Social Physics - Reinventing Analytics to Better Predict Human Behaviors

Irving Wladawsky-Berger

These data tell the story of everyday life by recording what each of us has chosen to do… Who we actually are is more accurately determined by where we spend our time and which things we buy, not just by what we say we do.”.

The Transformative Power of Analytics - The Houston Astros: a Case Study

Irving Wladawsky-Berger

The answer, in a nutshell, is analytics. Luhnow then brought his analytics and management skills to Houston and proceeded to transform the team into a top contender in a short few years. For certain elements of the analytics, we had to wait and be patient.

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The Transformative Power of Analytics - The Houston Astros: a Case Study

Irving Wladawsky-Berger

The answer, in a nutshell, is analytics. As VP of scouting and player development in St Louis, Luhnow built a strong analytics department and enjoyed great success as one of the top talent producers in baseball, helping the Cardinals win the 2011 World Series as well as reach the playoffs from 2012 to 2015. Luhnow then brought his analytics and management skills to Houston and proceeded to transform the team into a top contender in a short few years.

How collaboration is transforming the relationship between sell-side and buy-side financial markets

Trends in the Living Networks

I have spent considerable time working with the institutional financial services sector, and seen major changes over the years. One of the most obvious examples is in the relationship between buy-side and sell-side in financial markets. The availability of information and the concentration of analytic capabilities in the buy-side has shifted the balance of power, and made the value proposition of financial market sales activities ever more tenuous.

Buy 104

Ethical Codes and Learning Analytics

Stephen Downes: Half an Hour

Abstract The growth and development of learning analytics has placed a range of new capacities into the hands of educational institutions. The ethics of learning analytics will therefore need to be developed on criteria specific to education. It may be argued that the relation between ethics and law is such that in a treatment of the ethics of learning analytics we ought also to be concerned with the law in relation to learning analytics.

Guy Kawasaki Makes an Enchanting Offer: Buy One, Get One Free.

Bob Sutton

Financial sector: however good the pay, it doesnt buy results | Business | The Observer. Howard Gardner: Changing Minds: The Art and Science of Changing Our Own and Other Peoples Minds. Guy Kawasaki: Enchantment: The Art of Changing Hearts, Minds, and Actions. May: The Shibumi Strategy: A Powerful Way to Create Meaningful Change. Chip Heath: Switch: How to Change Things When Change Is Hard. Leading a Great Enterprise through Dramatic Change.

Buy 48

Online Community Purpose Checklist | Full Circle Associates

Nancy White

11/26/2009 HANH Le # uberVU - social comments on 14 Jan 2010 at 7:02 am Social comments and analytics for this post… This post was mentioned on Twitter by lordorica: Community builders can get a jumpstart using Nancy White’s Online Community Purpose Checklist.

The State of AI Adoption - High Performers Show the Way

Irving Wladawsky-Berger

A common theme throughout the report was that the same players who were leaders in the earlier waves of digitization and analytics were the early leaders in the AI wave. Nevertheless, the survey shows that a majority of companies are preparing for AI-related work-force changes.

The Emergence of Industry 4.0

Irving Wladawsky-Berger

They all attempt to describe and put a name to the disruptive changes taking place all around us within the context of the past 250 years. The WEF has taken the broad-scope view , having chosen The Fourth Industrial Revolution as the central theme of its January, 2016 annual meeting in Davos, Switzerland. “We are at the beginning of a revolution that is fundamentally changing the way we live, work, and relate to one another,” wrote Dr. Schwab in his 2017 book.

Guy Kawasaki's Enchantment: A Beautiful Business Book Cover.

Bob Sutton

Financial sector: however good the pay, it doesnt buy results | Business | The Observer. Howard Gardner: Changing Minds: The Art and Science of Changing Our Own and Other Peoples Minds. Guy Kawasaki: Enchantment: The Art of Changing Hearts, Minds, and Actions. May: The Shibumi Strategy: A Powerful Way to Create Meaningful Change. Chip Heath: Switch: How to Change Things When Change Is Hard. Leading a Great Enterprise through Dramatic Change.

