There are bad situations, good situations and no situations. A situation is something that applies to survival and if you evaluate the word "situation" against survival, you've got it. A good situation is a high level of survival; a bad situation is a threatened survival and a no situation is something that won't affect survival.

We've gone ahead of the whole show of intelligence with the Data Series.

Note: We are using intelligence as an example solely and only because it is the most inclusive system Man has developed for collection and evaluation of data.

We have greatly refined this system. Espionage and other intelligence activities and skills have no part in our application. We are using intelligence as an example of data usage systems, that is all.

You are out in an area of greater simplification and far more use. This doesn't necessarily make anyone an intelligence officer, but a general or a head of something or a general manager or an executive who does not know how to evaluate a situation will make nothing but mistakes. The mistakes of history are made by people who can not evaluate, by which we mean determine the situation-which even more simplified would be find out the situation. From this given body of data, from that indicator we can find a good situation, or a bad situation or a no situation. And this is what one is trying to determine. The more skilled one becomes in doing it, the less work it is. It is a matter of skill.

To give you an idea: If you tried to play every note of a concerto separately by having to look up each note in the chord and then strike it on the piano, you wouldn't have much of a tune, right? But the longer you did that, the more likely you were to begin to approximate some sort of something that sounds like music. But it would take a lot of practice.

Now you can get so all-fired-good at evaluation that you can take an isolated indicator and know immediately where it fits into because you know it fits into the plan of things and because you know it is or isn't part of an ideal scene. It's better than the existing scene or it is too far from an ideal scene. You can pick up an indicator in this way-and it sometimes probably looks magical to you how I will suddenly pick up an isolated instance and look down the line and we find a roaring hot situation at the other end of it.

Now that is done out of an economy of data. It is done because one has not the time to investigate or read all of the data which might exist on this particular subject being investigated. So one learns to do something that looks absolutely intuitive and when you're terrifically hot at this it is called "flair."

Prediction from data is an essential part of evaluation. "This datum is an outpoint-it shouldn't be, peculiar." Now it will predict more data.

You have to be so hot that you will notice something is an outpoint-it's a wild outpoint of some kind or another-accept its magnitude, size of datum, how important is this datum. The evaluation of importance is one of the more difficult things people have to do. They have a tendency to consider things a monotone importance. You have to train yourself out of that.

What do we get here then as a qualification for an evaluator? You have to know all the outpoints in sight. You have to know what outpoints are. But that's rather thinking backwards because you should know that something shouldn't be. And as soon as you get a "shouldn't be" you can do a prediction. And that leads you into an investigation-by viewing other data. In other words you find this terrific outpoint or these outpoints and you find out where they exist, it leads you into, very directly, the point that you should be investigating.

This is as close as the dictionary comes to the definition of evaluation: "to examine and judge concerning the worth, quality, significance, amount, degree or condition of." (The Third Webster's International Dictionary.) Now to edit that down, it's "to examine and judge the significance and condition of."

An evaluation: "the act or result of evaluating, judgement, appraisal, rating, interpretation." And an evaluator is "one that evaluates. An intelligence officer is supposed to be a professional evaluator." (The Third Webster's International Dictionary.)

This word is a technical word which isn't given in these dictionaries. It is an action which is basically an intelligence action.

The actual meaning which is supposed to be embraced in the word is "to examine the evidence in order to determine the situation" and that is the intelligence meaning and then it could have, further: "so as to formulate policy or planning related thereto. In other words 'What is the enemy going to do?’ So the general can say 'Therefore we should. . . .' "

Here is an example of what evaluation is, the type of thing expected of an evaluator.

I was looking at an org's graphs, all of a sudden I see a drift down of reserves and a level of bills. The bills are level, level, level-drift down of reserves, until all of a sudden it's about to cross and this was an org where we just changed the CO, so I say "Hey whoa! Wait a minute, wait a minute! This organization is spending more than its income obviously by the looks of this graph. So let's look into this just a bit further." I looked further and got more data and I found out that the org was running insolvent. The Data Bureau already had a report on this; I picked it up on another line. I just picked it up off graphs.

Further investigation found out that the new CO had taken over from the old CO and had inherited an extremely backlogged org-included backlogged bills. And the new CO had been sent in there on a set of Garrison Mission Orders-and they just contained standard COing actions when they should have been MOs designed to handle the insolvency scene-forcing the org to promote and make income; then making an announcement that no POs will be signed except promotion, wages and utilities; then get in the date-line paying and forcing Accounts to dig it up out of all their mouseholes and all those bills that have been in there for a year or two and the stuff they didn't file and get a date-line paying system in. Then you start surveying like mad to find out what the organization can sell and then you start delivering, beef up your delivery lines and so on.

