A crisis can sometimes act as an accelerant. The SARS outbreak of 2003 is often given credit for the rise of e-commerce giants such as Alibaba and JD.com. Starbucks swiveled during the global financial crisis of 2008−2009 to digital operating models that enabled them to rise and dramatically increase shareholder value. The coronavirus Armageddon is no different. In some industries, it is leading to an automation boom.
While the pandemic is having a harsh influence on companies at scale, mature ones are taking a pause and rethinking their approach. The global shock is acting as a moment of truth. According to a Deloitte study, before COVID-19, investment in artificial intelligence (AI) was already on the rise, going from $12 billion in 2017 to projected $60 billion in 2021. The trend only has gotten accelerated. COVID-19 is heralding significant investments in Intelligent Automation at an accelerated pace.
Investment is rising for robots that can help with the delivery of anything from medicines to the grocery. Government agencies like FEMA are engaged in how drone deliveries could assist during this emergency. In retail, there is an accelerated investment and installation of kiosk ordering systems. It’s an obvious move in the era of social distancing. Similar to essential checkout functions that automation can support.
As we look at COVID-19 shaping the new reality, let’s see how investment opportunities across Intelligent Automation can support business stability across the supply chain and logistics.
Intelligent Automation in Logistics
While eCommerce was a welcome indulgence in the past, it has become crucial in our new reality. As spending time at home increases, eCommerce logistics comes under the spotlight—comprehensive automated material handling solutions for eCommerce warehouses.
Intelligent Automation helps demand prediction for Inventory Management:
The most significant example is Amazon. In multiple aspects of operations at Amazon, Intelligent Automation methods such as time series prediction and reinforcement learning systems are beneficial. User demand, supplier backorders, warehouse optimization, stock levels are all guided by either machine learning or more sophisticated artificial intelligence systems.
Time series is an aspect of machine learning where, in extension to the observation datasets, an added dimension of time. The additional variable of time is both a constraint and a structure that provides a source of other information.
With the human check and balances in place, reinforcement learning is another branch of artificial intelligence based on a risk and reward system that helps with inventory management. For example, the system will punish the model every time an item runs out of stock. When done right, this model can yield phenomenal results.
Chatbots for Procurement
Chatbots can manage all of these through innovative automated datasets:
Conversing with the suppliers and accepting requests.
Set and follow a series of actions to the suppliers.
Placing purchase requests.
Answer doubts regarding the procurement of the suppliers
The COVID-19 pandemic has put unimaginable pressure on global supply chains, from medical supplies to household goods, as spikes in demand stress-test logistics foundations. There is an opportunity for crewless delivery vehicles to assist in addressing this demand and help to reduce the risk of COVID-19.
In the US, Nuro, a California-based builder of crewless autonomous delivery vehicles, was granted exemptions that were necessary to operate.
To speed up the back-office operations are vital for the logistics sector. Technologies like Robotic Process Automation help the companies to speed up the back-office processes. Data-related tasks that are repeatable can be automated to save time and money.
Using Intelligent Automation technologies, supply chain professionals can have actionable information at their fingertips. Thereby empowering them to respond quickly and focus their attention on higher-value activities like communicating with customers, suppliers, and other affected stakeholders rather than tracking information and status records.
Improve Customer-Service Experience
Intelligent Automation can improve the customer experience. For example, Amazon and DHL have a parcel agreement. Alexa answers questions about parcels, e.g., shipment details, whereabouts, and more. One can ask,” Alexa, where is my package?” and receive all the necessary information.
Track and Warehouse Analysis
Computer Vision (CV) is a field of knowledge that is responsible for developing various ways that help computers to decipher images and videos. For example, computer vision systems can automate the barcode reading process and, therefore, accelerate and simplify it. It can also monitor the warehouse boundary and track the employees, analyze the data, and prevent violation of the safety rules. Further, a computer vision system is also able to identify who is entering and leaving the warehouse area.
Logistics Route Optimization
The current situation calls for a faster shipping process. One can use artificial intelligence to decide on the best routes. Artificial intelligence (AI) can analyze the existing path, do the track route optimization. Therefore, a company can reach better results and make more significant contributions to society.
Shaping the Path Ahead
Diane Coyle, an economist, published a book called ‘The Weightless World’, where most economic activities took place in a digital form. Isn’t the COVID situation accelerating this vision? The world of bytes and atoms is fusing.
No one can predict the future with certainty. But the industry can be smarter by leveraging the power of Intelligent Automation technologies. Today the COVID-19 situation is creating multiple ripples within the global supply network. How can companies work towards creating a strategy that is capable of responding to such disruption?
Supply chain experts are facing the immediate challenges they are facing during this pandemic and finding ways to work through it. Intelligent Automation is helping organizations to manage better, predict, and limit the level of disruptions by building the capabilities necessary to respond to future events with both agility and confidence.