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AI can drive better supplier negotiations with faster outcomes

Today, most sourcing teams ask for quotes by emailing one spreadsheet to many suppliers and re-assembling the resulting chaos in a pivot table. Some technologies have helped digitize the process, but the basic information included remains the same. Companies ask for quotes, and suppliers send what they believe to be their best initial offer.

Many CPOs understand the benefits of adding technology to their procurement process. According to Deloitte’s 2019 Global CPO Survey, “increasingly intelligent e-procurement systems are able to direct stakeholders to preferred sources of supply or even use predictive analytics to warn users of the (un)likelihood of a purchase request being approved.”

In reality, there has been little advancement with regard to incorporating true artificial intelligence (AI) into procurement software. Most sourcing tools are still applied to traditional functions like auto-filling spreadsheet fields or tabulating responses to identify the bid winner.

CPOs understand this. Current technologies are not meeting their needs as they work to automate core work functions, including contract management, requisitioning/ordering, spend/supply analysis and planning, and supplier management, the Deloitte survey found. About 71% of participants voiced dissatisfaction with supplier management technology, and 58% are dissatisfied with their sourcing solutions.

To find out more about how technology is improving supplier negotiations, we talked to Edmund Zagorin, the CEO of Bid Ops, a Spend Matters Future 5 award-winning company that offers a cloud-based sourcing enablement tool. Bid Ops describes its platform as the first AI solution for automating sourcing negotiations using adaptive target pricing, or “Willingness to Discount” formula, as they call it.


Spend Matters: What do you see as a major factor that hinders supplier negotiations?

Edmund Zagorin: Today, a major gap in nearly every sourcing professional’s understanding of their negotiations is a comprehensive picture of individual vendor behavior and engagement. Many digital platforms simply ask suppliers to provide a quote, which ends up being the supplier’s best guess, a sales rep holding a wet finger up to see which way the wind is blowing.

For negotiations to change, both parties need to have better communication. The only way to get a better relationship is to communicate to your negotiation counterpart what you want. If you ask suppliers what they dislike about negotiations today, it all comes down to poorly managed expectations, a process fraught with ambiguity, complexity, delays, paperwork and the potential for conflict. If both parties can become more communicative and clearer about what they need, then suppliers will have lower costs associated with managing the negotiation process and therefore can offer sourcing teams better value.

Bid Ops has integrated AI in a different way, using it to individualize the process for each bidding supplier. How does that work?

When suppliers work within Bid Ops, they establish a “persona” that helps buyers understand their appetite for risk (and their willingness to deal). Some suppliers don’t feel comfortable offering big compromises while others are much more flexible, provided that the business opportunity is sufficiently large. In truth, most suppliers fall somewhere in the middle on the spectrum of 100% rigid to 100% flexible. Regardless, Bid Ops can analyze these behavior patterns and offer customized responses — feedback —  that moves each individual closer to potentially winning a deal.

Ultimately, suppliers want to get a sense of where they stand in the process. Bid Ops’ suggestions are generated using three factors — the overall persona of the negotiation itself, the persona of the individual supplier rep, and the supplier’s relative incumbency (meaning the prior relationship of the supplier with the buyer for that particular contract). New suppliers are suggested for a significantly lower opening bid to give them a fighting chance of overcoming the traditional bias toward existing suppliers. This by itself results in more optionality and more competitive awarding practices that drive savings.

Using Bid Ops, buyers are able to state their goals and intentions for the negotiation upfront or rely on a set of best-practice negotiation templates. This allows the whole contract negotiation cycle to run much faster. By gaining insight into how a specific supplier negotiates, the buyer is actually able to offer that supplier more deals, better terms and faster deal-closes.

