Companies are leveraging artificial intelligence to drive up supply chain resilience, as issues such as materials shortages and natural disasters threaten business stability.
Enterprises across industries will increasingly use AI for tasks such as answering complex procurement questions, which will in turn improve supply chain efficiency.
“Supply relationship management will enter an entirely new phase when so much more intelligence is available to buyer and supplier both,” says Paul Blake, senior director of product marketing at GEP.
One major benefit of AI in supply chain management is that, in the source-to-pay process, companies can gather immediate intuitive intelligence. AI helps to turn past activities and successes into actionable strategies for future projects at a stroke. For example, AI can quickly answer: what is the best strategy for optimizing savings in a rising market for a particular category?
“When in the thick of running a complex RFP, we might ask what combinations of suppliers give the best savings and lowest risk,” says Blake. “What AI will do is radically reduce the effort required to reach the correct information.”
What’s more, when dealing with vast repositories of documents such as contracts, AI allows users to request specific actions, such as which contracts are affected by a change in law or by new regulations.
By automating repetitive tasks, difficult problems get more attention, too. Automation elevates risk management, opportunity identification and effective relationship management.
The quest for the ‘holy grail’
These are “the holy grail of procurement, but so often are always on the horizon as savings tracking, invoice management, and order handling take up so much more of the bandwidth,” says Blake. “Automation takes care of the drudgery so people can tackle these harder problems.”
All of this enables enterprises to be proactive, rather than reactive.
“It’s huge that we face the possibility that we will be able to ask ‘what if,’ before it happens, and ‘what now,’ when it happens and for the answers to be rapid and actionable,” adds Blake.
One scenario in which AI can help is with a category or sourcing manager at a data center who needs to run a request for proposal with over a dozen suppliers, some they’ve worked with before.
Using AI, the manager easily has at their fingertips information on:
· How many suppliers or bids there are,
· Which responded to the last RFP,
· And how this response compares to their last RFP.
Triggered by data, AI can also generate an email to suppliers who have yet to bid.
“So, in that case, that mundane admin job is taken over by the AI bot,” says Rakhi Mullick, VP of digital transformation at GEP.
In a second example, a sourcing manager wants to know which suppliers are registered for a particular category they’re interested in. The manager asks AI who can provide them with this particular service, and they immediately receive a list of those suppliers.
Then, AI can narrow down the list by both location and by which supplier ranks highest in terms of supplier performance score.
“So, within a matter of a few seconds, you go from having no insight into knowing who you should be dealing with for a particular requirement to getting straight to the most important company,” Blake says.
Finally, AI helps with contracts, too. A manager working with contracts can seamlessly see which ones are expiring in the next quarter or next 90 days, then rank contracts in terms of total value. It’s easy to quickly get a thorough summary of a given contract as well.
Given the multiple challenges today’s supply chains face, driving efficiencies with technology must be a top priority.GEP’s products have AI built in and they help companies maximize their supply chain efficiency. Learn more here.
Artificial Intelligence, Machine Learning