It wasn't any surprise to me to learn that that graph was a false report, of course. But this is no explanation. It doesn't mean the situation doesn't exist but the graph is a false report. That is an outpoint all in itself. It's actually backed up by other data but you could have taken it this way: You could have seen the graph declining-that is reserves going down, bills staying the same and you find out it's a false report. At that moment, by Data Series, you charge in and investigate the heck out of it. Here's an indicator, then another indicator that's a false report.

Where did I count outpoints? I was counting them all the time. One is enough-a declining reserves graph and a holding debts graph-well that was enough. So the counting was "one," and as I looked a little further I got "two" and then as I looked a little further I got a "three" and a "four" and a "five" and a "six." We did a handling and more outpoints showed up. Right as you are handling the thing more and more outpoints show up so there is a point where you neglect any more outpoints, you can go on as a lifetime profession finding outpoints in one of these areas. It's enough. '

We have actually done something with the Data Series which has never before been done. Other data evaluation systems have to do with the reliability of the observer, which determines if the reported fact is a "proper datum." But all of their work is done on computers and those computers are built against logic systems developed by the Greeks. But it is data, data validity of, which monitors logic.

A black propaganda operation is almost totally concerned with feeding wrong data into the population and therefore the population cannot come to correct conclu­sions and their actions will be peculiar. There are experts in black propaganda and they're fully trained in it and they do it all the time.

Back of wrong data you will normally find an impure intent. So that somebody is giving you false reports is an evaluation in itself.

An evaluation first requires data. The absence of data you should have would give you an evaluation. We knew something was wrong with an area because all of a sudden somebody found out they weren't sending in their reports. The absence of data is an adequate evaluation that there is something wrong. And in one such case it actually took weeks to find out what was wrong.

If you find the outpoint, you're into evaluating a situation. You're just looking at data-you find an outpoint, you investigate that. You find more outpoints, you go along and say, "It's the thing that we're looking at now, what the heck. . . " because you're obviously traveling away from the ideal scene or you've found something that went much closer to the ideal scene or something that didn't change it. You then look it over and say, "It's this point," and at that moment you can figure out why this is occurring. "Now why is this occurring?" And that requires quite a bit of data. "Why is this occurring?" Therefore when you can say "Why," now you can handle.

What you want is the outpoint and an outpoint is a departure from the ideal scene. That tells you that there is an area to investigate and you can investigate it simply by going and finding more data and more outpoints and then as your data accumulates you can get why it's a departure. The accuracy of your Why then gives you the point which you will have to handle which is all very neat and there comes in your recommendation.

This is the trick on evaluation: You have to learn what is an outpoint, what is this outrageous thing and then that cones you down. Now you could find all kinds of little points.

Having handled the thing or having done something about it, don't be too surprised to now and then find a lot more data suddenly emerge. In fact it is almost usual now that you've started to handle something for more data to emerge. But you have to look it over. You have to say, "Well, have I handled it? Does this data confirm our Why or doesn't it confirm our Why?" And that's all you do with that data-it's confirmatory.

Sometimes you get data after the fact, after you've taken action. That is a review of your evaluation. When the data comes in after the fact, there's another step involved here.

You review the situation and all of a sudden you find out you were looking at a heck of a wrong Why. One of the first things that will tell you you operated on a wrong Why is that the stats went down-because it departed further from the ideal scene.

You get injustices and that sort of thing coming out of wrong evaluations, so this is one of the reasons why you watch an evaluation in your line of country-you watch an evaluation after the fact. Was it true? So there's a confirmatory step which isn't mentioned in the Data Series-"Was that the right Why?" The Data Series does mention it's whether or not the stat goes up. But it's worse than that: "Did you have the right Why?" or "Did you shoot down the wrong man?"

We have a considerable amount of technology which is administrative technology, which gives us an ideal scene, and with which we must be familiar in order to evaluate and handle. We would have to be as practiced in this as in the building of armament factories or running navies or building toy balloons or trying to get housing furnished to the great unhoused if that's what we were doing-you have to have some familiarity with the type of scene which you're handling.

If you're good at this you don't go on wasting your time and energy. You find the right Why, you set it up, you make sure that it does get set up-but there's nothing more you have to do with it and then that's that. Sometimes that takes quite a while but note that if you're immediately pressing down this Why all the rest of the way and you go on past the point where you corrected it-the thing is corrected-now you're handling a no-situation.

If you didn't have evaluation you would find yourself handling no-situations and neglecting tough situations and not taking advantage of good situations.

Occasionally you'll find a scene wherein a person's or area's PR is greater to him than his production-PR, personal PR, means more than production. And that is a characteristic of a suppressive. He'll fog the situation up with big PR about how good it is so it can't be handled.

You have to know when you don't have a Why. It is very, very important to know you don't have a Why.

The end product of your evaluation could be said to be "What do we do about this?" In other words, your recommendation could be said to be the end product. Actually that's a short circuit. As far as your investigation and your data analysis is concerned your first target, the Why, if skipped will defeat the end product of your evaluation. If that Why is found then you can handle.

