Win-win

Who wants to lose? Nobody - that’s why a win-win resolution is so important. The same applies to the contradicting goals in the service chain. On one hand, every customer is important and we must make sure to handle as much requests as possible. On the other hand – we must not break the cost effectiveness of our operation – handling requests in a costly manner would have serious consequences. So how do we find the “golden path” – how can we have a win-win situation so that both our cost and the customer satisfaction are met? In the clip below you can see Michael Scott’s way of finding a win-win-win resolution.
Some may say – find a compromise: don’t handle tasks that are costly (for example). But is a compromise as good as a win-win? Surely it isn’t. A compromise will not give a reasonable solution since it does not make any side ‘happy’. In a compromise, all sides of the equation lose face – the goal is not met as it should be. As opposed to a compromise, a win-win resolution finds the way to obtain both sides’ goals, without losing face.
So how is this done? There are several known ways of how to obtain such a situation. You can find a systematic way in here http://en.wikipedia.org/wiki/Evaporating_Cloud . But let’s go back to our service chain. How do we find a win-win solution to the problem of handling cost effectiveness as well as customer satisfaction? Come to think of it, there are much more goals within the service optimization – how can we find this “golden path”? This is what the Optimizer is for. The Optimizer does not look for compromise. Instead it follows all the objectives of the service, making sure that none lose face. Only by rechecking again and again that all of the objectives are satisfied, do we find this hidden path, this win-win situation.