Suppliers that win in Bid Ops also get recommended to other buyers from the same procuring entity. From a game-theory point of view, traditional supplier negotiations are Prisoner’s Dilemmas: If a supplier doesn’t take the deal, they stand to lose everything in the same way that a criminal suspect that refuses a plea bargain could be found responsible for the entire crime (if the other prisoner agrees to a plea bargain first). However, strategic relationships provide a solution to this game theory problem: A Prisoner’s Dilemma where both parties know that the dilemma will be repeated creates an alliance of mutual trust to form, since the long-term benefits of cooperation outweigh the short-term benefits of competition. By creating additional benefits for winning suppliers, Bid Ops allows buyers to effectively align incentives around long-term partnerships with quantifiable benefits to both sides.

However, in order for this to work, both parties must cooperate to reduce the costs of negotiations. Email-based supplier negotiations are incredibly expensive to execute and manage, and in many businesses, they consume a tremendous amount of time, attention, labor and resources. If they don’t produce results, then they’re simply not really worth doing in the first place. To be successful, negotiations run on Bid Ops must have a lower cost to serve for the same or better results. Thus far, our users have demonstrated the impressive business case for autonomous negotiations, negotiations in which the buyer uses AI to go first and name a price.

Spend Matters: You’ve taken a different approach with regard to pricing and category management, basically jettisoning categories as a benchmark for setting price. What led you to this decision? And what has replaced it in your system? 

In procurement, we have this mental model of category management (usually based on our company’s org structure), so all of the data tends to revolve around the idea of a category benchmark. Bid Ops’ historical dataset, which crosses a number of different direct materials categories, generates rich insights based on the similarities between dollar value of winning a contract and the competitiveness of the negotiations. We’ve found negotiations are more similar to each other across categories than within the same category. Intuitively, it makes sense that a $100,000 negotiation for any product is more like another $100,000 negotiation because the incentives are more similar for the supplier’s sales team (who are the ones making the decisions). In contrast, a $100,000 negotiation for paint has almost no similarity to a $100 million negotiation for paint. The stakes are completely different. That is the fundamental root of our forecasting model.

Our anchor pricing comes from a proprietary type of analysis called “Willingness to Discount,” which estimates each vendor’s perceived value of winning the contract. This starts the process, allowing buyers to review and adjust anchor prices when necessary. If the buyer or sourcing manager is a category expert, they may have insights that will cause them to adjust the price generated by our AI, but for the most part they will review and approve before telling Bid Ops to execute an AI negotiation. Then the price recommendations are pushed to the suppliers.

To build on something you mentioned, another major difference is the collection of data from losing bids. Why collect this? 

Today, due to the spreadsheets-in-email-chains problem (which is really what people mean when they talk about “data silos”), most companies are throwing away quote data from vendors that did not win the business. Bid Ops helps sourcing teams collect that information because it helps buyers understand what drives an award decision and generates a useful snapshot of the market. Sometimes, buyers need to be able to reach out to other vendors to re-award the contract or increase volume by adding an additional supplier. But overall, they understand their categories better by retaining and re-analyzing quotes other than the supplier who won the contract.

Surprisingly, we have seen that, most of the time, the winning supplier hasn’t offered the lowest price. It’s true that the incumbent supplier wins most RFQs, because there’s a huge cost in changing suppliers, and so, all things being equal, business buyers will prefer the status quo. But companies go through the process to get leverage to lower the bid cost. And, the ways that losing suppliers respond can teach companies about the market in ways that winning suppliers can’t. Quotes from these non-winning suppliers contain fundamental business intelligence that can drive business value for leadership teams well beyond the realm of strategic sourcing.

Does the Bid Ops platform provide options for companies with any amount of spend?

If you are using our enterprise platform and really want the biggest bang for your buck, you’ll get the best savings results by running AI negotiations for contracts worth between $5 million and $100 million and including a lot of different supplier relationships.

Smaller companies can use the platform to manage RFPs in more efficient ways by forward scheduling RFQs and making use of efficient templates. That is why we launched Bid Ops Free.

Bid Ops Free allows anyone who wants to be able to use our platform to request better quotes faster. But this capability has nothing to do with AI — it’s just a better experience than email-and-spreadsheets so that businesses can experience the magic of sourcing enablement.