problems. 
    • the true work of innovation is not coming up with something big and new, but instead recombining things that already exist.  And the more closely we look at how major steps forward in our knowledge and ability to accomplish things have actually occurred, the more this recombinant view makes sense
    • Each development becomes a building block for future innovations.  Progress doesn’t run out; it accumulates.  And the digital world doesn’t respect any boundaries.  It extends into the physical one, leading to cars and planes that drive themselves, printers that make parts, and so on.
  • “Big data has become the X factor of modern marketing, the hero of every marketer’s story. But it’s a promise at risk of letting you down. You may be thinking that data will magically turn bush-league marketing into a winning “Moneyball” performance. But that’s an artifact of our big data obsession. Data, alone, isn’t what makes marketing move the needle for business.”

    tags: bigdata marketing brand

    • If you are like most marketers, you may be at risk of becoming like the day-trader who is so dialed in to his data that he fails to see the patterns forming beyond the intraday trading bell. You may be at risk of simply asking too much of data.
    • That’s why we believe today’s data-obsessed marketers are at risk of cultivating only half a brain. Marketing leaders must remember that true brand intelligence lives at the intersection of head and heart, where the emotional self meets the analytical self.
    • That’s why we believe today’s data-obsessed marketers are at risk of cultivating only half a brain. Marketing leaders must remember that true brand intelligence lives at the intersection of head and heart, where the emotional self meets the analytical self.
  • “Pioneers in the application of advanced-analytics approaches, some borrowed from risk management and finance, are emerging in industries such as chemicals, electronics, mining and metals, and pharmaceuticals. Many are lean veterans: these companies cut their teeth during the 1990s (when sagging prices hit a range of basic-materials companies hard) and more recently doubled down in response to rising raw-materials prices. “

    tags: analytics bigdata lean kaizen

    • Indeed, our work suggests that, taken together, the new uses of proven analytical tools could be worth tens of billions of dollars in EBITDA
    • Nonetheless, to get the most from data-fueled lean production, companies have to adjust their traditional approach to kaizen (the philosophy of continuous improvement). In our experience, many find it useful to set up special data-optimization labs or cells within their existing operations units. This approach typically requires forming a small team of econometrics specialists, operations-research experts, and statisticians familiar with the appropriate tools. By connecting these analytics experts with their frontline colleagues, companies can begin to identify opportunities for improvement projects that will both increase performance and help operators learn to apply their lean problem-solving skills in new ways.
    • The steelmaker’s story shows that senior executives must take an active role. In our experience, the information and data required for many big data initiatives already exist in silos around companies—in shop-floor production logs, maintenance registers, real-time equipment-performance data, and even vendor performance-guarantee sheets. In some cases, data may come from outside partners or databases. Determining what to look for, where to get it, and how to use it across a dispersed manufacturing network requires executive know-how and support.
  • “Il y a peu, je publiais ici un billet dans lequel je ne manquais pas de soupçonner les entreprises de surévaluer leur maturité numérique.

    Aujourd’hui, le CIGREF leur propose de faire le point au travers du premier cadre de référence de la culture numérique, initiative à saluer sur le principe, mais également sur la qualité du support proposé.”

    tags: digital digitalculture culture cigref

  • tags: socialbusiness organization engagement bigdata scalability advocacy

Posted from Diigo. The rest of my favorite links are here.