Matt May's Shibumi Strategy: What a Lovely Book! - Bob Sutton

Bob Sutton

Financial sector: however good the pay, it doesnt buy results | Business | The Observer. Howard Gardner: Changing Minds: The Art and Science of Changing Our Own and Other Peoples Minds. Guy Kawasaki: Enchantment: The Art of Changing Hearts, Minds, and Actions. May: The Shibumi Strategy: A Powerful Way to Create Meaningful Change. Chip Heath: Switch: How to Change Things When Change Is Hard. Leading a Great Enterprise through Dramatic Change.

The Emergence of Industry 4.0

Irving Wladawsky-Berger

They all attempt to describe and put a name to the disruptive changes taking place all around us within the context of the past 250 years. The WEF has taken the broad-scope view , having chosen The Fourth Industrial Revolution as the central theme of its January, 2016 annual meeting in Davos, Switzerland. “We are at the beginning of a revolution that is fundamentally changing the way we live, work, and relate to one another,” wrote Dr. Schwab in his 2017 book.

How to Support the Widespread Adoption of AI

Irving Wladawsky-Berger

The companies with the highest returns on their technology investments did more than just buy technology; they invested in organizational capital to become digital organizations. Having business and operational people work side by side with analytics experts will ensure that initiatives address broad organizational priorities, not just isolated business issues. They require leaders to prepare, motivate, and equip the workforce to make a change.

Artificial Intelligence is Ready for Business; Are Businesses Ready for AI?

Irving Wladawsky-Berger

A successful program requires firms to address many elements of a digital and analytics transformation: identify the business case, set up the right data ecosystem, build or buy appropriate AI tools, and adapt workflow processes, capabilities, and culture.”. A common theme throughout the report is that the same players who were leaders in the earlier waves of digitization and analytics are now leading in the AI wave. AI is now seemingly everywhere.

The Continuing, Transformative Impact of IT

Irving Wladawsky-Berger

The social matrix, the Internet of all things, big data and advanced analytics, and realizing anything as a services are the report’s top four trends. SMAC - Social, Mobile, Analytics & Cloud, - has become the new plastics , capturing the future of IT in one word, or rather, one acronym. billion people will become consumers by 2025, that is, they will earn enough to buy goods and services beyond meeting their basic needs.

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My 25 Years of Ed Tech

Stephen Downes: Half an Hour

Into this environment came Second Life, which was distinct in two ways: it was commercialized and heavily marketed, leading institutions and organizations to buy and build 'islands', and second, there was nothing to do, which led to it being mostly empty. He finishes the section saying "personalized learning remains one of the dreams of ed tech, with learners enjoying a personalized curriculum, based on analytics." Anyhow, I document many uses of learning analytics here.

The Transformative Power of Cloud Computing

Irving Wladawsky-Berger

There are clearly other major technologies around us, - e.g., smartphones, IoT, analytics, AI, - but when you think about it, all of them rely on their connections to cloud-based data, applications, and services for much of their functionality. Instead of having to buy and operate their own computing resources, users could now obtain the IT resources they needed over the Internet on demand, paying for whatever cloud resources they actually used.

Data 194

Blackboard’s identity crisis, Desire2Learn’s optimism, and Instructure’s coolness

George Siemens

And the LMS is not being commoditized – it’s being integrated with new value adds including curriculum, eportfolios, analytics, learner relationship management, advising, mobile, etc. Their move to synchronous tools, their tactics of buying competing company to eliminate competition (Elluminate and Wimba), acquisitions of iStrategy, etc., Last week, I visited D2L’s main offices in Kitchener as part of a possible research project in analytics.

How Will AI Likely Impact How We Work, Live and Play?

Irving Wladawsky-Berger

Public safety and security. “One of the more successful uses of AI analytics is in detecting white collar crime, such as credit card fraud. Hardware platforms remain challenging to build, and there are few applications that people want enough to buy. A few weeks ago I discussed whether AI is finally reaching a tipping point, mostly based on a recently published report, - Artificial Intelligence and Life in 2030.

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Remaking education in the image of our desires

George Siemens

Change is happening on many fronts: economic, technological, paradigmatic, social, and the natural cycles of change that occur in complex social/technical systems. People have attempted to define change principles: Christensen’s disruptive innovation , Schumpeter’s creative destruction , Kuhn’s revolution structures , Paul A. David’s model of long systemic change , and (my personal favorite) Carlota Perez’ techno-economic revolutions.

