IoT has become a major focus area for mobile network operators worldwide. However, one fundamental question remains: Where are the real IoT business opportunities for MNOs to strategize and achieve volume, scale and growth?
First, let’s be clear — IoT is not just an isolated business segment, but it is an integral part of a bigger digital transformation strategy. Some operators are already in advanced stages with a mature IoT strategy in place, while others are lagging behind or somewhere in between.
It’s no secret that most mobile network operators (MNOs) face challenges in the commoditized voice and data markets while experiencing saturated subscriber growth. Additional challenges come from technology disrupters and global digital platform players that have become technology havens, attracting fresh innovation, large investments and financial market attention.
However, MNOs still have a solid position in regard to the ownership of their customers’ engagement, be it consumers or enterprises. MNOs will eventually be able to generate long-term IoT growth in the broader digital transformation landscape, where digitization has begun to transform a wide range of other industries.
First, let’s look at past lessons learned from two examples: media content monetization and mobile payment.
In the first example, leading MNOs realized how critical a media content strategy was to enabling growth and successfully moving up the value chain. Different enabling strategies were put in place, including the acquisition of media channels, the creation of partnerships and the building of media content delivery platforms. All of these have enabled MNOs to monetize, bundle new subscription-based services and generate higher data traffic on their networks.
In the second example, specifically in emerging markets, MNOs have created, through partnerships with the financial sector, new purpose-built payment services around their low ARPU customers to execute secured mobile payment transactions. These services have enabled a wide range of community-driven business models.
The main lesson learned from these two examples is that MNOs’ strong position in customer ownership and engagement combined with a deep understanding of market needs and dynamics has been key to driving new opportunities.
In the era of digital transformation, IoT is bringing a new set of data attributes that relate to devices and sensors associated with customer data in an ecosystem — let’s call this device data.
For example, one customer might have a car, phone, medical device and smart watch, and she may bike or use public transportation and she also visits the doctor, lives in a farm or smart city, travels, consumes electricity and water, and goes to work, school, shopping and so forth. All surrounding and embedded devices and sensors will generate a huge amount of data that relates to this specific customer in one way or another. The amount of device-generated data will surpass the customer’s data over time, and will both eventually converge.
As the IoT market begins to mature, we will find the amount of converged customer and device data will form unique new IoT opportunities to explore. This converged data holds many promises for new opportunities and will proliferate in many day-to-day industries, such as healthcare, transportation, smart cities, utilities, retail, energy, smart living and wearables, in developing and developed worlds alike. In many cases, this converged data proliferation will also be driven by evolving community-based activities.
MNOs can play an essential role in using their customers’ and enterprises’ ownership by thinking in this way. This will also require putting strategic plans in place to enable user integration across multiple industries through IoT aggregation platforms, data integration tools, developer and API-centric services, secure authentication, on-demand capacity, data analytics and integrated flexible billing capabilities, to list a few.
Equally important, innovation to enable business integration, data contribution models and data sharing incentive mechanisms must be culturally motivated. With socioeconomics as the underlying baseline, MNOs can take a more active and leading role with regulators and data policymakers to adapt to a data-driven mindset. This will require further business and data integration capabilities with a service-oriented approach, enabling a cross-industry digital transformation and thereby creating new possibilities.
It’s important to note that this won’t happen overnight, but it surely will happen fast — depending on how quickly MNOs’ strategies are put in place and adapted.
All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.
It was just over a year ago when the Mirai botnet made its dramatic debut on the world stage. After initially flooding a security journalist’s website with traffic, it went on to grind the internet to a halt for millions of users. The botnet did this by overwhelming Dyn, a company that controls much of the internet’s domain name system infrastructure. Since then, variations of the malicious source code have been used in a number of high-profile attacks on internet infrastructure.
Mirai and its offspring are self-propagating botnets that target and infect poorly protected IoT devices by exploiting people that repeatedly use default usernames and passwords. Once hijacked, these devices have been used to mount some of the biggest distributed denial-of-service attacks we’ve ever seen.
