Social Physics - Reinventing Analytics to Better Predict Human Behaviors

Irving Wladawsky-Berger

But, at the same time, mutations and innovations will vary among different groups, with natural selection favoring those human groups better able to adapt to changing conditions.

The need for innovation across boundaries and the power of big data analytics

Ross Dawson

The primary themes of the report were around spotting opportunities, innovation, transparency and trust, personalization, and 24/7 availability, and the implications for business.

The Promise and Challenges of Health Analytics

Irving Wladawsky-Berger

On February 24 I attended a workshop in MIT on the Future of Health Analytics. In a recent paper , Ausiello notes that health analytics has the potential to become the next frontier in medicine, driven by the confluence of three key revolutions: .

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.

The Competitive Value of Data: From Analytics to Machine Learning

Irving Wladawsky-Berger

The article noted that regulators, policy makers and academics in Europe and the US are increasingly concerned that the vast data assets of digital giants could become a competitive barrier to startups and innovation. Business analytics predates the big data era.

Institutional Innovation - I Have a Dream

John Hagel

Today they are an unnatural bundle of three very different and often conflicting business types: infrastructure management, product innovation and commercialization, and customer relationship businesses. Everyone talks about transformation these days, but the term is used so loosely that it’s begun to lose all meaning. I recently wrote a blog post suggesting that the ultimate test of transformation is whether the caterpillar became a butterfly – is it so different that it’s unrecognizable?

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.

The Internet, Blockchain, and the Evolution of Foundational Innovations

Irving Wladawsky-Berger

The concept of disruptive technologies, as defined by Clayton Christensen 20 years ago, has become widely accepted as a way of thinking about innovation-driven growth, but it’s been often misunderstood and misapplied.

White House: Innovation in Higher Education

George Siemens

The invitation was somewhat cryptic, but basically stated that the focus on the meeting was on quality and innovation. This invite was then followed a week later with a link to a post by Ted Mitchell, Undersecretary of Education, on Innovation and Quality in Higher Education , to help prepare for the conversation. This is the main space to watch in identifying which innovations will have legs and which ones will fail to get traction.

The Management of Disruptive Innovations

Irving Wladawsky-Berger

The management of disruptive innovations is very different when looking at relatively simple or self-contained technologies, products or services versus highly complex platforms and infrastructures. A lot of the hype you often hear when new innovations come about is the result of people not properly understanding the different dynamics that apply to simple versus highly complex innovations. The dot-com era was famous for its many innovations, but also for its hype.

Learning Analytics: Big Data Applied to Training, Teaching, and Learning

Beth Kanter

Learning Analytics comes from a report about the impact of emerging technologies for practitioners in a field. Two or three years to adoption: Learning Analytics (K-12/Higher Ed), Open Content (K-12), Games and Gamification (Higher Ed). Learning and Knowledge Analytics.

The Future of Learning Management Systems: Development, Innovation and Change

Stephen Downes: Half an Hour

A big long-term trend to watch: initially there was a lot of emphasis on analytics, where they say ‘we will analyze the data’. The big thing is data access; analytics is more secondary.

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Innovation in an Age of Austerity

Irving Wladawsky-Berger

On December 7 I participated in an Innovation Summit sponsored by the UK Innovation Research Centre (UK-IRC) at the University of Cambridge. The UK-IRC is “a collaborative initiative for cutting-edge research and knowledge exchange activities on how innovation can make businesses more competitive, improve public services delivery and help the UK meet the social, environmental and economic challenges it faces.”

Reflections on Innovation, Productivity and Job Creation

Irving Wladawsky-Berger

For example, over the past year I have given a number of seminars on Technology and Innovation in the Service Economy. I have also been thinking a lot about the impact of these innovations on the productivity of the service sector of the economy in general, and in particular, on the kinds of jobs that we can expect to be created over the next decades to replace those jobs that might decline or disappear as a result of such productivity improvements.

An innovative workshop on radical management

Steve Denning

In these three days ( March 19-21 in Washington DC ), you will discover how to use radical management to thrive in the 21 st Century creative economy and the world of continuous innovation. Have you ever wondered how your firm is going to survive and thrive as the world economy goes through a fundamental phase change—from industrial bureaucracy to a creative economy of continuous innovation? Why innovation happens “despite” the system, not because of it.