The Datafication of Business and Society

Irving Wladawsky-Berger

I first encountered the term datafication in The Rise of Big Data: How It’s Changing the Way We Think About the World , by Kenneth Cukier and Viktor Mayer-Schönberger. Physicists, astronomers, biologists, geophysicists and other scientists and engineers were developing methodologies and architectures for dealing with very large volumes of unstructured data, as well as analytical techniques, like data mining , for discovering patterns and extracting insights from all that data. .

Data 200

The Continuing Evolution of Service Science

Irving Wladawsky-Berger

In July of 2009, the UK’s Royal Society released a report - Hidden Wealth: the contribution of science to service sector innovation. “Our main conclusion,…” said the report “is that services are very likely to remain central to the new economy, not least because we are at or near a tipping point: innovations now underway seem likely to change dramatically the way we live and to generate many services (though few can be predicted in detail at present).”. This has all been changing.

Data 138

The Internet, Blockchain, and the Evolution of Foundational Innovations

Irving Wladawsky-Berger

Last year, a panel of global experts convened by the World Economic Forum selected blockchain as one of the Top Ten Emerging Technologies for 2016, based on its potential to fundamentally change the way economies work. In a digital world, the way we regulate and maintain administrative control has to change…”. Along with smartphones, cloud computing, social media, analytics and related technologies, the Internet has been systematically transforming one industry after another.

The (Uneven) Digitization of the US Economy

Irving Wladawsky-Berger

The companies with the highest returns on their technology investments did more than just buy technology; they invested in organizational capital to become digital organizations. Multi factor productivity: Big data and analytics, IoT, mobile devices, cloud computing, AI and other technology advances could lead to major new innovations, faster product development, improved energy efficiency and smarter overall operations across just about all industry sectors.

Data 150

Institutional Innovation - I Have a Dream

Edge Perspectives

Yes, the business will look very different in terms of the specific activities being performed, but the overall approach to how to be successful in business will not necessarily change. This institutional transformation is an imperative because the scalable efficiency model is increasingly challenged given the profound changes playing out in our global economy (see our work on return on asset trends for US companies). Growth: Shift from make or buy to mobilize.

The Big Shift: Challenge and Opportunity for Women

John Hagel

How are women affected by the longer-term changes that are transforming our business environment?   The masculine archetype is built upon a certain set of beliefs : We can't afford to get tied down in long-term relationships - our focus is on short-term transactions (“battles”) where the goal is to get as much as possible out of each transaction and to treat each transaction as an independent event – buy low, sell high and move on.

Module 203

Wise and interesting words

Harold Jarche

Yesterday afternoon I caught up with Jon Miller and Maria Pergolino to get an inside view of their new Revenue Cycle Analytics (RCA) as well as what's coming up. In other words, their buying process may be different than your sales process.

Managing Multiple Learning Managment Systems - The High Cost of Choice

Xyleme

In this environment of too much choice, the buying decision is complex and drawn out, and the unintended result is that learning organizations often end up implementing more than one LMS. Expensive maintenance The maintenance nightmare begins when you make changes to a course that’s already been dispersed through multiple LMSs. Did you know that today there are approximately 500 Learning Management System vendors in the market?

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Data-Driven Decision Making: Promises and Limits

Irving Wladawsky-Berger

This Big Data comes from location data from your cell phone and transaction data about the things you buy with your credit card. Data mining and similar analytical methods are most applicable in the ordered contexts, whether simple , - having a clear cause-and-effect relationship that the analysis can uncover, - or complicated , - which unlike simple contexts may have multiple options and answers which can be analyzed, evaluated and compared prior to making a decision.

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Artificial Intelligence is Ready for Business; Are Businesses Ready for AI?

Irving Wladawsky-Berger

A successful program requires firms to address many elements of a digital and analytics transformation: identify the business case, set up the right data ecosystem, build or buy appropriate AI tools, and adapt workflow processes, capabilities, and culture.”. A common theme throughout the report is that the same players who were leaders in the earlier waves of digitization and analytics are now leading in the AI wave. AI is now seemingly everywhere.

5 impacts of Apple’s app store subscription model on experience design

Adaptive Path

But what does the change mean for experiences and experience design? once for an app that you might or might not like, but a $25-plus subscription isn’t necessarily an impulse buy. This means consumers want to try it out before they buy it. Bottom line: If your trialing/demo experience sucks, people won’t buy your subscription.

