In recent years, the reliance on machine learning tools has become the craze among business communities. It is no secret that machine learning is set to become one of the most remarkable disruptive forces in the upcoming years that will affect nearly all industries. We frequently tend to speak about the potential for machine learning in the future tense, but the fact is that it is revolutionizing lots of business processes today.
Almost daily, we hear of new ways machine learning is transforming business digitally, but where does this leave supply chain and procurement?
Although procurement is not recognized for being the leader in implementing new technologies, this time it is different. In the past decades, efforts made to digitize procurement and supply chain processes have permitted many frontline entrepreneurs to implement machine learning solutions today and not in the distant future.
However, the vital thing to know is that if your procurement or supply chain organization is all set for digital transformation, it is ready for machine learning and AI solutions. Here are five substantial ways to get started.
Extend the Life life cycle with the Internet of Things and Machine Learning
Companies can make use of IoT sensors to collect usage data on essential supply chain assets, including warehouse equipment, transportation equipment, and other machinery. The data on its own is worthless, but combined with the power of ML algorithms, an entirely new world is opened up in terms of analyzing this used data and deriving insights about equipment efficiency and the fundamental factors that significantly affect performance. Using this information, you can extend the life cycle of your supply chain assets and get more from what you have.
Operational Procurement with Chatbots
Through the augmentation and automation of Chabot capabilities, companies can reform procurement-related tasks. As for repeated tasks, chatbots could be used to place purchasing requests, speak to suppliers during unimportant conversations, and set and send actions to suppliers regarding compliance and governance materials. Companies can also use chatbots to research and answer internal questions related to supplier or procurement functionalities. Moreover, AI-based tools could be effectively utilized for receiving or filing payments and order requests.
Machine Learning for Supply Chain Planning
Supply chain planning is the most critical activity in the supply chain management strategy. Having intelligent tools for developing solid plans is a fundamental need in today’s business world. Machine learning, applied within supply chain management, could help with predicting supply, inventory, and demand. If used properly through supply chain management tools, machine learning could transform the optimization and agility of supply chain decision-making.
By using machine learning technology, supply chain or procurement management professionals would be creating the best scenarios based on smart algorithms. This type of ability could balance demand and supply while significantly optimizing the delivery of goods. Moreover, it does not need much human analysis.
Warehouse Management with Machine Learning
If you take a close look at the domain of the supply chain process, you will see that its success is highly dependent on the correct warehouse management. Machine learning makes it easy for the SCM to store and manage warehouses in proper ways using self-improving algorithms. These algorithms are capable enough to find the flaws efficiently and quickly, which is relatively much more efficient than manual intervention by an assessor. Moreover, ML also makes it possible to find out the patterns in the procurement and supply chain by analyzing the warehouse data, which can significantly affect the success of the chain.
Shipping and Logistics with Autonomous Vehicles
In recent years, intelligence in shipping and logistics has become a main focus within SCM. More accurate and faster shipping minimizes transport expenses and lead times, adds several elements of environmentally friendly operations, reduces labor costs, and expands the gap between competitors. If autonomous vehicles were developed to their potential, the impact on logistics optimization would be immeasurable.
Conclusion
These days, procurement teams are reasonably stressed to do more, not just in terms of more savings but also improved insights, new sources of value, and new ways to drive even more efficiency. Digital evolution and transformation using machine learning tools in supply chain and procurement could be a perfect way to take on a limited share of the burden.
However, it is also essential to know that it is impossible to only implement innovations in the system of the company. It is essential to utilize these technologies properly by skilled and capable personnel, which is vital to getting the intended result.
