Links for this week (weekly)

• Experimentation Is The New Planning | Fast Company

  “Let’s be honest: You have no idea what’s going to happen to your industry. That’s why you build your organization into an engine of possibility. “

  tags: strategy planning discovery experimentation emergent

  • Management theorist Henry Mintzberg makes a distinction between deliberate and emergent strategy. Deliberate strategy relies on senior leaders to set goals and develop plans and strategies to achieve them. Emergent strategy is a strategy that emerges from all over the company, over time, as the environment changes and the organization shifts and adapts to apply its strengths to a changing reality
  • Deliberate strategy is goal-oriented. It asks, “What do we want to achieve?” Emergent strategy is means-oriented. It asks, “What is possible, with the means we have at our disposal?”
  • Emergent strategy requires that the company continually generate a broad range of hypotheses, testing them in small-scale experiments, and feeding the more successful experiments while pruning the failed ones
  • • Jack Welch, GE: “Size either liberates or paralyzes. We tried every day to remember that the benefit of size was that it allowed us to take more swings.”
  • Eric Schmidt, Google: “Our goal is to have more at-bats per unit of time and effort than anyone else in the world.”
  • Jeff Bezos, Amazon: “You need to set up and organize so that you can do as many experiments per unit of time as possible.”
  • Emergence is self-organization, order that bubbles up from the bottom instead of being pushed down from the top. Emergence is common in complex systems where agents have the autonomy to move around and interact to discover possibilities. For
  • Employees at Mailchimp, an email marketing company with about 100 employees, decide on new features and services in a similar way
  • Computer game maker Valve allows workers to self-organize based on individuals’ interests, passions, and feelings about what’s right for the compan
  • People commit to projects, and project leaders emerge based on informal consensus. Temporary organizational structures arise based on the needs of a particular project or team, but they are disbanded when the work is done.

• Transforming Indian Cities: Social Sentiment and Analytics « A Smarter Planet Blog

  “Now, cities will have a way to better measure and understand public opinions on key city issues and services, such as public transportation or education, using advanced analytics. By understanding the public sentiments of those living and working in a city, public sector leaders can create a new virtual town hall that can foster faster, more informed decisions that will in turn lead to improved services for citizens and more judicious uses of valuable resources.”

  tags: casestudies india bigdata sentimentanalysis government government2.0 ibm smartcities

  • If cities can understand the wealth of online content and public commentary –positive or negative — on social channels such as Twitter and Facebook, it will give them new opportunities to engage with its citizens in real time and more quickly pinpoint and prioritize areas that are top of mind.
  • So, the latest IBM Social Sentiment Index reveals what citizens in Bangalore, Mumbai and New Delhi feel is impacting congestion most in their city. The Index showed some interesting insight, particularly when comparing the cities to each other, for

• Les Serious Games au service des entreprises

  ”

  C’est sous ce titre que le « serious game » s’est invité chez IBM France pour une journée « sérieuse » proposée en partenariat par GUIDE Share France (association d’utilisateurs IBM indépendante) et le CIGREF (Réseau de Grandes Entreprises). Journée de réflexion sur la pratique des « serious games » dans l’industrie, la finance, la médecine…”

  tags: seriousgames casestudies ibm guideshare franceloreal learning training dassaultaviation univeritéparisdescartes renaul renaultacademy

  • Depuis, le serious game est devenu un support pédagogique efficace « on retient mieux ce que l’on fait que ce que l’on voit », et apprécié car il génère plus de motivation et d’implication de la part des apprenants
  • Le serious game d’IBM « Innov8 CityOne » est un jeu dont l’objectif est d’agir pour rendre la ville plus efficace, que l’eau soit plus propre, etc. résoudre les problèmes environnementaux, logistiques…».
  • . En effet, certains jeux permettent des apprentissages fortuits, comme l’apprentissage de l’anglais parce que l’on interagit avec des joueurs utilisant ce langage…
  • Il est beaucoup plus facile de comprendre une simulation dynamique que du texte décrivant une opération. On forme maintenant les mécaniciens à partir de jeux sérieux. Non plus à partir de capteurs, mais désormais avec des caméras.
  • on peut imaginer énormément de choses en matière de formation, ce qui est important car les budgets formation sont très lourds et l’apprentissage du geste est fondamental. Un autre intérêt de ces jeux sérieux est de faire entrer le compagnon dans un environnement qui n’est pas de formation, mais un environnement beaucoup plus ludique.
  • La pédagogie de la formation en médecine se transforme, le serious game répond vraiment à l’impératif pédagogique qui est de rendre les étudiants beaucoup plus actifs dans leur formation. Ces outils technologiques nous permettent d’améliorer l’efficacité des formations à la fois en augmentant la motivation et avec le recours à l’expérience

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    L’objectif ayant conduit Renault Academy à la réalisation des serious games était d’augmenter la satisfaction client et la performance commerciale de l’entreprise

  •  Pour la réalisation du serious game, on se base principalement sur des thématiques métiers, non sur des produits car ils seraient nettement moins pérennes. Avec les thématiques métiers, on est sur des standards comportementaux et des standards métiers, donc d’une durée de vie plus longue ».
  • L’objectif est de permettre un apprentissage de connaissances, d’accroitre les performances et les comportements des conseillers vis-à-vis du client. On est donc sur les champs du savoir, du savoir-faire et du savoir-être. L’apprenant doit pouvoir rejouer et améliorer ses comportements, sur une étape en particulier si nécessaire

  •  

    Le jeu offre une capacité à explorer, à comprendre des mécanismes complexes, et plus généralement ce qui est difficilement explicable. Le défi est de combiner le jeu numérique avec le monde réel, proposer des modes d’appréhension centrés sur l’utilisateur et les intégrer dans des processus de décision

• What Executives Don’t Understand About Big Data

  “Although big data already is — and will continue to be — a relentless driver of revolutionary business change (just ask Jeff Bezos, Larry Page or Reid Hoffman), too many organizations don’t quite grasp that being “big data-driven” requires more qualified human judgment than cloud-enabled machine learning. Web 2.0 juggernauts like Google, Amazon and LinkedIn have the inborn advantage of being built around both big data architectures and cultures. Their future success is contingent upon becoming disproportionately more valuable as more people use them. Big data is both enabler and byproduct of “network effects.” The algorithms that make these companies run need big data to survive and thrive. Ambitious Algorithms love Big Data and vice versa.”

  tags: bigdata algorythm judgment watson vqlud decisionmaking BI

  • One of the CEOs actually declared that the surge of new data might even lead to losses because his firm’s management and business processes couldn’t cost-effectively manage it.
  • Instead of asking, “How can we get far more value from far more data?” successful big data overseers seek to answer, “What value matters most, and what marriage of data and algorithms gets us there?”

  •   

    Too many executives are too impressed — or too intimidated — by the bigness of the data to rethink or revisit how their organizations really add value.

  • Executives need to understand that big data is not about subordinating managerial decisions to automated algorithms but deciding what kinds of data should enhance or transform user experiences
  • The innovative insights flow not from the bigness of the data but from the clear alignment to measurable business outcomes

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