Design 209

The Future of Social Media

Kevin Wheeler

Analytical tools are being applied to “grock&# your likes, dislikes, political persuasion, and personality so that both marketing and recruiters can more effectively screen you in or out of a job or persuade you to buy a service of product.

On marketing’s terminal addiction to personal data fracking and bad guesswork

Doc Searls

times more likely than Laggards to incorporate unstructured data into analytical models” The pipes are called: Customer Sentiment. 1) We are always in the market to buy something. All three of those will change. Quit fracking our lives to extract data that’s none of your business and that your machines misinterpret. — New Clues, #58.

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[shorenstein] Managing digital disruption in the newsroom

David Weinberger

Processes : They’ve done a lot to change their newsroom processors. We also need better realtime analytics. We’re not pushing for digital change because we want to but because data backs up our claims. About frictionlessness: It’s so easy to buy goods. Even buying a necklace. Q: Analytics? The three legislators who can change a law?

Top 10 eLearning Predictions 2011 #LCBQ

Tony Karrer

Learning Analytics 6. Analytics will be the buzzphrase of the year. Convergence of educational institutions to the supply chain of corporate training will change the supplier landscape. This month's #LCBQ is the first with the Big Question Thought Leaders.

Social Business: e-business 2.0. and Beyond

Irving Wladawsky-Berger

It is a company that engages its employees and clients in a two-way dialogue with social tools, is transparent in sharing its expertise beyond its four walls, and is nimble in its use of insight to change on a dime. This requires a coordinated, three-pronged approach, with leadership driving the initiative, human resources supporting the necessary cultural change, and IT providing the necessary tools.

A Time of Institutional Recomposition

Irving Wladawsky-Berger

There is little question that our economy, our society and just about all our institutions are going through major structural changes mostly caused by the digital technology revolution that has been all around us for the past several decades. Such technology-based structural changes are not new. While sharing a number of similarities, each such period of structural change has its own distinct character. I am well aware of the difficulties of implementing these changes.

MOOCs for Development - Day 2

Stephen Downes: Half an Hour

elite education - experts/authors as doctors, solving the ''knowns'' - cooperative - we''re neighbours, articipation and buy-in necessary - the Global Generation - development is a generational; responsibility to protect the future''s sustainability - like radio, TV, MOOCs can impact millions - don''t want to show up with tech and not address core issues - elite education is. The Challenge of MOOCs Panel Stephen Downes Please see my presentation and audio here: [link] N.V.

[aif] Re-imagining public libraries

David Weinberger

On the other side, as the world of information changes, we’ve been experimenting with learning through experience. are all changing. BB: Our model for sharing knowledge is changing dramatically because of the law. As the environment changes, so will the spaces. BB: Patron driven acquisitions has us buying books when users want them. TG: That’s where you have to be careful about these decisions made by the analytics of usage

Beyond Free ? Open Learning in a Networked World

Stephen Downes: Half an Hour

It''s not simply the money, but it''s the background, the expectations, the culture, and the values that money can buy." And they''re saying what we really need is a culture change in the institution, that what we really need is accountability – perhaps to the BMO financial group that offered this study. or you can buy the season for $29.99 or maybe you can buy an open access, public domain work for who knows how much. More money won’t fix need for change in education.

[2b2k] Jon Orwant of Google Books

David Weinberger

He’s giving a talk to Harvard’s librarians about his perspective on how libraries might change, a topic he says puts him out on a limb. Maybe a library should buy lots and lots of different e-readers, in different form factors. We could each have our own virtual rooms and bookshelves, with books that come through various analytics, including books that people I trust are reading. Analytics of multifactor classification (subject, tone, bias, scholarliness, etc.)

The 2016 Look at the Future of Online Learning

Stephen Downes: Half an Hour

And the third was the set of global changes happening, from the rise of Asia to the increasing urbanization of society, and the stress on resources and reserves. Listen to this, from the 'Context' section: "it it is not technology that drives adoption; it is the institutional strategy, the changing nature of the student population and the decisions of individual instructors and faculty members." The word 'institution; connotes defiance to change.

Customer Learning

Jay Cross

It’s the way we adapt to change. It’s a marriage of informal, self-service learning and business analytics. Web-based analytics are easily baked into online communities such as this, and Google now provides a service that enables a Web site to compare itself to its peers. They buy more. Analytics inform marketing decisions. Administrators monitor changes in customer interests and behavior. Customer Learning , CLO magazine, December 2008.