ABSTRACT
All the chapters prior to this point serve to help us prepare for the main event, which is to present an understanding of the government’s problem or opportunity as defined by pain points and to present the best solution based on the government’s evaluation metrics. We have explored the ways to influence the emergence of the main event, approaches for preparing the solution concepts prior to the main event, and techniques for avoiding tragic outcomes during the main event. Once we have done all we can to prepare for the win, we must develop the solution with the highest probability of win given our competitive situation. No solution is a guaranteed win when a competitive RFP is released. A bad solution, however, can cause a loss even when one is the incumbent offeror, when the customer has shaped the RFP to favor one’s capabilities, and when one has all the knowledge of customer processes. Let us now study the art of creating solutions that meet or exceed our objective probabilities of win. If a competitive situation only allows for a 20 percent probability of winning, then our solutions development across multiple endeavors must reflect a 20 percent or greater probability of winning. If we have done our preparations correctly and have not lied to ourselves as in the scenarios presented, then our understanding of the P-Win should be fairly realistic as long as we keep it within the scale of 20, 40, 60, and 80 percent. It is better to be accurate in predicting P-Win over the course of many government RFP responses than to randomly hit major successes. This is because major successes that occur randomly make it hard for businesses to plan long-term growth.
