According to a Consumer Technology Association (CTA) study, 83 million households and approximately 22 million homes today own more than one smart home product. The US home IoT market is projected to grow at a double-digit CAGR of 19.83% from 2020 to 2026.
IDC estimates that IoT spending in Europe will have reached $202 billion by 2022 and will continue to grow at double digits until 2025.
Despite the global impact of the COVID-19 pandemic, the IoT market is still growing this year, albeit at a slower pace than in previous years. IDC expects this growth to continue in 2021 across various sectors as operations, projects and employees begin to get back on track.
In 2021, most of the spending remains in the hardware category (modules and sensors), followed by the service category as a vital cost area for enterprises to assess, design, and deploy physical devices – the “things.” The category of IoT application software – the “Internet” – is projected to be the fastest-growing one in the next few years.
As per different estimates, COVID-19 and the associated uncertainty will continue to impact some industries over the next several years, creating mixed industry metrics during the transition to the next normal.
Another factor that is still holding back IoT mass adoption, especially within the SMB sector, is the myriad of myths surrounding the IoT space.
Through extensive conversations and discovery calls with our business prospects and existing customers, we at rinf.tech have identified five myths about IoT that unnecessarily bother business leaders.
In this article, we’re going to debunk these myths based on our firsthand experience with building and deploying high-performance Industry 4.0 solutions that help other businesses advance technologically, financially, and operationally.
Not only does IoT help companies collect and analyze data; it also helps turn it into useful insights for problem-solving and fast and informed decision making.
Consider, for example, how the speed of real-time data collection and analysis has dramatically accelerated the collection of information for epidemiologists and medical researchers dealing with Covid-19 treatments, testing methods, and vaccine options.
Although many companies are already collecting data, a lot of them still have no clue how to use it for robust business intelligence (BI).
Combined with data lakes and processing platforms, IoT automatically generates real-time analytics and alerts to enable users to identify trends and take actions much more effectively. Solutions and ideas can then be shared with other teams, locations, and applications, thereby increasing their value for the entire enterprise. When properly integrated, real-time data can be used in important innovations and strategies.
Deploying the Internet of Things intelligently requires a thorough understanding of the business and how it generates value. It also means knowing the company’s pain points so that it can invest in IoT where it matters the most and where it can realize its full value. Thus, where and how IoT is deployed is an important strategic decision that should be driven by the business strategy set by senior leadership.
One of the leading European retail companies has once turned to rinf.tech for help building an interactive real-time dashboard to solve the following internal issues:
As a result of their cooperation with us, the company got a custom IoT solution allowing them to map each client’s needs and solve their most sophisticated requests.
Using CCTV cameras and video analytics servers (including Facial Recognition, Queue Detector, People Counter, Activity Visualizer and Analytics system packages), our IoT engineering team delivered a custom tracking device and dashboard providing the following types of data:
This custom IoT-based dashboard allowed the company to see a 90% increase in customer insights, a 50% increase in the immediate response rate, and a 60% rise in the accuracy of customer patterns.
As such, the value that the whole business has gained from IoT development is significant.
While it’s true that a typical IoT development project requires skills in hardware, networking, security, software engineering and design, mobile application development, automation, data science, AI/ML/DL and Mixed Reality (XR), most of roles on the IoT team can be combined or developed from existing employee re-skilling or re-training.
To nail it even more, companies should take advantage of globalization and outsourcing, which provides access to the untapped pools of the IoT talent and allows for faster recruitment cycles and overall turnaround. Leveraing external R&D teams specialized in IoT/hardware/embedded development also helps lower down IoT dev budgets and optimize expenses.
Employee training must take place along the entire value chain. For instance, companies will need more cost engineers experienced with cost modeling tools to estimate equipment and logistics costs in procurement.
The ability to identify opportunities for improvement requires training and education. Organizations can train employees to think and act differently, become more involved in problem-solving and develop local solutions that can then be disseminated across the enterprise across technical platforms for maximum impact.
Given the breadth of new skills needed for teaching specific technologies and new ways of working, some companies are developing programs in partnership with higher education institutions.
One of the main candidates for helping to secure IoT is quantum computing. However, the idea of converging IoT and quantum computing is not a new topic, it has been discussed and covered by various researchers, but nothing comes close to practical applications so far. Quantum computing is not yet ready, and it is still several years before it can be implemented on a commercial scale.
