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Showing posts from 2016

New Report: 40 Months of Hyper-Digital Transformation

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Forty months is not a lot of time to design, develop and deliver something monumental. Consider that it took 182 years to build the Notre Dame Cathedral in Paris, 20 years to build the Great Pyramid of Giza and 10 years to build the Panama Canal. Executives from digital-leading companies, however, tell us that in just over three years – the year 2020 – 17 different digital technologies will dramatically impact the way they work, and transform the work that gets done, so we don't have much time.  This means that within the next 40 months the exponential growth of digitization and machine learning will fundamentally change how businesses create value, satisfy customers and outperform competitors. This also means that in this same time period, companies must take actions that position them for the next level of success. If they don’t embrace digital, for many it will be game over. To better understand the strategies and technologies that digital transformation winners require,

Virtual Reality Moves to Real with Sensors and Digital Transformation

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I was on a high-rise construction site 34-floors above the city.  I was talking to the construction crew when a fight broke out.  There was an explosion and the floor collapsed.  I removed the virtual reality (VR) goggles and laughed.  It was so real.  The VR solutions provided an incredible experience, almost like being there.  As good as my experience was, it was not reality.  It was a controlled pre-programmed experience - a notional idea.  Today, however, VR, sensors and sensory feedback technologies enable a notional idea to become reality – a Real-Reality. IoT sensors extend our physical senses beyond our physical reach.  Haptic feedback systems enable us to physically feel distant objects and experience events, digital odors can be collected, profiled, transmitted and recreated locally on odor printers, 3D infrared scanners can capture and scale physical shapes and environments and transmit them anywhere to be used by 3D printers or in digital scenes.  We can visualize, sen

How Good is Your Mind at Predicting?

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My friend, Peter Rogers, who lives in the UK was wrong at predicting Brexit, but right at predicting Donald Trump would win.  How did he get one wrong and the other right?  Read about his experiences here. Guest Blogger - Peter Rogers Peter Rogers Predicted Donald Trump I always thought I was particularly good at prediction as a result of me working as a technologist most of my life, but my world was turned upside down after Brexit. It took a long time for me to work out why I got Brexit so wrong, but eventually I brushed myself off and started to read a lot of material on Super-Forecasters. It learned I had been misleading myself for many years.  I thought I was good at non-technical decision-making. I recall looking at the Ladbrokes Swingometer for Brexit and being so sure of a "remain" vote, that I was going to place a large bet.  I was however, wrong. I made the classic mistake of polluting the decision-maker-mindset. In order to forecast accurately I needed t

Digital Technologies Must Disappear in 2017

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Almost a year ago, I wrote these words, "T echnology has reached the tipping point for me, it moved from a help to a hindrance."  The plethora of adrenaline and endorphin inducing mobile apps, 24x7 news, notifications, alerts and updates, drip fed my brain and hindered my  "deep work and deep thoughts."  In Cal Newport's new book titled, "Deep Work" he posits that most knowledge workers need concentration and substantial time, dedicated and uninterrupted, to produce their best work. He argues that a lot of technologies and open office layouts today inhibit creativity, "deep work" and "deep thoughts," and are the very things that are most highly valued, and one of the key differentiators between humans and robots. Newport argues that we must understand and optimize the conditions that enable our brains to work best.  To sum up his argument, constant drip feeding technologies serve to prevent deep thoughts and deep work, our m

The Day Big Data Analytics Died

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The Huffington Post gave Donald Trump a 2% chance of winning, The New York Times 15%.   The best polls, prediction markets and analytics predicted a Hillary Clinton victory in the days before the election, yet they were all wrong.   The national media’s predictive analytic systems failed catastrophically.   Why? Analytic systems require timely data on all the variables that impact a system and measure its performance.   Analytics requires support from an optimized information logistics system (OILS), which describes the a system that manages the full lifecycle of data from collection, transmission, processing, analysis, reporting, data driven decision-making, action and archiving.   An OILS is only as good as the data.  It can only function correctly if it is collecting the necessary data inputs.   For example the sensors in an Internet of Things (IoT) system must be attached to the right “things” that impact operations, to provide full system visibility and insight. The pre-ele

Merging Humans with Enterprise AI and Machine Learning Systems

Artificial intelligence and machine learning systems are made up of code and algorithms, and as such, they work as fast as computers can process them.  Often this means massive amounts of learning can be accomplished every second without stop 24x7x365.  Code doesn't need to take weekends off, holidays, or sick time. Code doesn't get tired. It can recognize complex patterns, areas of potential improvement and problems in real-time (aka digital-time).  Given these available computing capabilities and speeds, what are executives to do with AI and machine learning, when we live and operate in relatively slow human-time, and work within organizations that work at an even slower pace of organizational-time. I believe the first step is to admit we have a problem - the problem is a difference in the speed that computers can operate and the speeds us humans can operate.  The second is to understand what a solution might look like - how humans and computers can best integrate and oper

Mobile Expert Interviews: PowWow Mobile's CEO Kia Behnia

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The enterprise mobility software vendor space has been around for more than a decade, but new start-ups continue to enter the market with ambitions to address unsolved problems and challenges.  In this interview, I ask  PowWow Mobile  CEO Kia Behnia, why an enterprise mobility start-up now?   Kevin Benedict's latest video on mobile commerce trends and strategies: ************************************************************************ Kevin Benedict Senior Analyst, Center for the Future of Work, Cognizant Writer, Speaker and World Traveler View my profile on LinkedIn Follow me on Twitter @krbenedict Subscribe to Kevin's YouTube Channel Join the Linkedin Group Strategic Enterprise Mobility Join the Google+ Community Mobile Enterprise Strategies ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of