Artificial Intelligence (AI) in procurement is transforming the profession. It is automating tasks and improving efficiency and allowing organizations to rely on their data on decision-making moments.
In a broad sense, AI manage data coming from difference sources and extract valuable information from it. Those data may be from online catalogues, supplier management software (SRM), contracts, management software (ERP) and others.
Doing that data analysis, AI can help procurement at every stage of the process, from identifying suppliers to contract implementation.
Uses of Artificial Intelligence in Procurement
As established, AI can directly impact business by improving the decision-making process by giving insights from data analysis. That will help identify new possibilities and increase profit.
Also, it will improve operations throughout the entire business. Automating manual tasks can free employee time to focus on more strategic points.
Capturing data will also result in a better relationship with suppliers and optimized delivery routes and inventory management. But how to apply AI?
For instance, you can make:
- Spend Classification: classify spend in categories and subcategories.
- Vendor Matching: connect supplier data and purchase orders to vendors.
- Anomaly Detection: detect unexpected changes and problems in procurement process.
Cognitive Procurement
Cognitive procurement is basically using AI techniques to copy human intelligence and behavior. You can use them to automate data mining, recognition of patterns and self-improvement.
The base of cognitive procurement is cognitive computing, which represents any software that seeks to copy human intelligence and decision-making. It is a model of the human brain and response to tasks.
Then, the cognitive computing analyzs trough large amounts of structured and unstructured data. The idea is that the algorithm can recognize patterns and extract information in the same way a human would do.
This process also allows a cognitive sourcing, for example, using chatbots and algorithms to assist the sourcing process.
Implement Artificial Intelligence in Procurement
Adjusting the procurement process to use Artificial Intelligence is not easy. You need to have a strategy and proceed step by step when implementing the algorithms and defining the functionality.
Machine learning professionals have gathered a list of rules when implementing AI in operations, we’ll go through them.
Select a small task
Start by analyzing your procurement process and identifying tasks that can be automated and optimized. A good way to do that is look for simple functions that are spending a lot of employee time.
Artificial Intelligence will be a good fit for process that already exists, so, adapting the process to the technology will result in value for the operation and a better process.
Capture a lot of data
The higher the amount of data you must analyze, the more trustworthy your process will be. But not only assuring the quantity of data, is important to have updated and good quality data.
So, before starting the artificial intelligence implementation, capture as much data as you can. That way will be easy to train the model and get to the expected result as soon as possible.
AI algorithms can interpret historical data and give new insights.
Define direct tasks for Artificial Intelligence in Procurement
Start by giving your model tasks that aren’t much complex. The clearer the information and instruction you feed your model, the better results you will get.
Always rely on human input
Although artificial intelligence can make your process more efficient and accurate. Always considered human input on process and operations. That can be from the information extracted by the data or even more intuitive points.
In Sum
Artificial Intelligence in procurement is software’s that can resolve tasks, making it automated and liberating time from employees to focus on more strategic points.
It change the process and fix problems the team didn’t perceive. But the process to implement it must be thought and carefully executed.
