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After so many years evangelizing the Internet of Things (IoT) or developing IoT products or selling IoT services or using IoT technologies, it is hard to believe that today there are as many defenders as detractors of these technologies. Why does the doubt still assail us: "Believe or Not Believe in the IoT"? What's the reason we keep saying every year that the time for IoT is finally now?

It does not seem strange to you that if we have already experienced the power of change that involves having connected devices in ourselves (wearables), in our homes, in cities, in transportation, in business, we continue with so many non-believers. Maybe, because the expectations in 2013 were so great that now in 2020 we need more tangible and realistic data and facts to continue believing.

In recent months I have had more time to review my articles and some white papers and I think I have found some reasons to continue believing, but also reasons not to believe.

Here below there are some of these reasons for you to decide where to position yourself.

Top reasons to believe

  • Mackinsey continue presenting us new opportunities with IoT
    • If in 2015 “Internet of Things: Mapping the value beyond the hype” the company estimated a potential economic impact as much as 11,1 US trillions per year in 2025 for IoT applications in 9 settings.
    • In 2019 “Growing opportunities in the Internet of Things” they said that “The number of businesses that use the IoT technologies has increased from 13 percent in 2014 to about 25 percent today. And the worldwide number of IoT connected devices is projected to increase to 43 billion by 2023, an almost threefold increase from 2018.”
  • Gartner in 2019 predicted that by 2021, there will be over 25 Billion live IoT endpoints that will allow unlimited number of IoT use cases.
  • Harbor Research considers that the market opportunity for industrial internet of things (IIoT) and industry 4.0 is still emergent.
    • Solutions are not completely new but are evolving from the convergence of existing technologies; creative combinations of these technologies will drive many new growth opportunities;
    • As integration and interoperability across the industrial technology “stack” relies on classic IT principles like open architectures, many leading IT players are entering the industrial arena;
  • IoT regulation is coming - The lack of regulation is one of the biggest issues associated with IoT devices, but things are starting to change in that regard as well. The U.S. government was among the first to take the threat posed by unsecured IoT devices seriously, introducing several IoT-related bills in Congress over the last couple of years. It all began with the IoT Cybersecurity Improvement Act of 2017, which set minimum security standards for connected devices obtained by the government. This legislation was followed by the SMART IoT Act, which tasked the Department of Commerce with conducting a study of the current IoT industry in the United States.
  • Synergy of IoT and AI - IoT supported by artificial intelligence enhances considerably the success in a large repertory of every-day applications with dominant one’s enterprise, transportation, robotics, industrial, and automation systems applications.
  • Believe in superpowers again, thanks to IoT - Today, IoT sensors are everywhere – in your car, in electronic appliances, in traffic lights, even probably on the pigeon outside your window (it’s true, it happened in London!). IoT sensors will help cities map air quality, identify high-pollution pockets, trigger alerts if pollution levels rise dangerously, while tracking changes over time and taking preventive measures to correct the situation. thanks to IoT, connected cars will now communicate seamlessly with IoT sensors and find empty parking spots easily. Sensors in your car will also communicate with your GPS and the manufacturer’s system, making maintenance and driving a breeze!. City sensors will identify high-traffic areas and regulate traffic flows by updating your GPS with alternate routes. These IoT sensors can also identify and repair broken street lamps. IoT will be our knight in shining, super-strong metallic armor and prevent accidents like floods, fires and even road accidents, by simply monitoring fatigue levels of truck drivers!. Washing machines, refrigerators, air-conditioners will now self-monitor their usage, performance, servicing requirements, while triggering alerts before potential breakdowns and optimizing performance with automatic software updates. IoT sensors will now help medical professional monitor pulse rates, blood pressure and other vitals more efficiently, while triggering alerts in case of emergencies. Soon, Nano sensors in smart pills will make healthcare super-personalized and 10x more efficient!

