Today, buyers cannot award suppliers based solely on simplistic metrics like overall price or delivery speed. Rather, stakeholders from across the business expect deals to account for factors like corporate best practices, vendor risk, and category compliance.
To better understand the challenges by today's sourcing managers, let's look at a hypothetical purchase decision being made by John.
John is a buyer at a reasonably large corporation and must balance a wide range of stakeholder requests and requirements with each purchase—conditions and constraints that the stakeholders want John to satisfy while awarding business to suppliers.
In this particular purchase, the CFO (Chief Financial Officer) asks that the price be not more than 10% of a benchmark, while the CPO (Chief Procurement Officer) wants the award to be de-risked across various geographies, and the supply chain officer does not want dependence upon only one or two vendors.
As John reviews hundreds of supplier bids, understanding how well each sourcing scenario complies with these varying constraints is a monumental task that simple sourcing platforms cannot handle.Watch demo in action
For example, if he wants to manage and analyze the scenarios in Excel, then not only is it extremely laborious, but Excel has limited abilities for doing constraint-based calculations. What John needs is a solution that can analyze bids against all conditions to recommend the best possible decision that satisfies the maximum possible conditions for him based on his inputs.
To aid buyers like John and empower sourcing organizations to make holistic and nimble sourcing decisions, Icertis introduces the "Scenario-Based Award Optimizer" to its Sourcing application built on top of the Icertis Contract Intelligence (ICI) platform.
While optimization tools have been around for some time, most of them are too complex for the end-users to apply to a wide range of sourcing events with complex cost breakdowns and various other business constraints required to be considered in an award decision.
Today's procurement professional expects an intuitive, easy-to-use solution with a robust optimization engine to help them maneuver through numerous complex business constraints and optimize the award recommendation with the push of a button.
Overview on Scenario Based Award Optimizerplay videoWatch demo in action
Robust Algorithms for Holistic Decisions
The Scenario-Based Award Optimizer's robust optimization algorithms empower procurement and sourcing professionals to analyze a large and complex set of supplier bids to receive a recommendation for the "optimal" award allocation meeting the business constraints.
In addition, ‘What If?' scenarios enable the sourcing team to rationalize the cost tradeoffs and make informed and balanced decisions.
Speed to Award Increases Process Efficiency
Enterprise-grade tools have been used to build the optimization engine which accelerates the computation process for complex, large-scale sourcing decisions.
Also, automating the process of arriving at award recommendations compresses the sourcing cycle time, and the risk of any manual error reduces significantly.
"The Scenario-Based Award Optimizer takes full advantage of the power of optimization complemented with game theory. Furthermore, built as an extension to the ICI Sourcing app, complimentary concurrent contracting provides the necessary flexibility and agility in the sourcing process."
– Sandeep Lalka, Associate Director, Product Management, Icertis