Nonlinear Thinking

Smart Grid: The 5 Minute Overview

 

 

 

Business Models and the Internet of Things

Two topics close to my heart - Business models and the Internet of Things

 

Big Data and the Science of Storytelling

Big data, and the analytics that make sense of the exponentially growing volumes of it, seem to be top-of-mind across the business landscape and increasingly central to both strategic and tactical decision making today.  In certain realms, marketing comes immediately to mind, it possesses the potential to become the central unifying force that moves the practice further from art and closer to science.  But, with big data has come big challenges in using the data for practical and impactful purposes.

That is why telling stories built upon data and analytics will become the critical manner for articulating the value buried deep in the lines and columns of huge stores of data. Narrative has been foundational for communication since words were first spoken.  It is the way to simplify and make sense of complexity in our lives, our businesses and our world.

Storytelling is central to the human experience.  As humans, we are wired to understand the connection between cause and effect via stories.  We think in narratives all day long.  Whatever our physical world may look like and however we choose to move through it, it is the narratives we create and pass along that bind us and the places we inhabit in a level of coherence that enables progress toward goals, actions and results.  Of course, this is not new.  What is a more recent element of the story making and telling process is the ability to incorporate the immense amounts of data that we can now generate and aggregate into a data-driven narrative through the use of analytics.

Data tells you what’s happening. Stories tell you why it matters.

This is where “the rubber meets the road” in the world of big data.  Data is inert until animated by the mathematical models that transform it into elements of insight that can be woven into a narrative that makes the complex simple and the overwhelming into something digestible and understandable.  With a data-driven story, hundreds of millions of rows can be distilled into a unique story. By following that narrative, it’s much easier to understand what’s going on beneath the surface. The data and corresponding analysis can tell you what’s happening, but you need a story to articulate the importance and the potential impact, allowing you to make decisions that are more targeted and supported.

But, storytelling is about more than simply understanding and articulating one’s world, though that is critically important.  Stories that incorporate data and analytics can be catalysts for change, driven by the insights and actions that result from “crunching the numbers”.  The impact of big data can be extraordinary with the potential to influence much of the way things will be done in the future but that requires moving out of the realm of the quants.  Telling the stories, with data and analytics, can communicate the who, what, how, when and where of the business, creating context for making strategic and tactical decision, both big and small.  To tell a great story with data and analytics, data scientists must begin to think like storytellers.

Decision science has been around for decades but computing power, communication speeds and smart technologies have driven the need for better analytic tools.  Big data is big and getting bigger and our methods and means of analysis have become faster, finer and more robust and that creates both opportunity and threat for the enterprise.  Extract insights from the data and craft a story that resonates with key constituencies and you create competitive advantage.  Bore them with spreadsheets and charts and you just may find yourself out of business.

Big data and analytics have now entered the realm of must have for the enterprise to realize the greatest success.  Storytelling has always been thus.  The combination has the potential to change the way we do everything. But the holy grail has to be the story; the story that communicates what is happening in the business and what can and needs to be done to address the challenges and exploit the opportunities that the analysis uncovers.

Perhaps most importantly, though, stories motivate action. And in today’s world of information overload, it’s crucial to be able to make informed, actionable decisions based on all of your data. 

By using analytics to create a compelling story, big data can become the transformational force that it’s promise has suggested it can be.

 

. 

Surprising Stats Regarding the Internet of Things

CMO.com publishes a weekly column, "Mind Blowing Stats"  that collects disparate and sometimes arcane data points about a specific topic.  A recent edition of the column highlighted the great traction and movement forward that IoT is achieving though most people, and companies, don't recognize how fast the technology is being embraced.  From the column:

1. In 2008, there were already more "things" connected to the Internet than people. By 2020, the amount of Internet-connected things will reach 50 billion, with $19 trillion in profits and cost savings coming from IoT over the next decade.

