New technologies, such as blockchain, artificial intelligence (AI) and machine learning, can potentially and significantly disrupt existing supply chain operating models, information technology research and advisory multinational Gartner VP analyst Christian Titze said on Tuesday.

Gartner identified various strategic supply chain technology trends that have broad industry impact, but have not been widely adopted. These technologies are, however, experiencing significant changes or are reaching critical tipping points in capability or maturity.

“Companies seek to exploit the benefits of greater levels of digitalisation. For example, blockchain technologies could be an answer to address problems across three areas including counterfeiting, visibility/traceability and efficiency,” Titze said.

Blockchain is aligned to potentially fulfil critical and long-standing challenges present across dynamic and complex global supply chains that traditionally have held centralised governance models.

Current capabilities offered by blockchain solutions for supply chain include a loose portfolio of technologies and processes that spans middleware, database, verification, security, analytics and contractual and identity management concepts.

“Although supply chain-related blockchain initiatives are nascent, with solutions in early stages of development, interest has accelerated significantly during the past year, making blockchain a top trend for supply chain leaders to watch in 2019,” he said.

Further, a digital supply chain twin is a digital representation of the relationships between all the relevant entities of an end-to-end supply chain — such as products, customers, markets, distribution centres/warehouses, plants, finance, attributes and weather – and creates end-to-end visibility by being synchronising with real-world supply chains.

“This enhances situational awareness and increases the quality and speed of decision making. Appropriate predictive and prescriptive analytics – including machine learning and AI – would be applied to the digital supply chain twin so that aligned (and to some degree, automatic) decisions could be made,” said Titze.

Further, the impact of advanced analytics on supply chain is significant. Advanced analytics are increasingly being deployed in real-time or near-real-time in areas such as dynamic pricing, product quality testing and dynamic replenishment.

“The availability of supply chain data – such as Internet of Things (IoT) data, dynamic sales data and weather patterns – provides the ability to extrapolate the current environment to better understand future scenarios and make profitable recommendations,” he explained.

AI, which is one of the technology trends, supports broader supply chain automation, which could be semiautomated, fully automated or a mix, depending on the circumstances, he noted.

“Through self-learning and natural language, AI solutions can help automate various supply chain processes such as demand forecasting, production planning or predictive maintenance. Along with automation comes augmented human decision-making.

“AI technologies in supply chains seek to emulate human performance and knowledge, such as improving order delivery and service levels by using AI capabilities to determine the routes to optimise deliveries, or optimising shipping replacement parts by applying AI algorithms and notifying users of a potential equipment failure prior to it occurring,” said Titze.

Similarly, IoT adoption is growing in certain supply chain domains, although rarely as part of a complete end-to-end supply chain process, and companies are assessing the business value of expanding beyond their current use of operational technology. Logistics groups already use sensors to track assets or containers.

“IoT could have a broad and profound impact on the supply chain in areas such as improved asset utilisation and higher uptime, improved customer service, improved end-to-end supply chain performance, or improved supply availability, supply chain visibility and reliability,” said Titze.

Meanwhile, the use of autonomous devices is also a growing trend, such as robots carrying out jobs in a coordinated fashion to create a seamless and connected process in manufacturing facilities or drones used for inventory-quality assurance through taking images with the drone’s camera to reduce time for inventory checks.

Robots, drones or autonomous vehicles enable new business scenarios and optimise existing ones. Supply chain leaders should evaluate the use of autonomous objects as substitutes and complements to the human workforce. Labour reductions seem the most likely drivers, but improvements in overall output and productivity will be the primary value, regardless of whether labour is reduced, said Titze.

Meanwhile, robotic process automation (RPA) tools reduce costs and keying errors and accelerate processes and link applications.

“RPA has proven to be effective in simple use cases, mainly where a third party in the supply chain will not provide an application programming interface or other means for automated data integration. However, the potential to achieve strong return on investment is entirely dependent on the applicability of RPA in each individual organisation,” he said.