Companies in all industries are continuously looking for new ways to automate tasks with the help of emerging technologies. Automating manual tasks lowers the production cost while improving the quality of the product. Enterprises are designing a robust automation framework to satisfy the new demands of businesses, resulting in reduced process costs and outcome continuity across industries. Here is where Hyperautomation is disrupting the supply chain industry and creating a positive impact.
Hyperautomation is ranked by Gartner in the top 8 leading developments in supply chain technology trends for 2020 and beyond. According to a new forecast from Gartner, Inc. The worldwide market for technology that enables hyperautomation will reach $596.6 billion in 2022, this is up from $481.6 billion in 2020.
Hyperautomation is enabling a digital workforce that leverages different applications, analyzes, takes action on unstructured data, explores new possibilities for improvement of processes, and makes crucial decisions.
Companies are on the lookout for a promising outcome that creates a new business opportunity for businesses to increase their ROI and reduce their TCO (total cost of ownership). Renowned companies like Amazon rely on technologies such as AI (artificial intelligence) and Cognitive Analytics tools to increase their growth over the last few years, and this is something that every company should take note of.
Transforming the Supply Chain automation with Hyperautomation
Hyperautomation is the sole embodiment of modern technology. With the increase in supply chain connectivity, the majority of operations undergoing digitalization, and managing massive volumes of data, the adoption of Hyperautomation in supply chains is proving to be a game-changer.
Use of Robotic Process Automation (RPA) & AI in Supply Chain
Hyperautomation is the gateway to larger networks in Supply Chain Management that requires no human intervention.
Businesses today have shifted their focus to the digital revolution for addressing current Supply Chain challenges. This digital transformation and innovation are centered around reimagining the operational processes, customer experience, and business operating models.
Structured as well as unstructured data collected from the connected devices is analyzed to explore new possibilities for improving the supply chain processes, and this is possible with the combination of data, AI and RPA.
RPA software consists of software bots that generate automated notifications for order placement, and also keep a tab on the inventory, by sending out a reminder if any product is going out of stock. Precious manual time and efforts spent in ordering or monitoring the resources are saved with the help of bots, reducing the service costs and improving productivity by a significant margin.
Eg: Bots in inventory management send out alerts when any product goes below the demand level or there is a shortage of stocks. Bots perform processes like reading email notifications / alerts in certain formats, pulling the data from emails and updating the ERP system, notifying the concerned person once the information is updated, etc.
With the world moving at such a fast pace, the organizations are facing the challenge of keeping up with the latest demand with customers continuously changing their minds and requirements; hence, there is a need for self-sensing and learning algorithms. For any given company, it is difficult to perform demand forecasting of a product manually by analyzing its historic data with qualitative and quantitative methods.
Cognitive Data Analytics
Data plays a major role in the digitization of Supply Chain networks. By analyzing structured and unstructured data, AI (Artificial Intelligence) & ML (Machine Learning) are continuously updating the systems dynamically by learning and analyzing these data. This saves the time taken on creating and implementing new test cases for the management of Supply Chain operations to become more productive.
Supply Chain departments generate a tsunami of data from their stakeholders and partners, including images and videos too, and with the rapidly moving market, it is not easy to read and make the forecast of such data. Technologies like RPA and predictive analysis, help predict the forecast with great ability, and provides various other benefits like-
- Helping organizations predict the demand forecast to stock up the inventory.
- Predicting the health of their units like computing platforms, software, internet connections, etc.
- Predicting the customer choices, eg: If the demand for a certain coffee flavor toffee is trending, it notifies the company to increase the production of that product.
- Gaining new insights with real-time data and simplifying the decision-making process while improving customer satisfaction.
By adopting Hyperautomation, companies are eliminating daily manual repetitive tasks, which is also helping save the environment by eliminating paperwork. Hyperautomation is helping supply chain organizations to mitigate the risk of human intervention with the tools while saving a good amount of time and money.
Hyperautomation is not replacing the workforce, but rather empowering them by providing them with the opportunity to focus on valuable tasks that require more cognitive work and decision-making.
How can Neebal help?
Choosing the right Hyperautomation strategy and implementation partner is crucial to successful adoption. Your entire technology architecture should have seamless integrations supporting multiple features. Here’s where Neebal can help you.
Neebal has over a decade’s experience in successful Hyperautomation implementations while mitigating risks across multiple domains and industry verticals. Contact us today to jump-start your Hyperautomation journey the right way!
Also read- Benefits of introducing RPA in finance and banking in 2022