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Business Outcome Simulation: Seeing is Believing

March 19, 2020

Business Outcome Simulation

Putting Decisions into Action with "What-If" Analysis



Date: March 19, 2020

Time: 11am PST / 1pm CST / 2pm EST
Duration: 60 minute complimentary webinar

When it comes to making simple, everyday decisions, our brains will naturally analyze a multitude of scenarios and make rapid tradeoffs. This reflexive thought process—based upon our experiences and the information at hand—is usually enough to quickly guide us to the correct next action: “Here’s what I know, so here’s what I should do.”

Unfortunately, most business decisions aren’t that simple, especially in the field of supply chain management. And while nearly every mid- to large-sized company has invested in data and analytics, very few are sure of what they know, let alone what they should do.

Join our webinar to learn why Business Outcome Simulation (BOS) – the ability to compare and analyze multiple possible scenarios – is critical to putting business decisions into action. With the right decision technology, it’s possible to convert seemingly intractable business challenges into straightforward choices.

Supply Chain


What you’ll learn:

  • How to reduce decision complexity by enabling business and technical users to run what-if analyses and quickly compare multiple possible scenarios.
  • How to protect and maximize your current investments in data science and prescriptive analytics by ensuring applications are deployed.
  • Why this combination—empowered end-users and rapidly deployable business applications—are so critical to unlocking the fastest possible ROI.>

What you’ll see:

  • Real-world examples of BOS in action in a variety of applications, including:
  • Supply Chain Management: How to easily weigh the tradeoffs between enforcing business rules vs. total costs
  • Manufacturing: How to schedule production that accounts for competing objectives>
  • Transportation: How to optimize package delivery

Who will benefit:

  • Anyone responsible for supporting and making logistical decisions, including:
  • Line-of-business leaders and managers
  • OR developers
  • Data scientists
  • Business analysts / everyday users


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