Top reasons not to believe

  1. Three fourths of IoT projects failing globally. Government and enterprises across the globe are rolling out Internet of Things (IoT) projects but almost three-fourths of them fail, impacted by factors like culture and leadership, according to US tech giant Cisco (2017). Businesses are spending $745 billion worldwide on IoT hardware and software in 2019 alone. Yet, three out of every four IoT implementations are failing.
  2. Few IoT projects survive proof-of-concept stage - About 60% of IoT initiatives get stalled at the Proof of Concept (PoC) stage. If the right steps aren’t taken in the beginning, say you don’t think far enough beyond the IT infrastructure, you end up in limbo: caught between the dream of what IoT could do for your business and the reality of today’s ROI. That spot is called proof-of-concept (POC) purgatory.
  3. IoT Security still a big concern - The 2019 annual report of SonicWall Caoture Labs threat researchers analyzing data from over 200,000 malicious events indicated that 217.5 percent increase in IoT attacks in 2018.
  4. There are several obstacles companies face both in calculating and realizing ROI from IoT. Very few companies can quantify the current, pre-IoT costs. The instinct is often to stop after calculating the cost impact on the layer of operations immediately adjacent to the potential IoT project.  For example, when quantifying the baseline cost of reactive (versus predictive or prescriptive) maintenance, too many companies would only include down time for unexpected outages, but may not consider reduced life of the machine, maintenance overtime, lost sales due to long lead times, supply chain volatility risk for spare parts, and the list goes on.
  5. Privacy, And No, That’s Not the Same as Security. The Big Corporations don’t expect to make a big profit on the devices themselves. the Big Money in IoT is in Big Data. And enterprises and consumers do not want to expose everything sensors are learning about your company or you.
  6. No Killer Application – I suggest to read my article “Worth it waste your time searching the Killer IoT Application?"
  7. No Interoperable Technology ecosystems - We have a plethora of IoT vendors, both large and small, jumping into the fray and trying to establish a foothold, in hopes of either creating their own ecosystem (for the startups) or extending their existing one (for the behemoths).
  8. Digital Fatigue – It is not enough for us to try to explain IoT, that now more technologies such as Artificial Intelligence, Blockchain, 5G, AR / VR are joining the party and of course companies say enough.

You have the last word

We can go on forever looking for reasons to believe or not believe in IoT but we cannot continue to deny the evidence that the millions of connected devices already out there and the millions that will soon be waiting for us to exploit their full potential.

I still believe. But you have the last word.

Thanks in advance for your Likes and Shares

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A new wave of technologies, such as the Internet of Things (IoT), blockchain and artificial intelligence (AI), is transforming cities into smart cities. Many of these cities are building innovation labs and zones as part of their new civic landscape. Smart city innovation labs are vital components of the smart city ecosystem (Figure One). They provide an organized structure for cities, communities, experts, and vendors to come together to create solutions. Successful solutions piloted in smart city innovation labs are then scaled and deployed into a city’s operations and infrastructure.

Figure One. Strategy of Things Smart City Ecosystem Framework.

 
Many municipalities are considering and planning smart city innovation labs today. Over the past year, we helped to create, launch and operationalize San Mateo County’s Smart Region innovation lab (SMC Labs). From this experience, we share ten best practices for civic innovation leaders and smart city planners.
 
 
Ten Smart City Innovation Lab Best Practices
 

Develop a well defined innovation sandbox. Every smart city innovation lab has an unique mission. That mission is specific to its community, capabilities, priorities, and surrounding ecosystem. However, it is easy to get distracted and work on the “next shiny object”, vanity projects and “me too” innovation pilots. These projects don’t add value, but take resources and focus away from the problems the lab was created to address.

Build innovation discipline and focus by defining a “sandbox” from the start and updating it annually. The innovation sandbox defines clearly what types of projects are in-scope and which ones are not. The criteria includes alignment with city or department priorities, problem set type, problem owner(s) or sponsors, budget availability, cost, resource requirements, and organizational jurisdiction.

 

Create procurement policies and processes for innovation projects. Innovation pilots fall outside the “sandbox” municipal procurement processes and policies operate in. These pilots may work with start-ups with limited operating history, use immature and evolving technology, or bought in non-traditional ways (“as a service”, loans, etc.). This mismatch leads to higher risks, extra work and long sourcing times. Due to this, many vendors choose not to work with cities.

Effective smart city innovation labs are agile and responsive. They employ new procurement policies and practices designed specifically for the unique needs of innovation projects. This includes simplified processes and compliance requirements, new risk management approaches, faster payment cycles and onboarding models.

 

Build a well defined plan for every innovation project. Many innovation pilots are “successful” during the pilot phase, but fail during the scaling phase. This is because the pilots were not fully thought out at the start. Some test a specific technology or solution, and not the approaches. Others test the wrong things (or not enough of the right things). Some are tested in conditions that are not truly reflective of the environment it will be deployed into. Still others don’t test extensively enough, or over a sufficient range of conditions.

Successful projects in smart city innovation labs involve extensive planning, cross-department collaboration, and a comprehensive review process throughout its lifecycle. They have well defined problem statements. They define a targeted and measurable outcome, a detailed set of test requirements and specific success criteria. While innovation projects contain uncertainty, minimize project execution uncertainties with “tried and true” project management plans and processes.

 

Continuously drive broad support for the lab. A successful civic innovation lab thrives on active support, collaboration and engagement from stakeholders across the civic ecosystem. However, many city departments and agencies operate in silos. Launching and having an innovation lab doesn’t mean that everyone knows about it, actively funnel projects to it, or support and engage with it.

