- Spend classifications
Spend classification is the process of grouping related spending data into categories using a given approach. This process is important in the preparation of data to spend analyses. The process of classifying data starts with gathering ERP data from contracts, purchase orders, and internal and external data and putting related items together. Spend classification is a tedious and repetitive process which may strain an organization in terms of human resources if done manually. However, with the help of machine learning, it is possible to gather data from different sources and classify it faster and accurately. The procurement staff can be left to do other useful things.
- Analyzing stock in transit
Companies that send and receive products must follow the status of materials and products in transit in near real-time. This will help the address emerging problems such as delays and other issues before they can occur. Predictive analytics give them exactly that. It allows them to ensure orders are delivered in time and at the right state.
- Automated sourcing
Through an increment of supply assignment sourcing, procurement departments can reduce the need for interacting manually while securing materials at the best price, faster and in high quality. With machine learning, the system automatically creates a bidding event when an internal source of supply is exhausted. It will act like a human purchaser, sending the bidding invitation to a specific list of suppliers.
- Making purchase recommendations
Machine learning can be helpful in making quick purchasing decisions. It helps create systems that act like search engines where customers can search products. With these search engine-lie abilities, the system can be refined to show a list of suppliers that meet specific criteria. A recommendation system can be built to support quick and accurate purchase decisions. A recommendation system recommends the right supplier for a company to source products based on the prevailing market conditions.
- Matching Capabilities
Machine learning can help in capabilities matching. Since all buyers want their suppliers to fully meet their needs while delivering exceptional service, having the right systems in place to match capabilities of each supplier will be crucial for operations. However, it can be tough to determine the potential of suppliers based on the manual systems. Machine learning can scan the industry for new competencies and align them with business requirements. With this information, the abilities of the existing and new partnerships can be tested and understood.
- Tracking and monitoring efficiencies
Efficiencies of operations is what every company seeks to achieve. However, this cannot be possible with manual systems. Machine learning allows organizations to track and monitor the efficiency of every company within the supply chain and rate them based on their abilities and performance. With this information, procurements are made efficient and fast. Furthermore, having information of every organization ensures operations run at their peak in terms of standards.
Generally, as technology continues evolving, we should expect more value and increasing efficiency in machine learning. As it is evident today, procurement companies can no longer ignore machine learning. It is upon them to work harder to benefit themselves with it.