In some ways, enterprise IoT security is being managed a bit like IT security was way back in the ’90s — as an afterthought. This has to stop. After all, we forecast that there will be 20 billion connected IoT devices by 2023. Clearly, there are new and different security requirements than there were in the past.
IoT devices are being targeted for many reasons. Often, poor understanding of enterprise IoT security leads to weak protection for many IoT devices, which makes them easy targets for hackers.
Many IoT devices still don’t have advanced security features. This is especially true of simpler devices, such as a temperature sensors, which have limited processing power and basic operating systems. As they are designed to be plugged in and forgotten about, owners tend not to do security updates frequently, if ever, making it quite easy for an attack on such devices to go unnoticed.
In a connected world, these simple devices can be connected to more critical systems further up in the network. If even a small, simple device malfunctions or is tampered with, it can lead to serious security issues.
The Mirai botnet was an eye opener, not least because it neatly illustrates that the IoT industry is facing ominous threats and that we need to prioritize securing the IoT ecosystem. But what can be done to help secure the IoT?
In my opinion, the prevalence of insecure IoT devices makes it likely that, for the foreseeable future, they may be one of the main entry points for future attacks on mission-critical systems. The silver lining is that IoT botnets can be averted if IoT vendors follow basic security best practices.
In fact, all participants in the IoT ecosystem need to have security as a top priority, from device manufacturers, through networks to platforms and applications. Which means security is no longer a “nice to have” add-on feature. It is a necessity.
Thankfully, enterprise IoT security is steadily becoming an issue of high concern. Measures are being taken by many IoT vendors to prevent security breaches at the device level, and efforts are being made to tackle major disasters before hacks occur.
It’s still not enough.
When you’re going up against expert hackers, you can’t partner with amateurs or you risk paying the price. To ensure their customers’ telco infrastructure is secure from complex attacks, IoT vendors must work with competent partners whom they can trust.
All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.
The far-reaching effects of globalization on the manufacturing industry in the United States — and those who work in it — are impossible to downplay. While certain sectors like pharmaceuticals, aerospace and electronics have surged, others have been slowly losing ground. By some estimates, the erosion of manufacturing in the U.S. has contributed two-thirds of the fall in labor’s share of U.S. gross domestic product, according to a recent report from the McKinsey Global Institute — with much of that hitting small and midsize manufacturers the hardest.
Even amidst that scene, the U.S. still accounts for 20% of the world’s manufacturing activity, McKinsey pointed out. Far from signaling a sort of slow demise of manufacturing in the U.S., a host of factors are coming together that can incite a U.S.-based manufacturing resurgence. In fact, the McKinsey report finds that the U.S. could boost annual manufacturing value added by up to $530 billion (20%) over current trends by 2025, and create more than 2 million jobs.
How can the U.S. achieve these targets? With Industry 4.0 technologies (IoT and related technologies) that will enable U.S.-based manufacturers to hone greater efficiencies in production, streamline labor costs and even lay the foundation for developing service-driven business models.
In many ways, manufacturers have been the earliest adopters of base IoT technologies — as operational technologies have for decades used sensors and RFID technology to automate supply chain management and ensure equipment health and safety. With the advent of new IoT technologies, the data from those machines and processes can be used in new ways to drive further efficiencies in asset management and the supply chain.
Taking a closer look, here are some ways industrial IoT technologies can help manufacturers:
Boost efficiencies by reducing downtime. Predictive maintenance is the single biggest driver for industrial IoT implementations. Enabling a piece of crucial equipment to “tell” a plant manager when it deviates from standard temperature or vibration parameters means the team can plan service before the equipment breaks down, potentially avoiding delays in production and all the ripple effects of associated costs. In more advanced scenarios, action can be automated all the way through ordering the parts and scheduling the work order to fix the issue long before it becomes a problem.
Enable remote monitoring and equipment maintenance. Gartner recently reported that nearly half of the 200 companies it surveyed either had digital twins — which use IoT technology to create a digital mirror of a physical asset — in use or were planning to implement them within the next year. The number of participating organizations launching digital twins will double in 2018, and by 2022, that number will triple. Digital twins enable manufacturers to accomplish two very important goals. They reduce the complexity inherent in industrial IoT development, which can require embedded programming skills not often in rich supply with traditional IT developers. And subsequently, digital twins can bridge the IT and OT worlds by building a digital thread, of sorts, which connects disparate systems to enable visibility and traceability.
