Within many organizations, the procurement team is on the front line in terms of saving money. Never leaving money on the table is always a priority, and the idea is that predictive sourcing can achieve savings by negotiating better deals with suppliers. If cost savings can be achieved painlessly, that takes the pressure off the rest of the organization
This puts considerable pressure on procurement teams, especially someone like a category manager who is working on strategy and analyzing customer data.
There are different types of sourcing that attempt to tackle the challenge, each with a different approach. However, none has been proven to consistently deliver the results that satisfy everyone. That is, until predictive sourcing.
Can Predictive Sourcing Save You Money?
Predictive sourcing is a new approach to procurement. It did not exist until recently when a convergence of factors finally made it technically possible. The advent of centralized storage of procurement data combined with artificial intelligence (AI) and machine learning (ML) has been the key to unleashing this incredibly powerful tool.
Companies that switch to predictive sourcing save money, with results that are far more dramatic than any other type of sourcing. Here are three reasons why predictive sourcing ensures you never leave money on the table when working with suppliers.
Predictive AI Uses Statistical Models
Companies have years worth of historical supplier data to draw from. So much data that it’s virtually impossible for even teams of humans to analyze with any effectiveness. However, AI and ML have the power needed to process this data at lightning speeds.
This technology can also account for real-time updates for a wide range of variables that could impact everything from pricing to availability. The critical win from this deep data analysis is what artificial intelligence can do with it. AI “learns” from the data, detects patterns, and then makes use of that knowledge.
Predictive AI employs advanced statistical modeling that benefits the procurement process in many ways. It will catch any exceptions in supplier quotes, flagging them so a buyer or a category manager can take action. It can shortlist the most relevant suppliers for a bidding event, auto-populate demand data, forecast expected line-item pricing, and even recommend quotes to suppliers (which helps to set expectations around pricing acceptance).
Predictive AI is an incredibly powerful tool but what makes it even better is the fact that the AI also learns from every event. It just keeps getting smarter. Compared to bidding events that were run entirely by humans, predictive sourcing delivers better outcomes with substantial cost savings. It finds the money the procurement team had inadvertently been leaving on the table.
Predictive Sourcing Leads to the Best Business Outcome
Predictive sourcing is built on an archive of historical purchasing and supplier data. It’s that vast quantity of centrally accessible data that makes machine learning and predictive analysis possible. It’s what makes predictive sourcing the best of breed approach.
When companies make the transition from other types of sourcing to predictive sourcing, this shift also means the adoption of unified data. Going forward, all data relevant to the procurement process, including requisitions, logistics, demand, and buyers’ quote data, is also captured in the central data repository. So is all the supplier data such as performance statistics, compliance, and diversity.
In other words, all data relevant to procurement—historical, current, stakeholder, buyer, and supplier—is available to the AI.
With machine learning and artificial intelligence analyzing this massive trove of data, predictive sourcing can detect subtle patterns or trends that humans miss. It is then able to suggest the optimal path to achieving the best business outcome. This outcome accounts for important factors like maintaining supply chain diversity, meeting the quality requirements of stakeholders, and ensuring on-time delivery. But it also delivers the cost savings the organization is looking for procurement to deliver.
Predictive Pricing Including Intelligent First Offers Drive Savings and Quote Velocity
Artificial intelligence and machine learning can also be employed to enable predictive pricing. This is an incredibly beneficial capability. It saves time and eliminates human error by automating repetitive compliance tasks. It can predict demand for future sourcing activities, so the procurement team is one step ahead of business stakeholders. It can even forecast the quoted pricing on a bid for every supplier.
Predictive pricing is a crucial element of predictive sourcing. For example, utilizing Arkestro can bring cost savings of two times to five times the level of less advanced types of sourcing. In addition, predictive pricing significantly cuts down the amount of time required for a bid process. It can deliver quote velocity that’s 10 to 15 times faster.
See For Yourself How Predictive Sourcing Will Save Money
You’ve read about the power of predictive sourcing. Its ability to ensure your procurement team never leaves money on the table is an eye-opener. Now it’s time to see firsthand just how dramatic the savings will be. Visit Arkestro for a demo of predictive pricing in action to see how your team can predict, procure and win!