IoT technologies driving supply chain growth, says Frost & Sullivan
August 6, 2019
Technologies such as artificial intelligence, machine learning, blockchain and robotics will drive multiple growth opportunities in the supply chain, according to market watcher Frost & Sullivan.
The company’s latest analysis reveals that end-to-end visibility, predictive analysis, transparency and real-time insights are some of the benefits driving the adoption and implementation of IoT systems within the supply chain management (SCM) market. The trend towards IoT-enabled SCM is creating a convergence of disparate sets of providers and the rise of a new ecosystem that will have far-reaching benefits for users.
"Current supply chains will be reinvented as IoT-enabled systems allow unprecedented end-to-end visibility, remote tracking and control," said Deepali Sathe, senior industry analyst at Frost & Sullivan. "The increase in automation will significantly improve accuracy of predictions and speed of execution."
One of the biggest impacts of technology adoption on SCM has been the introduction of new business models. As data siloes diminish, users can focus on the benefits that can be achieved as a result of improved end-to-end visibility, ability to control devices remotely and automated processes.
"Predictive analytics based on artificial intelligence, machine learning and big data analytics will reduce errors and take the guesswork out of planning, forecasting and execution," said Adrian Drozd, research director at Frost & Sullivan. "Technologies such as blockchain can create better and faster processes and prevent fraud, while robotics will enhance automation and precision for greater accuracy."
Vendors offering IoT-enabled products and services can tap into growth opportunities by:
- Focussing on increasing demand for IoT-enabled, multi-function robots and cobots;
- Investing in the development of sensors and tags required for connected devices;
- Offering strong, multi-layered cyber security to tackle potential threats;
- Harnessing data using AI and machine learning technologies to enable the likes of chatbots or smart home speakers; and
- Meeting customer preference for XaaS business models such as platforms and sensors.