“Slowly, at a pace measured in decades, we are shifting to technologies whose main character is that they can be combined and configured endlessly for fresh purposes,” said W. Brian Arthur, a renowned author and economist.
Today, digital transformation is influenced by four simultaneous technology shifts: cloud computing, big data processing, enterprise mobility, and the Internet of Things (IoT). Each technology has reached a certain level of maturity yet organizations still face challenges of upgrading to these solutions and delivering business value.
Among the four, IoT is one of the most apparent topics to tackle because it extends and complements the capabilities of other technologies including software-defined networking (SDN) that is becoming more evident across industries.
Connectivity is a fundamental building block of IoT. It links things together and integration makes them into a whole. With the growing IoT demand, this process does not come easy. Many organizations are facing difficulties with their IoT implementation and management, highlighting the importance of businesses to overcome the potential struggles that they may face along the way.
Full IoT value does not rely on just connecting a few devices together. Being a “system of systems,” IoT is made up of many different components and expertise. Hence, to revolutionize a business model and use cases, end-to-end systems integration and highly-coordinated initiatives must be designed.
Biggest IoT connectivity challenges
The way people live, communicate and do business has been touched, one way or another, by IoT. All around the world, billions of web-enabled devices are turning the world into a massive digital hub. Aiming for smarter homes, offices, vehicles, and other operations, IoT connectivity encounters various problems such as the following:
- Scalability — The ability of the underlying infrastructure to scale is necessary as more devices get connected. In 2021 alone, reports indicate that there will be 35.82 billion IoT devices installed worldwide. In line with this, IoT scaling also unleashes a tsunami of new forms of data as organizations add more IoT connectivity devices, such as sensors, gateways, routers, or cameras.
The scalability issue is multifold and encompasses other matters like cost, complexity, and bandwidth efficiency. McKinsey Digital reported that 127 devices hook up to the internet for the first time, every second. Thus, service providers, network operators, and other digital enablers must implement a connectivity solution to keep up with the maintenance and management load as the network grows.
- Compatibility — With IoT’s expansion, many different technologies compete to become the standard which causes difficulty upon IT integration. Other compatibility issues may also arise from diversified operating systems, non-unified cloud services, and a lack of standardized machine-to-machine (M2M) protocols.
Users must keep their devices updated and patched for continued compatibility. As an example, when an IoT device communicates with another device and both devices run on different software versions, performance issues can occur. With regards to this, synchronization and interoperability of data flow between different smart devices in an IoT platform are also difficult to achieve.
- Security — Can you imagine that an average IoT device gets attacked just five minutes after it goes online? This trend is only expected to grow as more devices connect to the internet. Symantec revealed that the majority of cyberattacks on IoT devices are also a result of network routers, with an average of 5,200 attacks per router on a monthly basis.
Apart from the scalability and compatibility challenges mentioned above, successful IoT deployment would also need to resolve traditional network security challenges. These include device identity, personal data protection, access control, distributed denial of service (DDoS) attack, authentication, and other confidentiality issues. End-to-end security in practice requires the ability to make changes quickly so that problems can be fixed before they are exploited.
Essential strategies to implement
Company investments in IoT can be up to $15 trillion in 2025. These include investments being done in healthcare, manufacturing, automotive, retail, telecommunications, finance, and cloud, among others.
Yet to ensure IoT success, it’s vital to understand the immediate needs of the connected infrastructure to map out all integral technical requirements. An IoT initiative might start small, but enterprises and solution providers must think big and prepare to scale sooner than later.
By and large, IoT connectivity has evolved from point-to-point communications into complex, multicarrier ecosystems. As a result, enterprises are demanding more from their IoT solution providers for sophisticated and up-to-date services.
Here are some IoT strategies to keep in mind during the planning and execution stages:
- Design and test solutions that are highly flexible and configurable are priority. Flexibility will demonstrate the device performance under actual operation modes. The solution should be simple, inexpensive, and able to be used in both R&D and manufacturing to minimize correlation issues across the different phases of development.
- IoT devices must undergo compliance testing which includes radio standards conformance and carrier acceptance tests, and regulatory compliance tests such as radio frequency (RF), electromagnetic compatibility (EMC), and specific absorption rate (SAR) tests. This will reduce risk of failures and guarantee that a device is up to the mark.
- Coexistence testing measures and assesses how a device will operate in a crowded, mixed-signal environment. With various IoT devices interacting with each other, it is important to assess the potential risk in maintaining wireless performance in the presence of unintended signals found in the same operating environment.
- Organizations must design and implement each layer of an IoT architecture (perception, transport, processing, application, business, and security) at-scale to handle large volumes of device and sensor data to be collected and analyzed, leading to informed operational and strategic decisions.
- More IoT use cases correlate with economic success, an analysis derived from a McKinsey research. Thus, greater widespread usage forces a cultural shift into the organization wherein companies must be capable to adapt to any technology gaps, particularly in talents and expertise. In this case, a “go big” approach may seem counterintuitive, and depending on the business’ capacity, opting for a “slowly-but-surely” integration may work for long-term.
- Increasing the potential value from IoT activities can be derived from accessing all sensor data. Currently, there are many publicly-hosted IoT platforms that provide data access, storage and analytics for applications — but vigilance is the key. Learn which data should exist in a public environment and which should remain private. Establishing a hybrid strategy can help continued relevance and competitive advantage by retaining data ownership.
- Commonly known as “digital twin,” this virtualized replication of the environment is suitable for testing or development activities in parallel to live production. A best practice to do is automating conformance and regression testings to confirm compatibility between the IoT platform and applications.
There’s no single path to IoT success. With the current pace of digital transformation globally, companies have their own strategies that are deemed to be applicable on their industry or scenario. Some companies focus on connecting existing products to be more attractive and beneficial to customers while others harness opportunities for operational improvements that increase efficiency and lower costs. Additionally, several companies put their bets on creating new products or remaking business models that may improve their line of work substantially.