Why Machines Won’t Displace Human Workers in the Knowledge Economy is a short thought experiment, in the spirit of all Noodles, which was in response to a post in Wired. In Here’s How to Keep the Robots From Stealing Our Jobs, John Hagel posited that a major rationale for the Knowledge Economy firm would be its role as a “knowledge platform” that enabled people to accelerate their learning and productivity. I highly recommend the post, which sparked many intelligent comments.
It’s obvious that many people (not just me ;^) are having difficulties imagining the world toward which we are hurtling, a world in which machines are getting “smarter” and able to “compete” for work roles that humans now do. In writing The Social Channel, I thought long and hard about the Knowledge Economy and people’s roles in it, and its main thesis is that everything, from states and enterprises to people and products, will be differentiated in the social channel and that “humanness” will assume a much more visible importance in the economy. Continue reading Why Machines Won’t Displace Human Workers in the Knowledge Economy
10 Detailed Case Studies + Big Data & Analytics’ New Digital Divide + How to Think Like a Data Scientist
[UPDATED] Step inside a data scientist’s mind, and learn why probability is the key to profit and how it’s the key to understanding and using big data for better decision making. This fascinating and useful book clearly shows how people misunderstand probability and misuse statistics—and therefore big data—and how the knowledge gap leads to faulty models, thinking and decisions. New winners and losers are emerging in the digital social and big-data age. A new digital divide, people who think like data scientists and use probability to support decision making—and everyone else. The data science group will outperform, and Fung shows how creative, fun and useful data science is.
This book is a perfect twin to Duncan Watts’ Everything Is Obvious* Once You Know the Answer, which exposes how common sense pervades management decisions and failure. I shall refer to several specific connections between the two reviews. You can appreciate both reviews without reading the books, although I highly recommend buying both. Where Watts does an enthralling job of describing the limitations of the common-sense, hyperlocal human brain, Fung shows his readers new ways of thinking that take advantage of large data sets.
Best of all, although Numbers Rule Your World (hereafter “Numbers”) doesn’t skimp on details, it is not a dry book because Fung is an talented storyteller who revels in thinking about information in creative ways. He’s curious and smart. I covered his Chicago talk, and he’s like that in person, too, one of those people who thrives on what he’s doing. He’s a total geek, but he’s also an excellent interpreter. I have never studied statistics, although I am strong in logical and abstract thinking, and I enjoyed the book immensely.
My analysis and conclusions follow the outline of each chapter.
Continue reading Why Probability Is the Key to Profit in the Digital Social Big-Data Age
The rise of design signaled the fall of Nokia, RIM and Motorola describes how engineering is becoming less important in distinguishing hightech and other products from each other. It also presages a seismic shift away from product towards customer experience in determining market leaders for people-oriented products and services. A very large portion of product companies will follow in the footsteps of these three former mobile phone titans unless they transform their focus from product features (engineering) to customer experience (design).
By no means do I imply that engineering is not important—in fact, it is more important than ever—I assert that it is less important than design in differentiating people-oriented products. Engineering is abstracted away from the customer/user of the product, and design explicitly addresses how the customer uses the product to attain outcome(s).
Design is to the Knowledge Economy what engineering was to the Industrial Economy.
Continue reading The Rise of Design Signaled the Fall of Nokia, RIM and Motorola
Omni-Channel Retail, Mobile and Big Data offers tantalizing glimpses into current and future omni-channel retail trends and technologies. I “sat down” with three thought leaders and a crowd of smart people on AllAnalytics’ real-time webcast, which featured real-time Q&A with the panelists afterward. You can watch it here.
Panelists Dr. Erik Brynjolfsson, Dr. Yu Jeffrey Hu and Dr. Mohammad Saifur Rahman collaborate on numerous projects, and they are intensely interested in retail transformation. They also referenced one of their recent papers, Competing in the Age of Omnichannel Retailing, and I have added some of its points here as well. The webcast was well moderated by AllAnaytics’ Noreen Seebacher and Beth Schultz.
Although it wasn’t discussed in depth, I observe that big data is especially poignant to retailers for two reasons: they have extremely rich internal, proprietary transaction data on customers (loyalty cards, credit cards, returns information, call center information, service information) and retail customers are the most free-wheeling online. Retail customers discuss their experiences in situations in which they use most types of products. This gives retailers priceless information: the social context in which customers are using products to attain outcomes. Continue reading Omni-Channel Retail Mobile and Big Data