Reduce energy consumption. U.S. manufacturing energy consumption increased between 2010 and 2014 for the first time in nearly a decade, according to data from the U.S Energy Information Administration. Equipping factories with smart thermostats and smart lights can enable cost savings, and further integrating unstructured data sources can bring even greater reductions in overhead costs. In a use case detailed by Cognizant, IoT-enabled HVAC systems also offer integrated weather data and prediction analysis to help manufacturers understand expenses and plan energy usage.
Training the next generation. With impending retirements of the most experienced workers, U.S.-based manufacturers will face the difficult challenge over the next decade of properly training the next generation for these crucial roles. Companies like Honeywell are working to marry IoT technologies with augmented reality to meet this need. In one technology solution, workers donning wearable sensors will collect data on their job as they move through it in real time, which will then be used to create immersive training and competency development.
By using IoT technologies, U.S.-based manufacturers can lead a data-driven manufacturing resurgence — gaining efficiencies in the way processes are currently managed and uncovering ideas on how to evolve those processes to meet the more service-driven business models the industry is moving toward. IoT enables better visibility into every aspect of the business — something that is crucial for seizing opportunities to digitally transform business models.
All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.
5G holds great promise. The next-generation wireless network will enable large-scale internet of things applications and support blisteringly fast data processing across a diverse array of devices on a massive scale. Today’s 4G status quo will not be an option when it comes to supporting low-latency use cases like mobile 4K videos, virtual and augmented reality, autonomous driving, robotics and a plethora of yet-to-be-conceived innovative services.
But the promise of 5G will remain just that without the all-in commitment by mobile operators to use artificial intelligence.
It’s not that mobile operators are currently failing to harness data. Many are processing user data, network data and, increasingly, IoT data. However, the sheer scale of 5G means that current data analytics capabilities must evolve. That means operators must invest in AI if they expect to take full advantage of the potential of 5G.
There are two complementary areas for the application of AI. First, as a productivity driver in the product development process, and therefore time to market; and second, to power autonomous intelligent platforms for IoT and other customer-facing services. Together, the tangible benefits of AI are significant for operator business growth, margins and the delivery of the all-important customer experience.
The stakes couldn’t be higher. Here is what AI will mean for mobile operators.
AI brings the ability to enhance the development lifecycle. Integrating machine learning across the DevOps process will result in significant productivity gains and faster time to market. Operators already see significant efficiencies from increased automation across DevOps, but more sophisticated forms of machine learning will deliver improved uptime, predictive defect detection and root-cause analysis. These will come from the integration of AI into specialist machine-learning toolchains that can be used to support many use cases.
Beyond development, AI will play a decisive role in managing network capacity, freeing up resources, improving availability and deepening customer engagement.
Smart thinking in an IoT world
Central to the 5G proposition is the technology’s ability to support the demands of IoT. That is, to provide mass connectivity across diverse devices and process data into business insights in real time. To make good on the promise of smart cities and factories, connected cars, telematics and wearables require AI. Gartner predicted there will be nearly 21 billion connected devices by 2020. A handful of operators are finding ways to define and manage virtual network functions, policies, resource consumption and performance metrics to meet this challenge. Today, there are AI-based platforms dedicated to the management and orchestration of networks capable of these tasks.
Data-driven customer engagement
In a 5G world, operators will be judged on their ability to deliver enhanced, contextual services to customers. Advanced data analytics and AI will be essential for delivering these services, in part, because they identify the bandwidth requirements for the customer experience. An AI-powered management layer translates a customer’s intent and uses that insight to configure the network, optimize resources, remediate issues and launch services based on workload models.
This intent-based layer will control physical and virtual networks and network function virtual orchestrators. Operators can further drive customer loyalty by utilizing AI throughout the customer relationship — for example, by providing service recommendations based on existing usage, telemetry and cutting-edge customer care.
