These 4 Technologies Will Change the Procurement Process
As logistics and procurement continue to evolve, new technologies will rise to smooth processes.
Perhaps the most integrated and robust form of tech in procurement departments today, according to experts consulted for this report, is machine learning, a form of mathematical modeling often used to build artificial intelligence (AI) applications. Users might not even know what they are interacting with it. Machine learning is a big tent of capabilities and touches each of the technologies that follow on this list.
Natural Language Processing
Natural language processing is another form of AI that can read text and decipher meaning. The procurement process is full of text-heavy documents, agreements and conditions. Reviewing supplier contracts quickly is a key task needed to get goods moving, and language processing software can reduce this time by flagging suspect clauses.
Robotic Process Automation
Robotic process automation (RPA) takes the insight machine learning can provide and turns it into action. While machine learning observes procurement professionals’ behavior and gleans the right way for processes or documents to play out, RPA follows pre-programmed “if/then” instructions. It’s a more formulaic and less fluid technology, but that rigidity doesn’t make it less valuable. […] RPA can make one event or finished task automatically trigger another. If the machine learning algorithm spots a problem with a contract, RPA can send it to legal for analysis, without the need for humans to send emails.
Big Data Analysis
Big data analysis, another application of AI and machine learning in many cases, can help procurement officers see into the future — at least small slices of it.
How will a hurricane in Texas change energy availability, and what are the alternatives? How will climate change shift soy production? How will a supplier’s plant relocation affect the buyer’s supply chain risk? How can a facility network protect against supplier risk? Big data analysis can take massive amounts of data from disparate sources and turn it into actionable insights based on historical outcomes in the context of hypothetical scenarios.
These new technologies have yet to see wide adoption, but logistic companies have already begun integrating them into their processes. It’s uncertain what the future holds, but one thing is certain: new technologies will play a role.
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