If you ask any business leader about one thing they wish they changed in their business strategy prior to COVID-19 shuttering the world, it would be “to have been better prepared”. In a more globalized world, disruptions to the supply chain have more far-reaching consequences and require that businesses, large and small, adopt a proactive stance in preparation for the next disaster.
This necessary agility can be achieved through the conscientious adoption of new technologies such as artificial intelligence and machine learning within the supply chain.
Two of the industries that were significantly overwhelmed by the changes caused by the pandemic were grocery and logistics. Early on, panicked shoppers overwhelmed shelves and supply chains by purchasing goods in excess.
Concurrently, the shift to remote work and an explosion in online shopping, combined with lockdowns and trading pauses resulted in overwhelmed logistical pipelines. The primitive nature of many of these enterprise systems and the chilling effect of the pandemic resulted in the need for widespread digital transformation in order to respond to these challenges effectively.
For example, managing waste and optimizing quality control is one of the longstanding pain points in the fresh produce industry – an issue Clarifruit addresses. Using artificial intelligence and machine learning, Clarifruit’s mobile app, available on SAP Store, automates the quality control (QC) process for production.
When an inspector scans a piece of fruit into the database, it’s analyzed for several qualities, predetermined by the customer, and this analysis is then made available for QC directors via the cloud. This continuous oversight allows companies to identify negative trends more quickly and effectively within their supply chain, helping them to better address loss and waste – two pressing issues in the grocery industry
By automating the QC process, customers of the platform we’re able to increase inspector productivity by 300%. The automation and machine learning process is also developing a database of fruit ripeness assessment, with the goal of setting global standards that will further allow for the refinement of the lengthy farm to the supermarket to consumer process. Deep analytics empowers companies with tons of descriptive data, allowing them to refine QC resources and develop solutions to address disturbances efficiently and effectively.
Agile solutions that use artificial intelligence to anticipate or proactively respond to changes in the supply chain allow enterprises to make data-driven decisions in real time. Same day or one-day delivery are no longer options for enterprises – customers now expect shortened delivery windows as a rule.
With the massive increase in online shopping over the last 18+ months, it’s become more important than ever for enterprises to optimize last-mile delivery services – a term describing when an item is sent from a local warehouse or fulfillment center for final delivery to the customer – to reduce wait times for customers.
Technologies that refine and expedite a product’s journey from manufacturer to retailer to customer’s door are increasingly prevalent. Wise Systems’ dynamic, AI powered, SAP-integrated dispatch and routing systems, available in the SAP Store, uses predictive analytics, artificial intelligence, and data to empower enterprises to make real time adjustments to their supply chain where and when it counts.
As more organizations seek to refine the last-mile experience, which is expected to grow by over $50B USD in the next four years, there is a growing need for smarter technology to exceed the needs of a more competitive market.
A fairly disjointed industry, currently relying heavily on third-party players of varying levels of technological savviness, the logistics industry is ripe for digital transformation as a whole. Prior to adopting Wise Systems technology, Anheuser Busch’s last-mile delivery management was largely a pen-and-paper affair.
When the brewery sought to optimize their regional delivery network of 850 trucks, they used Wise’s fully automated optimization engine, which delivers a host of routing and dispatching capabilities to improve the delivery experience and outcomes for all stakeholders.
By analyzing tracking data in real time, the system determined optimal routes for last-mile delivery to avoid delays like traffic, accidents, road closures and other obstacles. By using the Wise app, Anheuser Busch saw an 80% reduction in late deliveries, in addition to a 6% YoY decrease in fuel costs.
While these pain points aren’t necessarily new to the supply chain, global shifts and challenges within the last two years are continuing to exacerbate these problems – and make them bigger. Changing behaviors and norms require digital transformation that conscientiously utilizes technologies like machine learning, artificial intelligence, virtual reality, and predictive analytics to increase the agility and dynamism of an organization. Using these solutions to their full potential will be the key to sustained growth in the future. These tools, combined with business strategies that encourage proactive, data-driven pivots in times of change, can redefine the entire supply chain.