As Gartner advised, operators need to do the groundwork now to ensure they are positioned to roll out effective AI technologies for 5G. This includes investing in skills, processes and tools for setup, system integration, algorithm and approach selection, data preparation and model creation.
The bottom line
As consumers are exposed to an increasing array of AI-based applications, their expectations for rich, immersive experiences will dictate the suite of network services network operators must provide. 5G has the power to deliver these experiences, but mobile operators must be realistic about the challenges ahead. They must transition from automation to predictive capacity planning and service delivery. Intelligent resource deployment in areas such as service provisioning, orchestration, network function virtualization and software-defined networking are key.
In the end, the success of a 5G network rollout will depend in large part on the operator’s ability to harness AI across the network value chain.
Amazon has released an unbranded, customizable Dash IoT button under the name Amazon IoT Button. It uses the horsepower of Amazon Web Services to allow you to create out-of-the-box, push-button (literally) functions.
The IoT Button takes the Amazon Dash button and allows a developer to make it do whatever they want. Want a button that sends a text message that you want to play foosball in the break room? Done. Want a button that sends a Slack message that you’ve made a pot of coffee? Done. Want a button that sends a helpful supportive message to someone in your life — an “I’m thinking of you” button? Done.
Part of the beauty of the IoT button is the simplicity of configuration (there’s an app for that — Android and iOS). With these apps you can get the button connected to Wi-Fi, provisioned in Amazon’s IoT platform and wired to basic templated functions. With about five minutes of configuration, you will have your button on IoT and doing something interesting.
Where you take it from there is up to you. Exadel is currently working with a client who has a specific group of users in mind who will benefit from the touch-of-a-button functionality. This button allows them to solve some of the tricky angles related to bringing this push button functionality to users — namely “how do I get it on the internet,” and also the hardware.
Traditionally, if you wanted a hardware technology, even for something simple, you needed to build it yourself or find a way to use off-the-shelf components to make something. The length of time and cost to implement something (even something simple) can be prohibitive. Now the IoT button lets you create a custom technology, with hardware. As long as what you need the hardware to do maps to “press a button and something happens.” What happens can be customized for any user.
There are other types of buttons out there that can solve this, but they usually have to have some type of hub to enable them to connect to the internet, and then, once you do, you’re still going to have to figure out the plumbing to get the button’s press signal to your back end.
Amazon makes it very easy to plug in the IoT button and connect it to its cloud infrastructure. From there you can connect it to other services easily and with little code. A few sample applications that we built used text messages, email and Slack.
Our client’s use case involves not just the button, but mobile apps and web applications. Pressing the button allows our client’s customer to execute a simple transaction when needed without the need for a sign in, app or any other interaction. Just press the button and things happen!
The signal from the app goes to the back end, where it is processed. Then a real-time communication wakes up an app on the concierge’s phone. The concierge can then take care of everything for them. The button can be given to someone, such as a business owner or administrative assistant — an easy way to make something happen.
Of course, there’s a bit of theatre to this, and that’s the intent. This type of always-on, “press a button and things happen” functionality has yet to become ubiquitous, although we are coming closer. Soon, between connected home devices and one-press functionality, we’ll see this type of thing everywhere.
There’s still a lot of bang for the buck here. The IoT Buttons are $20 right now. It might be expensive if you bought a lot of them, but for a targeted use case like this client, where we’re looking at a few hundred targeted users, it can make a lot of sense versus the hardware development costs or custom configuration that may be needed for a different system.
The beauty of the IoT Button is its simplicity. It can be set up and connected simply, and it can pass a command to a cloud application, allowing action to take place. Because of its simplicity and price point, it can be incorporated into a wide range of applications with relative ease.
What else could it do? Anything that expresses a dedicated, repeatable customer desire — order a pizza, place an order, call a taxi, send a notification, publish a tweet, place a notification on a web page. The sky’s the limit.
As recent security breaches have shown, malicious actors are becoming increasingly clever and sophisticated. They break in through unlocked doors, such as weak or nonexistent passwords on IoT devices like security cameras. As billions of devices are becoming connected (including many that have tremendous impact on business processes or consumer safety), security should become a primary concern. But are we really doing enough to mitigate threats? Are we learning from the painful recent experiences? According to NXC Group, nearly half of companies with an annual revenue above $2 billion estimated that the potential cost of one IoT breach is more than $20 million.