2. Connected homes will be a huge part of the Internet of Things. By 2019, companies will ship 1.9 billion connected home devices, bringing in about $490 billion in revenue. Google and Samsung are already ahead of the pack. Google bought smart thermostat maker Nest Labs last year for $3.2 billion, and Samsung purchased connected home company SmartThings for $200 million.

3. Right now, most IoT smart devices aren't in your home or phone; they are in factories, businesses and health care. By 2025, the total global worth of IoT technology could be as much as $6.2 trillion--most of that value coming from devices in health care ($2.5 trillion) and manufacturing ($2.3 trillion).

4. Only 0.06% of things that could be connected to the Internet currently are, which means 10 billion things out of the 1.5 trillion that exist globally are currently connected.

5. By 2020, it’s estimated that 90% of cars will be connected to the Internet as compared to 10% in 2012.

6. The connected kitchen will contribute at least 15% savings in the food and beverage industry by 2020.

7. By equipping street lights with sensors and connecting them to the network, cities can dim lights to save energy, only bringing them to full capacity when the sensors detect motion. This can reduce energy costs by 70% to 80%.

8. GE estimates that convergence of machines, data, and analytics will become a $200 billion global industry over the next three years.

9. More than two-thirds of consumers plan to buy connected technology for their homes by 2019, and nearly half say the same for wearable technology. Smart thermostats are expected to have 43% adoption in the next five years.

10. In 2008, Proteus Digital Health created a pill with a tiny sensor inside of it. The sensor transmits data about when a patient takes his medication and pairs with a wearable device to inform family members if it's not taken at the right time.

11. A whopping 94% of all businesses have seen a return on their IoT investments.

12. Wearables will becomes a $6 billion market by 2016, with 171 million devices sold, up from $2 billion in 2011 and just 14 million devices sold.

13. Currently, 7% of consumers own a wearable IoT device, and 4% of consumers own an in-home IoT device. Nearly two-thirds of consumers plan to buy an in-home device in the next five years, and wearable technology ownership will double by 2015—increasing from 7% in 2014 to 14% by 2015. By 2016, wearable technology is expected to double again and reach a total of 28% adoption rate.

14. Among wearable technology devices, wearable fitness applications and technology stand to see the most growth in the short term, with 13% of consumers planning to purchase within the next year and a total of 33% looking to adopt in the next five years. Smartwatches are the second most popular wearable device, with 5% planning to purchase in the next year and a total of 23% planning to adopt in the next five years.

15. Although the mass adoption of connected technology is likely in the long term, the majority of consumers (87%) haven’t heard of the term “The Internet of Things.”

 

The True Internet of Things

A recent article in the Deloitte Review by Tom Davenport and John Lucker provided some much needed context around the quickly expanding conversations on the Internet of Things (IoT).  Having written about the IoT often over the past 15 years, I have witnessed the term be applied too often to the mechanics of machine-to-machine (M2M) communications with less thought given to the broader impact of all those devices connecting and sharing information and data.  While we are still trying to get our hands around Big Data and ensure that we realize all the value we can derive from that aggregation and analysis, IoT will almost certainly create more data, often in much greater detail, than what many have imagined big data will comprise.  For Davenport and Lucker, the real imperative in IoT is to focus on the integration, analysis, value-add, and action processes around IoT data.  To that end, they define IoT as much more than M2M .

The “Internet of Things” (IoT) is often described as a collection of connected sensors, but it is actually a much more complex concept. It involves not only the connection and integration of devices that monitor the physical world—temperature, pressure, altitude, motion, proximity to something else, biometrics, sound, images, and so forth—but also the aggregation, relationship, and analysis of the information those devices create in order to take action on the situation, and the business and technology changes required to use the data and analyses.

Davenport and Lucker propose a hierarchy of sophistication when leveraging all the data and information created by an IoT ecosystem.

Local Sensing

At this local level of the IoT, the activity tracker is typically connected to one or a few other devices for simple actions and data gathering.

Data Integration

Integration of the data is necessary for analytics and control to take place.  At the moment, this is the most challenging area of the IoT.

