What if your smartwatch could tell when you’re getting agitated while driving and signal your car radio to play music that soothes you? What if your vacuum cleaner could identify certain spots in your house prone to harboring particles you’re allergic to and clean them more frequently? What if employees in an office could be alerted when they’re within two meters of each other so they can maintain social distancing?
IoT has already made the last example possible – via wristbands. The system is already in use. And there is a growing market for it.
Customers drive business. Therefore, all your business transformation initiatives should focus on improving the customer experience in some way, directly or indirectly. The digital transformation of a company is complete – or at least poised to succeed – when their products are mapped to every user individually.
This mapping is nothing but a digital “link” between a company and its customers, which can be facilitated and enhanced with IoT whenever the company has access to a device that the customer owns, even if it hasn’t been sold by them. IoT of course starts with connectivity, but connected devices by themselves don’t deliver value – either to the customer nor to the business.
It is the digitisation of the product and the use of data and analytics to improve the utility of user interactions which actually transform the very business model of the company. This fits in with Gartner’s definition of digital transformation: the process of exploiting digital technologies and supporting capabilities to create a robust new digital business model
While Fortune 500 companies are expected to and already have digitised many of their product lines, the real digital transformation is being led by small businesses, which are more likely to “create a robust new digital business model” in the process. Let’s examine where IoT comes in and how it contributes to ongoing digital transformation in organisations that already have an agile approach in place, automated their core processes, adopted analytics for all business functions, and made strategic investments in innovation and IT.
IoT facilitates data collection and analytics
Businesses make money by selling products and services – even if they’re virtual, informational, or digital. IoT works on a physical device that assists the transaction between a company and its customer by collecting and using data. It is up to the company to convert this data, generated from the physical world, into useful information that sustains and grows its business.
This physical device has a sensor that collects real-time data – such as the amount of items within or the temperature of the system – from its surroundings or components. The IoT
software then converts this data into a digital payload, packs it with encryption and network protocols, and sends it along to the company’s database, which resides in its data center or in a public or private cloud.
Once you have this data, you can format it and feed it into your analytics software or AI-based business process models to gain critical insights into various business functions as well as make forecasts.
There are two technical components that that play crucial roles in the journey of data from metrics collected by the sensor to insights that drive decision and strategy. Together, they make IoT-driven digital transformation possible.
The IoT platform is a software-defined solution that drives the whole process from connectivity to data processing to integration with analytics tools. It performs some crucial functions:
- Delivering local compute power to edge devices
- Analysing data from the IoT sensor embedded in the physical device
- Connecting to a public cloud, private cloud, or on-premises data centre
- Deploying analytics functions where the data is generated
All this makes the IoT platform a “middleware” between remote user devices and the apps that use their data – merging the physical layer, the application layer, and everything in between.
The IoT platform acts like an OS driver, managing both hardware and application interaction. What’s more, it has to provision and automate all connected devices, be compatible with multiple network and cloud protocols, manage network security and encryption, have data processing capabilities, and also enable new or native application development.
No wonder IoT platforms are incredibly complex to manage and monitor. The amount of data generated makes it near-impossible to analyse in real time. This is why a critical feature of IoT platforms is observability – how easily the admin can understand, control, and troubleshoot a complex system, with the ability to drill down to a specific device, application, region, or user role.
Traditionally, all data processing occurred centrally in data centers owned and operated by enterprises. Consumer and Industrial IoT devices are now placed in driverless cars, drones, utility meters, CCTV cameras, heart monitors, oil rigs, and so on.
These devices generate a massive amount of data that is invaluable it is created and stale moments after. Milliseconds matter when the police are trying to catch a fleeing criminal, someone is having a cardiac arrest, or a pedestrian walks into a self-driving car’s way.
In such situations, moving critical data over a long distance from the IoT device to a public cloud or a data center and back incurs a delay that defeats the purpose of data collection itself. They require analytics, AI, and processing to happen locally or as close to the device as possible, so that the data becomes actionable in real-time.
This is leading to a huge shift in computing where data processing is being moved out of data centers and public clouds to distributed, standalone, self-contained mini data centres at remote locations, closer to clusters of IoT devices in a given region.
But this doesn’t mean the cloud is passé when it comes to IoT-driven digital transformation. For data that delivers insights over time, it pays to unite edge data with applications in the cloud. It helps you aggregate and correlate IoT data and workflows across multiple sites, benchmark and compare them against one another, and know which ones are productive or profitable.
Digital transformation 2.0
The Internet of Things is evolving into a more broadly defined Internet of Everything (IoE) in the new hyper-connected reality of hyperconverged edge and public cloud environments. Advances in all of these technologies are enabling the second wave of digital transformations in both the B2B and B2C sectors, leading organisations to scale out their IoT deployments.
Many small and large companies are going from pilot IoT projects and proof of concepts to bigger opportunities driven by data, machine learning, and predictive analytics. You can emulate them and bridge the OT/IT divide between the operational and IT side of your company. Ultimately, this will help you fast track innovation and bring you closer to your customers.
Source : iottechnews.com