Organizations have historically weighed the cost and time of focusing on security as a deterrent, citing time-to-market delays, design complexity, fragmented ecosystems and more. But as the world moves towards a trillion connected devices over the next 20 years, we as an industry must change our behaviors and agree that security is no longer optional or an afterthought. Users need to know and trust that their IoT devices are born secure, upgradable and managed end to end.
As an industry, we have a social responsibility to build secure devices and maintain a high level of security throughout their lifecycle. We need to make it easy for organizations to securely build, deploy, connect, manage and update devices. This is why Arm has worked with our partners to develop Platform Security Architecture (PSA), the first industry framework for building secure connected devices. PSA provides a common set of ground rules and resources to reduce the cost, time and risk associated with IoT security today, simplifying the security consideration process for device manufacturers, vendors and service providers.
Strong IoT security starts by empowering developers with the tools and system-on-chip (SoC) designs needed to securely develop devices at the very beginning of design, without slowing down time to market. They should incorporate multiple layers of protection, scaling from software to silicon implementations, such as protecting against physical attack threats, which can occur when an attacker has direct contact with the device SoC or is in close proximity to it. Organizations should build technologies into separate partitions that mutually distrust each other in case an attacker breaks into one part of the system.
However, even the highest integrity devices built with the latest security protocols need updating as both devices and attack techniques evolve. Whether a smart meter or smart streetlight has been installed in the field five months or five years ago, it will need to be updated as attackers become more sophisticated and identify new attack vectors over the device lifecycle. When we consider the number of devices deployed could range anywhere from hundreds to millions, over-the-air (OTA) firmware updates become a critical requirement to mitigate new threats. Key considerations when designing in OTA firmware for secure devices include:
- Space requirements for storing the newly received firmware upgrade;
- Properly checking firmware signatures before installing them;
- Ensuring enough bandwidth to support a firmware download; and
- Determining how many firmware updates can be supported before the devices shut down if they are running on batteries.
True end-to-end security requires a comprehensive IoT device management technology for protecting connected devices throughout their lifecycle once they are deployed. This includes securely provisioning the device once it’s turned on in the field, managing the updates over the air and securing the communication between the device and the data store. Secure communications should be encrypted and based on widely deployed and tested security protocols such as transport layer security (TLS) and datagram transport layer security (DTLS).
Security is undoubtedly complex and expensive. The industry works relentlessly to consider and try to protect vast attack surfaces, while hackers need to find just one vulnerability to undo all that hard work. It’s time for us to bring security efforts out of the shadows and make it a first-class citizen in our companies. By working together, we can build a safer future for everyone as we move towards a trillion connected devices being deployed over the next 20 years.
There is a cutting-edge technology aiming to increase blanket connectivity, solve for the last mile and provide a new approach to delivering high-quality connections. It is being tested in underserved markets, and technology leaders such as Google and Microsoft are investing heavily in it.
Today, the statements above would be about the CBRS and LAA bands, but five short years ago, they would have referred to white spaces, the unused frequencies between channels allocated to various broadcasting services. The utilization of white spaces hasn’t yet materialized in the way that its benefactors expected, but there are lessons and takeaways that companies in today’s IoT ecosystem should consider from the once popular “next big thing.”
The regulatory battle
One of the reasons that white space initiatives have been slow to materialize has to do with regulations. Many of the TV broadcasters were loath to give up spectrum that they controlled, leaving a challenge for the FCC in terms of creating usable swaths of available spectrum. Similarly, LAA has come into a variety of political and regulatory issues as well. For instance, the New York City mayor’s office has expressed concerns over use of the LAA band due to the city’s heavy investment in Wi-Fi, fearing that there might be interference.
This isn’t to say that usage of CBRS or LAA will ultimately be regulated out of usage, but it is something that companies planning to implement these technologies should be aware of, given the limited growth regarding white spaces.