Libary Lab funds library innovation projects

David Weinberger

The Library Innovation Lab [ blog ] that Kim Dulin and I co-direct had a few of its proposals accepted: Library Analytics Toolkit : Tools to enable libraries to understand, analyze, and visualize the patterns of activities, including checkouts, returns, and recent acquisitions, and to do so across multiple libraries. LibraryCloud Server : Build and maintain a web server that makes available to all Harvard library innovators data and metadata gathered from the Harvard libraries.

The role of informal social networks in building organizational creativity and innovation

Ross Dawson

This is evident in the California Management Review paper I co-authored on Managing Collaboration: Improving Team Effectiveness through a Network Perspective , in which we examined how to improve performance in sales, innovation, and execution.

Irving Wladawsky-Berger: Creativity, Innovation and Design

Irving Wladawsky-Berger

Irving Wladawsky-Berger A collection of observations, news and resources on the changing nature of innovation, technology, leadership, and other subjects. After all, we are talking about innovation. Design adds the more subjective - and equally important - dimensions of innovation.

Getting on the AI Learning Curve: A Pragmatic, Incremental Approach

Irving Wladawsky-Berger

Two-thirds of the opportunities to use AI are in improving the performance of existing analytical use cases,” is the paper’s overriding finding. And, in the remaining 15% of cases, machine learning provided limited additional performance over existing analytical methods. .

Why Innovation is Critical to Help Governments Adjust to the Realities of the 21st Century?

Irving Wladawsky-Berger

Aligning government with 21st century economic realities will require innovations at least as disruptive and profound as those embraced by the private sector. By harnessing major technological shifts and adopting best business practices, we can not only make our government far more productive, but also foster greater innovation in areas ranging from healthcare to education and energy – innovation that will generate economic growth and job creation.”. “We

Social Physics and Cybercrime Detection

Irving Wladawsky-Berger

These patterns can be used to detect emerging behavioral trends before they can be observed by other data analytics techniques. Endor’s analytics engine identified 80 Twitter accounts as potential EOIs because they were similar enough to the positive samples that the agency provided.

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Everyday Technology: Innovative Ways To Do More With Less

Beth Kanter

Note from Beth: Innovation was the buzzword at the Nonprofit Technology Conference! I ran into the good folks at Idealware who offered to do a guest post on the topic – looking at small ways to be innovative. Flickr Photo by Nielio.

Beyond Machine Learning: Capturing Cause-and-Effect Relationships

Irving Wladawsky-Berger

Machine learning is a statistical modelling technique, like data mining and business analytics , which finds and correlates patterns between inputs and outputs without necessarily capturing their cause-and-effect relationships.

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Irving Wladawsky-Berger: Reflections on Leadership and Innovation

Irving Wladawsky-Berger

Irving Wladawsky-Berger A collection of observations, news and resources on the changing nature of innovation, technology, leadership, and other subjects. In this course, I want to examine how to leverage disruptive innovations to significantly transform a business or even a whole industry.

Getting on the AI Learning Curve: A Pragmatic, Incremental Approach

Irving Wladawsky-Berger

Two-thirds of the opportunities to use AI are in improving the performance of existing analytical use cases,” is the paper’s overriding finding. For the vast majority of the use cases, 69%, the key value of machine learning is to improve performance beyond that provided by traditional analytic techniques. And, in the remaining 15% of cases, machine learning provided limited additional performance over existing analytical methods. .

The Jobs Outlook for 2022

Irving Wladawsky-Berger

The survey identified four specific technology advances that are set to dominate business growth over the next five years: ubiquitous, high speed mobile Internet; widespread adoption of big data analytics; artificial intelligence; and cloud computing.

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Blockchain Can Reshape Financial Services… But it Will Take Significant Time and Investment

Irving Wladawsky-Berger

wrote the WEF in a very timely message. “Over the last 50 years, technology innovation has been fundamental to financial services industry transformation. Others include biometrics, cloud computing, cognitive computing, machine learning and predictive analytics.

The Emergence of Industry 4.0

Irving Wladawsky-Berger

Many of these innovations are in their infancy, but they are already reaching an inflection point in their development as they build on and amplify each other in a fusion of technologies across the physical, digital and biological worlds.”.

