Olay Skin Advisor is a mobile app that relies on machine-learning algorithms to analyze skin care needs. The app performs a facial analysis from a consumer’s no-makeup selfie and recommends products based on personal data and best practices from skin care experts. The artificial intelligence (AI)-enabled app also collects buying behavior data directly from the consumer and uses that data to determine the demand for and recommend specific products.
Explore the latest: Gartner Top 8 Supply Chain Technology Trends for 2020
Similarly, FlavorPrint, an AI-based platform introduced by McCormick spinoff Vivanda, determines what is called a “flavor DNA” — a digital taste identifier that matches consumers to food items. Through this direct customer engagement, FlavorPrint is sensing demand by better understanding customer preference. Furthermore, it can make this information available to the extended supply chain — suppliers, food manufacturers, content publishers — for better demand response and creation.
Supply chain leaders must assess their company’s risk culture to determine their readiness to explore and adopt emerging offerings
These are examples of how AI, a top trend impacting supply chains in 2018, can significantly improve a supply chain’s ability to sense and shape demand.
With the emergence of disruptive supply chain technologies like AI, supply chain leaders must determine the implications of those trends to enable the future of supply chain and operations.
“Supply chain leaders must assess their company’s risk culture to determine their readiness to explore and adopt emerging offerings,” advises Christian Titze, research director at Gartner. “If in doubt, consider piloting small projects to determine whether the potential benefit of the technology trend is worth the risk and required investment in new skills, capabilities and services.”
Gartner has identified eight strategic technology trends for supply chain and how they can provide a competitive advantage.
AI carries great potential to revolutionize supply chain processes. The ability to apply AI to enhance, and even automate, decision making, reinvent business models and ecosystems, and remake the customer experience could make many other emerging technology trends redundant.
However, although current AI solutions can find patterns and predict future scenarios, they still lack decision-making abilities. Combining pattern capabilities with more advanced prescriptive capabilities will therefore be critical to widespread supply chain uptake, enabling users to dedicate their skills to higher-order use cases such as strategic network design or capacity planning.
Advanced analytics enable companies to proactively take advantage of future opportunities and mitigate future adverse events. Prescriptive analytics can improve decision making in functional areas like supply chain planning, sourcing, and logistics and transportation, and can be deployed to improve end-to-end supply chain performance. Processes that previously relied on human judgment can be powered with predictive and prescriptive analytics that could have a significant impact on future demands for supply chain talent.
Internet of Things (IoT)
Adoption of the IoT is growing in select supply chain domains, but rarely as part of a complete end-to-end supply chain process. One exception is the air and defense industry, where airplanes have thousands of sensors and data is leveraged in the extended supply chain.
Other potentially impactful supply chain use cases are in preventative maintenance, sourcing, manufacturing, logistics, demand management and services. These include improved asset utilization, higher uptime through remote monitoring and maintenance, improved customer service by better understanding customer behavior and needs, and proactively responding to and shaping customer demand.
Current supply chain use cases for intelligent things — such as autonomous mobile robots and autonomous vehicles — are mainly targeted at defined scenarios and controlled environments, such as in warehouses. Intelligent things will make their initial business impact across a wide spectrum of asset-centric, product-centric and service-centric industries. As a result, the ability for organizations to assist, replace or redeploy their human workers in more value-adding activities will potentially create high, even transformational, business benefits.
Conversational systems — most recognizably implemented today in virtual personal assistants (VPAs) and chatbots — are taking interaction to the next level with the addition of conversational commerce. Not only can they handle discovery questions and offer solutions without any human agent involvement, conversational systems can enable transactions, handle payments, ensure delivery and provide customer service.
Robotic process automation
Robotic process automation (RPA) allows supply chain leaders to cut costs, eliminate keying errors, speed up processes and link applications. For example, an organization may want to work with structured data to automate an existing manual task or process with minimal process re-engineering or to avoid major system integration projects or specific new major application deployments.
Immersive technologies such as virtual reality (VR) and augmented reality (AR) allow supply chain businesses to enhance employee and customer digital experiences. Gartner estimates VR will reach mainstream adoption in the next two to five years, with AR going mainstream in the next five to 10 years, but these technologies are already in use in a variety of industries. These include enhanced repair and maintenance capabilities in manufacturing, logistics and warehousing and better purchasing choices for customers leveraging product visualization or store layout and planning.
Certain highly decentralized supply chain management functions such as smart contracts or traceability and authentication are prime candidates for blockchain. Multiple business use cases are yet to be proven, but some early pilot projects have emerged that are experimenting with the potential of blockchain for supply chain.
For example, blockchain is being used to track the movement of diamonds from mining to retail stores by developing a digital record that includes the unique attributes, including color, carat and certificate number that can be inscribed by laser into the stone.