The last last mile
White spaces were hyped as a solution for providing rural connectivity and solving for the digital divide in the U.S. In fact, Microsoft is still a believer in this approach, planning to provide broadband connectivity to 2 million in people in rural America by 2022. One of the biggest challenges to overcome for the last mile has to do with the actual infrastructure to support connectivity. This can be in the form of fiber that provides backhaul for signals, or the physical towers necessary to broadcast a frequency.
Today, we are seeing some of the same hurdles regarding this issue. Small cell technology, which can be used to create mesh networks for CBRS or LAA, is running into challenges across the U.S. as well. For IoT companies looking to stay ahead of competitor, it’s important to be aware of which bands are gaining access to the infrastructure necessary to maintain connection and which are not.
All of the above
The lack of hype around white spaces shouldn’t be considered as a death knell for usage of the bands, nor should it be a harbinger of bad news for the CBRS or LAA frequencies. Microsoft is still moving forward with white space initiatives, while Charter is rolling out a wireless network based on CBRS. The realities of blanket wireless connectivity, however, will ultimately be more nuanced and inclusive than some sort of “either/or” answer. In fact, the better answer might just be “all of the above.” With more than 20 billion devices expected to have some sort of connection by 2020, creating a network that can support all of them will require a combination of approaches. While CBRS and LAA will be important, white spaces may still have a significant role to play.
In recent years, the “smart city” buzz phrase has become more prominent than ever. What that means is up to interpretation, but the first place we have to start is with how we get around. Public transportation and, increasingly, private mobility companies are the lifeblood of a city — without them, it cannot grow.
Beginning our global transformation into an IoT-enabled society has to begin with transportation for two reasons. First, it will make the biggest impact on the day-to-day lives of average citizens. As we have seen in New York City, the recent crumbling of its subway system has had a daily negative impact on nearly 6 million people. Second, public transportation is the foundation upon which other innovations can thrive. Time spent waiting for a train or a bus is time that isn’t spent on other endeavors, slowing down creativity and wasting more than $60 billion every year.
The possibilities for how IoT can improve how people move around cities is nearly limitless; we like to describe its eventual form as “frictionless mobility.” Picture yourself biking to a metro station, leaving the bike directly outside in an open dock, walking down to the platform having paid in advance on your phone, and walking up to the approaching train. No time wasted, fully without inconvenience or frustration.
We may be closer to this reality than you think. More and more transit agencies across the world are developing real-time feeds for their vehicles, a movement spearheaded by Google, developing what is now known as General Transit Feed Specification, or GTFS. With a common way of formatting the data now in place, it is easier than ever for this data to be harnessed and used in a way that can help the average person.
At TransitScreen, for example, we use this data to create live displays at the place where people make decisions about how they’re going to commute that day — whether it be in their apartment building or at the office. They include public transit systems, bike-share, car-share and ride-hailing services so the viewer is able to make an informed choice about which form of mobility is best for each individual trip.
This is just one of many smart improvements that can be made in the transportation space to make our lives and our cities more efficient. These same sensors providing real-time locations could also be analyzed to determine if a particular route needs more or fewer buses. This could avoid the problem of “bus bunching,” which leads to slower travel and lower capacity overall.
Ameliorating these frustrations is essential not just to avoid headaches, but to help our planet itself. The transportation industry is responsible for 27% of greenhouse gas emissions in the United States, according to the EPA. Creating a better experience overall for people choosing sustainable transportation makes them more likely to take it again in the future. The fewer people who drive alone as a main form of transportation, the better off we will all be. Taking advantage of the IoT-enabled infrastructure already in place is the first step to a smarter future.
“You’ll never find your limits unless you’ve gone too far.” — Aron Ralston, Between a Rock and a Hard Place
The grand vision of industrial IoT is trillions of dollars in economic value and hundreds of billions in needed investments. That prospect alone is enough to make both the end user industry segments and the technology providers alike salivate at the prospect of what the IoT revolution will unleash. With tech vendors pushing hard to enhance IoT adoption and end users all too willing to indulge on the tech provider’s dime, nothing seems quite as right as an IoT proof of concept (POC) to begin with. The end game thus becomes navigating past the righteous POC phase before entering the territory of IoT at production scale. The IoT POC becomes the gateway which we need to mandatorily transcend on our way to IoT heaven.
