"We found Iasta offers the best solution set, combined with the highest value for our organization." -- Burlington Coat Factory
Basic & Advanced Decision OptimizationDecision Optimization is the key for your team to make more nuanced and educated award decisions after the strategic sourcing RFx and/or Auction events that you run. You’ve put in the time to identify a business need, suppliers, bid structure, etc. – greatly streamlined albeit by Iasta SmartSource, of course – so you want to make an award decision that accurately reflects your business needs.
What Decision Optimization does is layer different factors and constraint types so that you can build "real-world" award scenarios. Custom scenarios help you minimize risks by analyzing a wide range of factors associated with the selection of suppliers. Some risk scenarios could be low-cost country suppliers, new vs. incumbent suppliers, and high vs. low product quality issues. As you can see, you want to consider both price and non-price factors.
The award scenarios can be set up to allow you to evaluate the costs associated with doing business with a small or large base. With this information, you can optimize the correct number of suppliers that should provide you with goods and services.
Decision Optimization can act as a quick and dirty scenario analysis engine for a small team of procurement heroes, or a robust data comparison engine that factors in, among other things:
- Multiple price and non-price constraints (allocations, limits, exclusions, discounts, etc.)
- Multiple custom supplier attributes (incumbent, minority owned, etc.)
- Freight brackets
In-house Iasta experts built this application from the ground-up, not through acquisition. As a result, all features work well together and flow from one project phase through the next, meaning you can generate bids in an auction and gather non-price information in an RFx and use this information natively in the Optimization engine of Iasta SmartSource. Users never need to generate extra, cumbersome keystrokes in order to work with their project data.