The Analytics of Things

Much of the benefit of the Internet of Things lies in our ability to leverage the (useful) data we collect with it.

Cognitive Action

This is the business problem that the IoT is solving for your company or its customers.

The Landscape for the Internet of Things

The growth in Internet of things will far exceed that of other connected devices. By 2020, the emergence of mass-market smart phones, phablets, and tablets, combined with a mature PC market, will result in an installed base of about 7.3 billion units, used by an expected human population of 7.7 billion.  In contrast, the Internet of things will expand at a much faster rate, resulting in an installed base of about 26 billion units at that time. Installed base is the key metric here because it drives the value of service revenue, and it aggregates communications bandwidth and data center activity.

Source: Gartner Inc.

Building the Smart Grid

We always endeavor to uncover and share great treatments of topics aligned with the themes of Nonlinear Thinking and this recent article at Bloomberg.com on the advances being made by investor-owned and public utilities across the U.S. in building the smart grid is one to share.  It provides both some great background on why the smart grid is so badly needed and how it is being built and is excerpted below.

The U.S. utility system sits astride one of the world’s great marvels, the grid. And as with so much of U.S. infrastructure, it’s crumbling because of too little investment and lack of imagination. A $876 billion asset, the grid is an amalgam of almost 7,000 power plants that discharge electricity over 450,000 miles of high-voltage transmission lines and more than 2.5 million miles of feeder lines. All this is managed by 3,300 utilities serving 150 million customers. It’s been called the biggest machine in the world.

It’s also something of a relic. Much of it was built after World War II and little updated since the 1970s. A position paper by the Chicago-based Galvin Electricity Initiative describes the grid as “aging, unreliable, inefficient, insecure and incompatible with the needs of a digital economy” and “in dire need of modernization.”

The basic idea is to refashion the grid to manage electricity distribution in the same way that the Internet manages data. While talk of a smart grid has been around for decades, the concept is gaining momentum -- even urgency -- as evidence piles up showing the aging grid’s shortcomings.

Power outages are up 285 percent since 1984 and the U.S. ranks last among the top nine western industrialized nations in the average time that it takes to get the light back on after power failures. Outages cost businesses as much as $150 billion a year in lost continuity, according to the U.S. Energy Information Administration.

Half of U.S. homes still have mechanical meters that require workers to show up and read them. Utilities deploying such meters have little knowledge of their customers’ energy use or interests beyond a monthly bill; they are simply load.

Beyond improving reliability, the basic idea is this: When all energy-use data is digitized and flows freely between power generators and customers, the smart grid will know exactly how much power is needed, when and where, eliminating much of the waste, overbuilding and guesswork inherent in the current analog system and enabling enormous strides in energy conservation.

Many also see the smart grid as fundamental to the utility system being able to absorb and manage disruptive changes that are remaking the U.S. power paradigm. A surge in rooftop solar has turned tens of thousands of consumers into generators. Power is now flowing two ways in America and regulators and green groups are pushing utilities to integrate more and more of this power -- yet keep the grid stable.  Sensors on the old, dumb grid checked for trouble every six seconds. The new phasor units look 60 times a second. With energy flowing at almost the speed of light, this is a significant improvement.

Such successes give the smart grid momentum, though hurdles remain. A smart grid linked to smart homes and smart businesses raises cyber security and privacy issues. There are remaining technological challenges. An American Enterprise Institute report, while nodding to the virtues of an Internet-like grid, said controlling megawatt hours across a smart grid is far more complex than controlling megabytes on the Internet, analogous to “going from controlling a toy drone to a Boeing 777.”

 

The Growth of the Internet of Things (IoT)

Cisco continues to be among the vanguard of enterprises that are embracing the emerging Internet of Things (IoT).  John Chambers, CEO of Cisco, recently delivered another speech on the concept and the bottom line, from Cisco’s viewpoint, is that the IoT is going to be a $19 trillion profit market in the next few years. That includes $2.9 trillion for manufacturing alone. Internet of Things is becoming the backbone (at least in rhetoric) of Cisco's overall business strategy, and Chambers pointed in that direction once again, stressing that Cisco's IoT game plan combines the company's cloud strategy with data analytics, mobile, collaboration, and most important of all, security.