The Mobilisation Journal: A Way To Spread Learning About Social Change Movements Innovative Use of Technology

Beth Kanter

This is an example of a nonprofit organization that has invested in building an internal learning and innovation network that will lead to improved results for Greenpeace’s environmental mission. Storytelling and Knowledge Transfer :: sharing innovations, lessons learned, fail stories, and emerging best practices. Innovation Incubation :: piloting new ways of working, from practices to technologies.

Presentation to UNCTAD's Advisory Group on "Developing skills, knowledge and capacities through innovation: E-Learning, M-Learning, cloud-Learning"

Stephen Downes: Half an Hour

Finally, in the LPSS, or Learning in Performance Support System, is analytics, competence and assessment , and this is essentially the application of artificial intelligence, and the pattern recognition to identify the ways in which a person can become competent at some skill or task, and the gap between where they are, and becoming competent. based analytics, is that a personal learning record, can extend beyond the limits of the platform.

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The Business Value of Resilience

Irving Wladawsky-Berger

The Industrial Revolution was “as much about process innovations that reduced waste and increased productivity as it was about the application of new technologies,” wrote Roger Martin in a recent Harvard Business Review (HBR) article, - The High Price of Efficiency.

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.”. AI is now seemingly everywhere.

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Become a More Productive, Empathetic, Creative Person With the Help of AI-Based Tools

Irving Wladawsky-Berger

In a recent article in the MIT Sloan Management Review , MIT Research Fellow Michael Schrage proposed a provocative and counterintuitive approach for enhancing innovation and productivity through man-machine collaborations. Instead of just asking how can people create more valuable innovation?,

Becoming a Data-Driven Business: Challenges and Opportunities

Irving Wladawsky-Berger

A few weeks ago, McKinsey published The age of analytics: Competing in a data-driven world , a comprehensive report on the state of big data, and in particular, on the challenges and opportunities a company faces as it strives to become a data-driven business.

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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. Application innovation.

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Customer Experience - the Key Competitive Differentiator in the Digital Age

Irving Wladawsky-Berger

More specifically, the survey asked them about their progress in embracing five major digital trends: big data and advanced analytics, digital engagement of customers, digital engagement of employees and external partners, automation, and digital innovation.

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AI - the Creation of a Human-Centric Engineering Discipline

Irving Wladawsky-Berger

Machine and deep learning are the latest examples of tools like the World Wide Web, search and analytics that are helping us cope with and take advantage of the huge amounts of information all around us. AI is rapidly becoming one of the most important technologies of our era.

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Digital Twin: Bringing the Physical and Digital Worlds Closer Together

Irving Wladawsky-Berger

The myriad possibilities that arise from the ability to monitor and control things in the physical world electronically have inspired a surge of innovation and enthusiasm,” said a 2015 McKinsey report on the Internet of Things.

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Competing Against “Digital Invaders”

Irving Wladawsky-Berger

After analyzing the survey data, - including the use of Watson Analytics to extract inferences from open-ended responses, - IBM published its findings in Redefining Boundaries: Insights from the Global C-suite Study.

The New Era of Smart, Connected Products

Irving Wladawsky-Berger

For the past few years, some have justifiably questioned whether innovation has been going through a period of stagnation , especially when compared to major 19th and 20th century innovations like electricity, cars and airplanes.

A Talk On Fast Innovation, All In One Great Picture - Bob Sutton

Bob Sutton

The ergonomics of innovation -- The McKinsey Quarterly. interview Pixar Brad Bird - Innovation lessons from Pixar Director Brad Bird - Strategy - Innovation - The McKinsey Quarterly. Customer-Focused Innovation. David A Owens: Creative People Must Be Stopped: 6 Ways We Kill Innovation (Without Even Trying). McCraw: Prophet of Innovation: Joseph Schumpeter and Creative Destruction. Davenport: Competing on Analytics: The New Science of Winning.

Human-AI Decision Systems

Irving Wladawsky-Berger

Nor have they integrated the large amounts of data, analytical tools and powerful AI systems now at our disposal into their decision making systems. . Sports analytics are now used by just about every professional sports team in the world.

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Solow Paradox 2.0: The Lagging Impact of Technology Advances on Productivity Growth

Irving Wladawsky-Berger

In a 2014 article , The Economis t pointed out that realizing the benefits from technology and innovation takes time, often decades, and varies hugely from industry to industry. The steam engine and electricity, are each examples of such transformative industrial-age innovations.