Have you realized that if you have an incorrect ideal scene, your program will be wrong?
In using the Data Series, some evaluators tend to toss off the ideal scene as a sort of afterthought-possibly because it is part of the form of evals. To do so can be quite fatal to the success of the eval-and it can result in the wrong ideal scene!
So always work out the ideal scene with care. That is what you are trying to achieve with your eval.
We know that homework may be necessary for the data section. But have you ever thought that the ideal scene may also require homework?
I recall a ship's galley once that couldn't get itself unscrambled. So the cooks and stewards were sent over on a tour of a posh cruise liner. They were amazed at what a real ship's galley could look like. They had seen an ideal scene. Until then they didn't know why they were being harrassed by the officers. They got it.
If you can imagine Sitting Bull, the famous Indian war chief, trying to evaluate "Queen Victoria's last grand ball failed" as a situation, you would see that his eval was likely to be rejected. For he wouldn't have had a clue what the ball should have looked like. But, as Sitting Bull was a pretty smart Indian, if he had done his homework on the ideal scene of a Queen's grand ball, I am sure the eval would not only have passed but the next grand ball would have been a howling success!
So homework is often quite vital on the ideal scene.
Not only can a person establish what an ideal scene should be, he can also establish what it could be and that may be a long way ahead of old accepted ideal scenes.
It is possible (and often very necessary) to "evaluate backwards"; that is to say, to start with the ideal scene.
If you have something you want to bring about-some ideal scene you desireand simply shuffle off toward it, don't be surprised if you never get there or achieve it. The realities and conflicts of life have a habit of intervening. What they call the "vanishing illusions of youth" occur simply because youth, thirsting to be a movie star or a great lover or a fireman, seldom sits down and does a thorough eval first that finds the barriers that will permit a program that will work. If one sets up an ideal scene as an ambition-such as the org booming-it may just stay an ambition one remembers in his old age instead of a concrete occurrence unless one does a backwards eval on it.
One does one of these "backwards evals" without any situation in mind. In other words, one does not have to have a sit in order to start the eval. (And you are aware of course that most evals begin because a sit leaps up and has to be handled.) So, without a sit, one simply puts down the ideal scene one is hopeful of achieving. Then he finds the most glaring departure from the ideal scene. That is his sit. And he also may find as he works that he gets several sits and several versions of the principal ideal scene which in turn become THE ideal scene he had in mind in the first place.
There is a simple view of it: Just set the ideal scene, find the furthest departure from it, use that as the sit and then, gathering data and doing a regular eval, he will find Why that ideal scene hasn't occurred or won't occur, then he can realistically program it to handle and the ideal scene will occur if the program is done.
One can take the more complex view of it: One sets the ideal scene, finds the furthest departure from it, follows a data trail, discovers there is more than one sit and so has a multiple-sit eval, each one with a different version of the ideal scene but these ideal scenes adding up to his original concept of the ideal scene.
Let us take a simple example. The major purpose of a directive to a salesman is "Sell the ballpark." Now if we simply told him to do that, we would be relying on his charm and luck and while these might be quite good we are likely to get a failed salesman. A more sensible approach would be to convert that major purpose to the ideal scene of "The ballpark sold at a profit." Then find and take the widest departure from that ideal scene which possibly is "We have been trying to sell the ballpark for two years with no takers." Then we employ the standard steps of the Data Series and find the real Why, which could be "Nobody ever compiled a list of the people who buy ballparks or approached them." And we do a program based on the Why and ideal scene and then we can give the salesman that program and that major target and bang, we sell the ballpark at a profit. As it could have been any one of a thousand Whys we could have gotten a thousand different programs, all of which would probably have failed because no evaluation was done.
So do not send to find why missions fail or projects collapse. Just notice that one didn't take what was desired and make it into an ideal scene and evaluate it backwards.
To always need a catastrophic sit in order to evaluate is to ask for more and more sits to occur as it is sort of an outpoint-correct but by evaluation. Of course, when sits exist, it is vital to evaluate them. But realize also that when you don't see what you consider an ideal scene, you can simply set it and evaluate back from it as above.
And realize, too, that this is a great way to make dreams come true.