Automated Line Item Suggested Pricing Leads to Success

AI and machine learning is taking procurement by storm and once time consuming tasks are becoming streamlined through technology and data-driven processes. With so much potential to leverage, 79% of corporate strategists report that AI and analytics will be critical to business success over the next couple of years. Strategists anticipate that the adoption of such technologies could potentially automate 50% of strategic planning and execution activities, compared to today’s 15%.

Line item suggested pricing is one such opportunity for optimization through algorithms and machine learning. What is suggested pricing, how does automating it work, and how can an advanced machine learning model even further improve buying outcomes for procurement teams?

What Is Suggested Pricing?

Suggested pricing shows participating suppliers a pre-calculated line item best price at the start of a sourcing event. Communicating upfront competitive pricing expectations to suppliers will most often result in quicker negotiations and overall cost savings, making suggested pricing a valuable tool.

However, in most cases the suggested price used is simply the price paid the last time the line item was purchased. While easy, this method does not leverage all possible savings to help arrive at an actual best price. Procurement teams can expend greater resources gathering additional data and manually calculating a more precise suggested price, but that time investment prior to the event can offset any savings realized later through quicker negotiations and price assessments.

Suggested pricing is one of the many perfect targets for optimization with AI, game theory, and machine learning. Arkestro uses these advanced models along with instant analysis of historical trends and the parameters from the sourcing event to automatically calculate very precise suggested prices. When you consider applying highly targeted suggested prices to all line items on all your sourcing events, it is easy to recognize that a huge opportunity exists to save resources at scale.

Automated Suggested Pricing: How It Works

Arkestro uses a combination of a machine learning model and an algorithm based on game theory to discover the best suggested price for your line items.

The Machine learning (ML) model analyzes an organization’s purchasing data for patterns around event timing, duration, number of line items, quantities, and overall relative prices within an event to predict the mean final discount for each line item. This price is compared to the current baseline price, and the price most likely to achieve the greatest savings is used in the algorithm to calculate the suggested price.

Next, the algorithm instantly applies game theory to your baseline price, assessing the number and response history of the suppliers you have added to the event as well as the initial baseline of each line item. Discounts are applied to the baseline price depending on the likelihood and extent of competitive feedback to the participating suppliers and how those suppliers have historically responded.

Automated Suggested Pricing: Competitive Outcomes

Applying suggested pricing to your procurement function has immediate and clear benefits. The best of these is to obtain more competitive outcomes. By algorithmically driving pricing up front based on ML-analyzed data and specific rules, you can achieve the best price possible, even if only one supplier participates.

This competitive advantage comes from Arkestro’s application of game theory in addition to its cutting-edge technologies. In game theory, the mere fact of competition (even if it’s only perceived) and setting an initial price can influence the action of your suppliers. However, it ends up being a win-win for both parties — suppliers can win quotes where they might not have been considered previously (because you can run more sourcing events through the platform), and procurement can shorten negotiation cycles as well as cut down on costs.

Another benefit of suggested pricing on a platform like Arkestro is that you can scale it quickly and easily across more line items. By running more and more events through the platform, you end up scaling your savings as well. Let’s dive into a few examples of how customers have done this on Arkestro’s platform.

Automated Suggested Pricing: Arkestro Success Stories

By applying suggested pricing to sourcing events and line items, Arkestro customers have seen impressive results in short amounts of time. Don’t take our word for it — here are several examples of suggested pricing that resulted in better procurement outcomes for our customers.

Chemical Company Saves $10,000 on First Quote

Dover Chemical Corporation’s first event using Arkestro’s platform was an annual RFQ on valves the company uses. After multiple rounds with a suggested price pulled from Arkestro insights, the procurement team saved $10,000.

“Because Arkestro does its thing in the background and suggests the pricing, oftentimes companies will accept our bidding price, which was lower than what it had been previously!” said Patti DeVault, a buyer at Dover Chemical.

To date, Dover Chemical has completed over 1,000 projects within the Arkestro platform with an average of 2 quotes per day and has 95% of its spend flowing through the system. Not only this, but Dover Chemical’s savings have continued to grow by 10% year after year.

Retail Organization Saves $1M on MRO (Maintenance, Repair, and Operations) Spend

After applying Arkestro, an organization in the tools and safety items industry realized $1.1 million in savings on $7.9 million in annual spend. With 100% of their suppliers participating in both rounds of suggested pricing, they were able to reduce their pricing in the second round based on feedback from the Arkestro system. This move resulted in an average of 7% reduction round-over-round and savings in all four categories they quoted on the platform.

To conclude, suggested pricing is a tried and effective technological advancement that procurement teams should explore when looking to apply emerging technologies to their procurement strategy. Arkestro’s suggested pricing model can help your team achieve more than they could on their own. Learn more about our platform here.