Big Data and Analytics, Digital Strategy, Innovation

Digitization Lessons from Google’s Nest

6 Oct , 2016  

By now, most of us have seen or are even using programmable thermostats. One of the recent and more interesting offerings in this space is from Nest. Nest sells a thermostat that captures data about human presence to self learn what heating and cooling decisions are best. Programming is not needed; it learns what is […]

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The Future of the Internet of Things and the Digital Economy: Lessons from the Closure of Revolv

Big Data and Analytics, Digital Strategy

The Future of the Internet of Things and the Digital Economy: Lessons from the Closure of Revolv

10 Apr , 2016  

Revolv is a warning about how the digital economy will operate in the future. Revolv, the innovative home automation hub, that was purchased by Google’s Nest, recently announced that they will stop supporting all devices in the coming weeks.[1] Revolv’s home automation used radio signals to communicate with light switches, garage door openers, home alarms, […]

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Lessons from Nest: Leveraging Big Data for Solving Big Problems – Managing Complex Systems

Big Data and Analytics, Digital Strategy

Lessons from Nest: Leveraging Big Data for Solving Big Problems – Managing Complex Systems

29 Feb , 2016  

Big Data and Big Profits: Nest Optimizes the Mechanical Realm By now, most of us have seen or are even using programmable thermostats. One of the recent and more interesting offerings in this space is from Nest. Nest sells a thermostat that captures data about human presence to self learn what heating and cooling decisions […]

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Lessons on Big Data, Risk, and the Vertical Integration of Wearables and Startups

Big Data and Analytics, Risk Management

Lessons on Big Data, Risk, and the Vertical Integration of Wearables and Startups

4 Dec , 2015  

Lessons on Big Data, Risk, and the Vertical Integration of Wearables and Startups It is amazing how quickly the world of health sensors and wearables has developed. In just a few years, we have seen the wearable market explode with Fitbit, Jawbone, and Apple commanding healthy shares of the overall market that delivered some 70 […]

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The Importance of Automation in your Big Data Strategy

Big Data and Analytics, Digital Strategy

The Importance of Automation in your Big Data Strategy

9 Aug , 2015  

Big Data and the Value of Automated Data Capture The development of analytics that can process data and lead to automation and the removal of workers is very much discussion today. We read about artificial intelligence concerns from technology leaders like Bill Gates and economic leaders like Larry Summers. In fact, the use of data […]

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Big Data and the Value of Automated Data Capture

Big Data and Analytics, Digital Strategy

Big Data and the Value of Automated Data Capture

9 Apr , 2015  

 The development of analytics that can process data and lead to automation and the removal of workers is very much discussion today. We read about artificial intelligence concerns from technology leaders like Bill Gates and economic leaders like Larry Summers. In fact, the use of data and analytics has been removing jobs from various industries […]

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Big Data Driving the Driverless Car: Digitizing Travel A major change to driving and travel is soon upon us. With little doubt, we can expect driverless cars in the next decade or so. However, it is not driverless cars that will change how we travel, but rather the digitization of travel, enabling driverless cars, which will change how we travel. In the earliest versions of automated cars, driverless automation was approached mechanically. An early version proposed vehicles locking into a monorail when on the interstate, for instance. Similarly, early versions of speed control were simply mechanical means for keeping the speed at a designated level, with no specific measuring of the surroundings. The development of sensors and rapid digital processing on cars changed the paradigm for control of the vehicle and its subsystems. Mechanics would be controlled by data, not uber mechanics. Instead of controlling mechanics by brute force, sensors and data allow or a more precise and agile adaption to how vehicles are operated. This paradigm shift and movement to data creation for the purposes of mechanical control has already overtaken the next generation of aircraft. A single flight on a Boeing 787 is estimated to create no less than half a TB of data from sensors. This data is, in many ways, data exhaust. The byproduct of proactive sensors and devices communicating their status and conditions around them. It is reflected in the Internet of Things (IoT) and how connected devices communicate their status even if action is not taking place. Just being connected will create data! Location, availability, and operating status are just some of the basic measures that can be captured on a continuous basis for any autonomous vehicles (even before trip begins). Once a trip is undertaken, data about the trip, deviations from the expected course, energy use, system performance, and specific environmental, traffic, and road interactions are captured. All of this is Big Data that is valuable to engineers, customers, regulators, and other businesses. The future of driverless vehicles includes a radical change in how we travel, owing to the digitization of travel. Soon, we will be able to open an app on our smartphones and summon a driverless car. It might come from Google, Uber, Apple, or a traditional automobile manufacturer. The collection of data begins even before the trip begins. In many ways, the wave of Big Data has digitized vehicle use already. Consider how Uber has digitized car services already. Owning a car is less critical if instead in can be summoned with high reliability and at a reasonable cost, as also in the case of Uber. Data about demand and supply of cars is currently used by Uber to price trips. Once driverless cars are available on demand, digitization of travel will create a new market for travel and the opportunity to seek out new efficiencies on when and how to travel. Data is created about the trip at a granular level allowing for new optimal decisions. In fact, the digital layer controls everything about the trip. By digitizing travel, travel by time of day, destination, route, and even purpose can be ascertained and used to make new optimal decisions. Might this suggest differential pricing? Sure it does. Want to go faster, you can pay for that. Taking the kids to school? Perhaps the local school district picks up part of the cost for the trip. Want to save on travel costs; your driverless car might suggest using the roads at non-peak hours or making long-distance trips at night. Taxing bodies might see the digitization of travel as a convenient means to tax trips based on distance, speed, energy use, or even just popularity and convenience of a road. You get a bill (on your app of course) that includes payments to all the invested parties: driverless car provider, tolls for roads, insurance, and energy use. The implications for how we travel and use vehicles are endless once we have digitized travel. The prerequisite digitized maps are now in place. Sensors allow Google’s driverless car to regularly travel on roads with traffic. Mobile technology is ready to interface with users. Digitizing travel will require Big Data and make new Big Data that will create new markets or travelers and travel providers. It will also change how we travel and pay for travel.

Big Data and Analytics, Digital Strategy

Big Data Driving the Driverless Car: Digitizing Travel

28 Feb , 2015  

Big Data Driving the Driverless Car: Digitizing Travel A major change to driving and travel is soon upon us. With little doubt, we can expect driverless cars in the next decade or so. However, it is not driverless cars that will change how we travel, but rather the digitization of travel, enabling driverless cars, which […]

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