There however remains a small glitch! The POC purgatory is holding us captive. It’s akin to crossing a chasm that can’t be breached. The POC approach is emblematic of the “look before you leap” psyche that typically pervades any big ticket technology initiative. It’s an eerie reminder from three decades back at the onset of the ERP revolution, where the initial approach was to begin just with financial accounting functionality (despite all ERP talk about integration capabilities!). It was a while before the course correction was applied by implementing all core modules together. The floodgates eventually opened and we then saw the mass adoption of ERP.
A survey by McKinsey revealed that 71% of IIoT initiatives are stuck in POC purgatory (41% in limbo at pilot stage and another 30% in startup phase). Another study by Cisco indicated that 60% of all IoT initiatives stall at the POC stage and that only 26% of companies have an IoT project that they classify as a complete success. While there are definitely signs of some green shoots, those scalable yet limited IoT initiatives are clearly not enough for the trillions in economic value to be realized over the next decade.
Here’s why isolated IoT POCs are a bad idea and key takeaways to avoid the same.
Missing the forest for the trees: Often, the way the POCs are structured is that they work hard to prove that the technology works. What this eventually leads to is that the plumbing works just fine, but the mains remain off. Focusing the POC on purely the technology aspects without a business metrics yardstick is a sure short recipe for disaster. It does get the juices flowing of the technology folks, but the initiative doesn’t get the management buy-in owing to a lack of an associated business case justifying the ROI.
Takeaway: Conduct a detailed diagnostic assessment to pick the right business use case which addresses key business metrics and delivers the right business impact.
Taking a scatter-gun approach: Very often, IoT initiatives get initiated by the diktat of an enthusiastic but largely hands-off management team. The folks entrusted with driving the initiative missing any leadership guidance end up spawning multiple POCs (often with different vendors!). Quality and focus are sacrificed at the altar of quantity and giving everyone a shot at the freebie POC.
Takeaway: Ensure a holistic approach with a concerted focus (you can’t possibly take four different tech stacks to the production phase). Pick complementary partners wisely after a thorough evaluation and co-create with them.
Inhibiting the law of accelerating returns: Ray Kurzweil’s law of accelerating returns states that while we humans are linear by nature, technology is exponential. Constraining an IoT initiative within the bounds of a narrowly defined POC translates to holding it captive, clipping its wings and not allowing it to take flight — which goes against the law of accelerating returns. The end result is that the end outcome has limited overall appeal since it focuses on a very tiny dimension, works off a limited sliver of data and is poor on meaningful insights.
Takeaway: Ensure that even the POC has a reasonable scale (functionality and complexity), uses adequate data and is supplemented with the right context to be representative of real-life scenarios.
Taking the road to nowhere: Quite often, there is an excessive focus placed on the POC without defining a clear roadmap on how the POC will transcend into a full-blown production rollout. Once the POC is over, the metrics measurement is hazy, the next steps are unclear, the major stakeholders are not aligned and the nuances needed to scale the POC have not been addressed. The POC stays stuck in a quagmire.
Takeaway: Define the roadmap from POC to production and ensure adequate socialization with key stakeholders who will ensure successful transition to production.
The (false) lure of machine learning nirvana: Crawl, walk and run — that’s how life works. Expecting machine learning to give instant gratification is a blunder. Machine learning projects take at least a few months of arduous efforts to collect and curate the data and tweak the algorithms to eke out the relevant insights. Even then there is no silver bullet, no single big-ticket item. It’s all the small analytic victories that add up over time, so expecting a single isolated POC to magically deliver insights is a myth.
Takeaway: Have realistic expectations of what machine learning can deliver and in what time frame. Ensure that the use case has enough fuel (i.e., data) to fire the machine learning algorithms.
