The human brain likes simple straight lines. As a result, people tend to expect that relationships between variables and outcomes will be linear. Often this is the case: The amount of data an iPad will hold increases at the same rate as its storage capacity. But frequently relationships are not linear: The time savings from upgrading a broadband connection get smaller and smaller as download speed increases. Would it surprise you to know that upgrading a car from 10 MPG to 20 MPG saves more gas than upgrading from 20 MPG to 50 MPG? Because it does. As fuel efficiency increases, gas consumption falls sharply at first and then more gradually. This is just one of four nonlinear patterns the authors identify in their article. Nonlinear phenomena are all around in business: in the relationship between price, volume, and profits; between retention rate and customer lifetime value; between search rankings and sales. If you don't recognize when they're in play, you're likely to make poor decisions. But if you map out relationships in data visualizations, you can actually see whether they are nonlinear and how--and then make choices that maximize your desired outcome.

This case describes a method for valuing outcomes and appraising tradeoffs in a multiple-issue negotiation. Employing an illustrative example, this case details the step-by-step process of articulating, testing, and revising scores which may help negotiators clarify their own preferences and priorities.