Successful smart city innovation labs proactively drive awareness, interest and support from city leaders, agencies, and the community. This includes success stories, progress updates, technology briefings and demonstrations, project solicitations, and trainings. They engage with city and agency leaders regularly, host lab open houses and community tours. They conduct press and social media awareness campaigns. Regardless of the “who, how and what” of the outreach, the key is to do it regularly internally and externally.

 

Measure the things that matter - outcomes. There are many metrics that an innovation lab can be measured on. These range from the number of projects completed, organizations engaged, number of partnerships, investments and expenses, and so on. Ultimately, the only innovation lab metric that truly matters is to be able to answer the following question - “what real world difference has the lab made that justifies its continuing existence and funding?”.

All innovation lab projects focus on solving the problem at hand. It must quantify the impact of any solutions created. For example, many cities are monitoring air quality. A people counting sensor, mounted alongside an air quality sensor, quantifies the number of people impacted. Any corrective measures developed as a result of this project can now point to a quantifiable outcome.

 

Build an innovation partner ecosystem. A smart city innovation lab cannot address the city’s innovation needs by itself. A city is a complex ecosystem comprising multiple and diverse domains. Technologies are emerging and evolving rapidly. New digital skills, from software programming to data science, are required to build and operate the new smart city.

Successful smart city innovation labs complement their internal capabilities and resources by building an ecosystem of strategic and specialist partners and solutions providers, and subject matter experts. These partners are identified ahead of time, onboarded and then brought in on an as-needed basis to support projects and activities as needed. This model requires the lab to build strong partnership competence, processes, policies and the appropriate contract vehicles. In addition, the lab must continuously scan the innovation ecosystem, identify and recruit new partners ahead of the need.

 

Test approaches, not vendors or solutions. Real world city problems are complex. There is no magic “one size fits all” solution. For example, smart parking systems use sensor based and camera based approaches. In some cases, both approaches work equally well. In other cases, one or the other will work better. A common innovation mistake is to only test one approach or fall in love with a specific vendor solution and draw a generalized conclusion.

Effective innovation lab projects focus on testing various approaches (not vendors) in order to solve problems effectively. Given the rapid pace of technology evolution, take the time to identify, test and characterize the various solution approaches instead.

 

Employ a multi-connectivity smart city strategy. There are many options for smart city connectivity. These include, but not limited to cellular 3G/4G, Wi-Fi, LoRaWAN, SigFox, NB-IoT and Bluetooth, and so on. Use cases and solutions are now emerging to support these options. However, some smart city technologies in the marketplace work on one, while others work on more. There is no “one size fits all” connectivity method that works everywhere, every time, with everything.

To be effective, smart city innovation labs need to support several of these options. The reality is that there is not enough information to know which options work best for what applications, and when. What works in one city or region, may not work in another. Pilot projects test a possible solution, as well as the connectivity approach to that solution.

 

Make small innovation investments and spread them around. Open an innovation lab and a long line of solutions vendors will show up. Everyone has a potential solution that will solve a particular problem. Some of these solutions may even work. Unfortunately, there is not enough budget to look at every solution and solve every problem.

Focus on making smaller, but more investments around several areas. Overinvesting in one vendor or one approach, in a market where technologies are immature and still evolving, is not wise. Invest enough to confirm the pilot outcomes. A more detailed evaluation of the various solutions and vendors should be made when the pilot moves out of the innovation lab and into a formal procurement and RFP phase.

 

Simplify administrative and non-innovation workloads. While innovation pilot projects are challenging, interesting and even fun, administering and managing the projects are not. These unavoidable tasks range include managing inbound requests, proposals and ongoing projects. These tasks increasingly consume time and resources away from the core innovation activities.

Effective smart city innovation labs get ahead of this by organizing, simplifying and automating administrative activities right from the start. For example, SMC Labs reviews inbound proposals once a week and organizes follow up calls and meetings on a specific day once every two weeks. In addition, the lab uses a tracking and pilot management tool (Urban Leap) to track innovation projects. Administrative and management activities are unavoidable. However, advanced planning and tools help reduce the burden to keep the lab's focus on innovation.

 

Benson Chan is an innovation catalyst at Strategy of Things, helping cities become smarter and more responsive through its innovation laboratory, research and intelligence, consulting and acceleration (execution) services. He has over 25 years of scaling innovative businesses and bringing innovations to market for Fortune 500 and start-up companies. Benson shares his deep experiences in strategy, business development, marketing, product management, engineering and operations management to help IoTCentral readers address strategic and practical IoT issues.

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