In closing, although the industrial IoT revolution is for real, we are bound to witness these early false starts and growth pangs. Significant barriers related to leadership, skills and expertise, ROI quantification, security and implementation still need to be surmounted to realize the true promise of industrial IoT. As with other tech adoption, we will eventually cross the chasm to scale the industrial IoT initiative — and hopefully quite soon. Until then, we are stuck between a rock and a hard place!
The internet of things is facing a dilemma. While connected devices are expected to dominate every aspect of our lives in the coming years — and already outnumber humans in terms of a basic headcount — belief in the ecosystem’s security is still lacking, and has a long way to go before businesses and individuals fully invest in its potential.
In a recent poll (note: registration required) of IoT professionals, 54% expressed concerns around current standards of IoT security. Take into account that 56% of these same professionals expect every single device around us to be voice-enabled within 10 years, and you have a tension that’s only set to grow.
Connecting technologies, not just devices
The answer may lie in the complete opposite of the traditional notion of centralized data — the decentralization of data. In other words, blockchain.
Many see blockchain as the tool to bring scalability and privacy to the IoT universe, and 68% in the recent poll expect integration between the two technologies within five years. It has all the signs of a successful marriage too, with geographically distributed IoT devices suited to the similarly decentralized peer-to-peer ledger.
Individual sectors are already seeing blockchain disruption — for example, the music business with the protection of artists’ intellectual rights, and financial institutions in the handling of payments and guaranteeing the integrity of transactions. It’s not far-fetched to see the synergies of multiple technologies as the next step in the innovation timeline.
The specific question for IoT, and those businesses that see such great potential in connected devices, is what type of blockchain can wield the greatest rewards.
The other blockchain
Most people will now be familiar with public blockchains through the stardom of Bitcoin. The democratization of payments has seen blockchain technology become part of mainstream conversations, but private ledgers are largely unexplored.
Private blockchains, which allow only a preselected group of people to maintain the integrity of the ledger, can empower businesses to be more intuitive in the way they manage IoT devices. Most businesses do not operate in silos and have to abide by certain regulations or bodies of authority. It’s not practical to reinvent every industry in the mold of Bitcoin, so permission-based ledgers may hold the key to scaling IoT sensibly, while all the while maintaining compliance with external structures.
Take agriculture, for example. IoT is already helping optimize supply chains and deliver smart logistics — tracking assets from a farmer’s field all the way to the shop floor through a web of connected sensors. A partnership with blockchain, however, can take this one step further, guaranteeing food safety or ensuring the correct farm is given credit by hosting information on a living ledger.
What’s more, farmers must abide to strict codes when it comes to what they can and cannot deliver to consumers, whether that be hygiene standards or conditions of livestock. In uploading a wealth of IoT data to private ledgers, a form of cryptographic auditing is ensured, broken down into simple inputs and outputs.
The joy of blockchain technology is that in coding the sensory data of machines directly onto the ledger, validity can be guaranteed from the first entry onward. In short, IoT and blockchain are self-reinforcing.
Preparing for the machines
Optimizing current systems is one half of the story, preparing for the future remains the other. Industrial IoT is revolutionizing how we manage supply chains and logistics. IoT-enabled devices allow for real-time, predictive maintenance of machines, with the more devices connected to the network contributing to a smarter system. This, however, also raises threat levels, with each new connected device another potential entry point for attackers.
Connected devices have already altered the way businesses face up to security. There’s currently no uniform or overarching standard, so it’s up to individual businesses to take the lead. For those without the resources to design platforms with security in mind from the outset, it can often be an arduous task staying in control. Now imagine when AI becomes commonplace within manufacturing and the rate at which robots exchange data becomes exponential. Private blockchains may just prevent future issues when interactions go beyond single-thread conversations and into multi-threaded ones between machines themselves.
Both IoT and blockchain technologies are here to stay. Their convergence is largely expected, and the potential for them to benefit businesses is immeasurable. On one hand, security concerns can be addressed by distributing information across the ledger; on the other, IoT and blockchain can work together to disrupt many of the processes we have come to accept.
Private blockchains allow businesses to pick and choose the most favorable features of decentralized lists, and maintaining control in what is contributed to it at the same time. The result, if managed correctly, could change the very way we understand and utilize the internet of things.