M2M and the Internet of Things

A dozen years ago in a white paper on emerging technologies I included a section on machine-to-machine (M2M) technology, though at the time that nomenclature wasn’t generally accepted.  My simple example of the power of M2M featured communications among a population of Coke machines in a large downtown area sharing real-time inventory data to allow any individual machine to direct a customer to the next closest machine should they be out of the carbonated beverage that customer desired at that particular time.

That example was fanciful at the time, but M2M has now gained traction as one of the “next big things” as hundreds of companies are combining wireless, Wi-Fi, mobile, web, and context technologies to offer information and convenience in innovative new ways.  The escalating pace of adoption for smart devices – phones, tablets, home appliances, industrial equipment - is creating new demands on enterprises and consumers around the globe which requires new thinking about the connected environment.

M2M technologies allow wireless and wired systems to communicate with other devices possessing the same capability.  M2M uses sensors, meters or like devices to capture event data (electricity usage, temperature, inventory) and share it via network with an application that translates the data into information that can be used by other devices, networks, applications and enterprises.

M2M is a critical platform for the enablement and maturation of the concept of the “internet of things” which includes everything from smartphone apps that control a home's living environment remotely to real-time analytics that help ease traffic congestion and city parking challenges.

The notion of an “internet of things” has been around for a while now.  Kevin Ashton coined the term in 1999.  Of course, a concept is never truly viable until it has its own consortium hence, the Internet of Things Consortium

The Internet of Things (IoT) represents the connection of all machines, devices, sensors, automobiles, cameras, and other "things" to help customers improve operations and save valuable time, money and even lives. The IoT connects places such as manufacturing floors, energy grids, healthcare facilities, and transportation systems.

With cloud infrastructure becoming more prominent, M2M applications have expanded beyond a one-to-one connection to become a system of networks that transmits data to personal appliances. This has made it far easier to effect M2M communication and lessened the amount of power and time necessary for information to be communicated between machines.

The critical dynamic here, and one that has been growing for at least 15 years, is that smart devices connected to the internet would eventually far outnumber the people that would be connected to the internet.  Voila! We are there.  Per Cisco, over 12.5 billion devices were connected in 2010 and Cisco’s Internet Business Solutions Group (IBSG) predicts some 25 billion devices will be connected by 2015, and 50 billion by 2020.

ERP solution provider SAP has begun to explore M2M and recently conducted a survey among IT decision makers on the impact, current and forecasted, of M2M.  Some interesting data points that emerged from that survey included:

• 85 percent of IT decision makers (ITDMs) think that M2M is a natural technological evolution and will advance the "consumerization of IT" trend
• 82 percent think that M2M interaction enables businesses to respond to real-world events
• Sixty-five percent of ITDMs think increased workforce mobility is the biggest opportunity for M2M
• 65 percent think the major challenge in M2M is managing and analyzing the real-time data.
• By year's end:
  • Mobile devices will outnumber the human population
  • Data volume will reach 4 billion terabytes
  • 90 percent of consumer-connected devices will have access to some personal cloud.
  • SAP estimated that by the end of 2020, there will be 24 billion connected devices and by 2015, 35 percent of mid-to-large organizations will adopt in-memory computing

The possibilities for machine-to-machine in concert with other emerging technologies are extraordinary. Almost every machine or device has the potential to become connected, creating interactions with other technologies and services and bringing significant impacts to processes in and across all industries.

As the notion of an “Internet of things” becomes increasingly mainstream, businesses will incorporate machine-to-machine technology to gather and use information towards both strategic and tactical ends. The end result will be new products and services that will drive new revenue streams and reduce costs for businesses.