However, progressive software companies like rinf.tech ensure their software engineering talent’s future readiness by introducing an internal Quantum Computing course. It’ll be led by one of our senior engineers currently working on a Deutsche Bank project. Its key goal will be to increase our employee’s understanding of Quantum and how it’ll help secure future IoT solutions. We want to ensure they can easily “plugin” when quantum computing is ready to go mainstream.
Not only is it optional to be 100% ready, but this is also impractical and possibly even counterproductive. In fact, it is enough to be digital and flexible to hit the IoT developer journey.
In many cases, companies spend too much time planning. More importantly, getting started right away with a digital transformation office. This central team oversees pilot projects and guides the organization through a seamless and fast learning process. Like an executive “engine,” the transformation office helps a company grow over time with proven methodologies, best practices, and a holistic leadership vision for transformation.
Agile working methods enable rapid development, refinement, and continual improvement. Agile enables companies to move in sprints and iterate quickly to quickly learn from their failures and create an even better product faster.
What’s important is that whenever the company considers outsourcing its IoT project development, it should make sure its potential technology partner is 100% digital-ready.
Some business leaders believe old, legacy facilities are an obstacle to digital transformation and that outdated equipment needs to be replaced. Certainly, new equipment will be required. But equating the IoT with completely new from-scratch sites capable of fully automated production is a big exaggeration. Much of the industrial IoT value lies in improving existing facilities: connecting and optimizing existing infrastructure and expanding it by choosing new equipment on an ongoing basis.
By adding sensors, applications, and connectivity to existing equipment, companies can collect data and transform it into business intelligence that is available to employees right at their fingertips. The Internet of Things and new technologies can help employees manage results at all value chain stages.
Let’s take a connected car as an analogy. Before the advent of sensors, drivers had little understanding of what was happening under the hood in real-time. Today, dozens of sensors in the digital cockpit collect a wealth of data about the engine, transmission, suspension and other locations and transmit it to the interactive real-time dashboards.
Drivers can now anticipate and fix problems on-site to optimize their vehicle performance with the lowest possible margin of error.
Contrary to popular belief, implementing an IoT strategy and taking advantage of Industry 4.0 does not require a significant upfront investment. Companies can facilitate smooth transformation by starting small and letting their business cases drive technology adoption (rather than the other way around).
Other keys to ensuring the long-term success of an IoT strategy include using an open and scalable cloud platform for analytics and adopting a security-by-default approach to digital infrastructure deployment.
For example, smaller manufacturers do not always have the resources for large initial capital investments in large equipment. Engaging with an OEM that provides industrial capabilities as a service is changing that – opening up new business opportunities.
Most of the custom IoT projects we do at rinf.tech start small and scale as the customer begins to benefit from the business with their experimental solution. As a strategic IoT technology partner, we do our best to lower each client’s project development costs.
We achieve this by:
A Beecham Research IoT User Survey found that 96% of executives involved in successful IoT projects rated the following three factors as important or very important to success with your projects:
It is also clear from Beecham’s research that close collaboration between an in-house team and experienced suppliers is at the heart of many successful projects.
In 49% of successful projects, the development team combined expert solution providers and internal IT resources. In contrast, among unsuccessful projects, 57% relied only on internal resources, and only 17% mixed an internal team with external experience.
This is confirmed by our own experience as a custom IoT software developer.
Many clients come to us with a failed or stalled project, often managed in-house. It is a common mistake to think that the communication part of a project will “just work”, and very little attention is paid to this element in planning and development. The project is written off as failed because data is not being collected and transferred properly. Devices are switched on and off from the network, information gaps appear, and an incomplete picture is obtained, which devalues the entire project.
The number one reason for these failures is poor initial project design and insufficient time, resources, and experience to plan a network with clear results. Not enough attention is paid to IoT connectivity or issues. The belief that all of this can be handled in-house using open-source software and standard connectivity is at the heart of many project failures.
Most IoT project managers elude how much the technical complexity increases as IoT deployments scale. This process is clearly not linear and goes to the point of quickly breaking through internal systems, stressing the support organization, degrading the customer experience, and ultimately hurting the brand. Even a project’s most precise business goals become irrelevant if data is not collected efficiently and reliably.
IoT projects can be complex and costly but not as expensive as mistakes. And that’s so true!