A Why is just this: It is the reason there has been a departure or closer approach to or an exceeding of the ideal scene.

What will defeat you continuously is trying to find Whys in no-situations. You won't find a Why. If you can't find a Why readily then you can possibly suspect that you have a no-situation.

A Why, by essence, is something you can do something about. You have to have a recommended action on top of the Why.

The Why is something which departed from, the reason it departed from or the reason why it bettered the ideal scene or got closer to it. It is a Why you can use and which will bring you a better scene.

Therefore the definition of a Why is: It must be something which will permit you to bring about a better scene-not necessarily bring about the ideal scene.

You might actually have a better scene than the ideal scene. We've described the ideal scene as so and so and all of a sudden a Why suddenly emerges which actually makes the ideal scene look pale. Taking the ideal scene of a moderately affluent org-we might all of a sudden move into a situation where the ideal scene was quite something else and we found out "How come all of a sudden Keokuk has made 8 million dollars in the last 13 days?" How come? We don't have an ideal scene anymore.

We have a system of data handling which is superior to that of other data collection and evaluation organizations of today. 1 can say that because 1 know their systems. Systems? And they don't hold good. Imagine somebody saying "Well, we shouldn't pay any attention to Agent 622's reports from Kobongo because they're false." Oh? That'd mean one had a turned agent or an agent that wasn't working. In other words, it isn't meaningless, it's not something you discard into the wastebasket. Now a good data collection and evaluation officer doesn't always discard this. He says, "Well, it's false data so therefore it's probably been taken over by the enemy" and he does make some sort of hit at it.

But there are other outpoints that they would never have noticed. "A datum is OK. . . " this is the general think-not just of the generals but this is general intelligence think. "Of the data we receive, a great deal of it is not useful because it doesn't come from reliable observers." Well that's a hell of an outpoint in itself. If an enemy battleship was seen on the coast it wouldn't matter who saw it-intelligence organizations would not pick it up unless it had been observed by a trained officer. "The town could not have been shelled because no reliable observer put a report in-there was no artilleryman to tell us whether or not. . . ."

So our system doesn't begin with "The Slobovians are building 85,000 Panzer tanks, and that's by a reliable observer because Agent 462 has given us factual reports in the past and it's confirmed by aerial observation and satellite pictures. . . ." So what! The intelligence would be " Why are the Slobovians building this many Panzer tanks? Now, is this a lot more Panzer tanks than Slobovians normally build?" because maybe Slobovians go in for a lot of building Panzer tanks so they can call them T-something-or-other and say they were invented in Slobograv. Why? And we right away have a new brand of intelligence-Why? Why are they building these Panzer tanks? One is the fact that they're building these Panzer tanks, is that an outpoint? Well, is it a lot more Panzer tanks than they have built before? Is it a lot less? Did they build a million a year and are only building 200,000 a year now?

Now the officer evaluating this hasn't any Why, he hasn't anything so he makes the supposition that the Slobovians are now easing off. "Yeah, well general, the Slobovians are now easing off." "Yes, Mr. President, the Slobovians are now easing off and everything is going to be fine." The fool! What's the Why? Where's the Why? He assumed something-he didn't investigate further. He didn't look all over the place and find a whole lot of political or such ramifications and add it all up and so forth. Now, had he known about it he would have looked from that data to more outpoints and he would have found something or other-building the tanks for Bongoland so that they could knock out their neighboring country. Why? Why? Because they have a contract with Bongoland to furnish them with tanks. He could've found something like that.

You get these unwarranted conclusions because they don't have the mechanism of asking "Why?" and they don't investigate it until they have an adequate Why that explains it. When you've got a Why you can handle.

One more tip on this whole scene. If you can't find the Why, you revert. 1 learned this about life out of plant research. 1 found out that you went back to the point of major change in a greenhouse or a garden and corrected it the second you saw the plants dying. You required, then, a logging of everything that was done. If you had a log of everything that was done you could get the date and the change. You knew the date they started to wilt so what change was around the vicinity of that date. And you inevitably and invariably found a huge change had taken place. Not a small one, and the tip is that if all else fails, why just go back to your major change and you can do that by stats, go to major change, and so on.

You won't always be right but you're operating on a general Why-there was a change. Every once in a while you'll be scattering around trying to find this.

This works in almost all situations to some degree, what change was there. It has a liability. It tends to wipe out improvements. If you go back to the point of high stuff all the time, all the time, all the time, you're pegging yourself into a pattern where, as a matter of fact, there might have been better patterns. There might have been a better Why in there than just a change of pattern.

Once in a while you'll have found a Why and handled that, but find it keeps slipping out again. For example, an org having to be told to keep in its FP No. 1. FP No. I resulted from an evaluation of financial difficulties. That was a Why at one time and has since become a standard action-but where you keep having to say to an area "Get your FP No. I in"-now why do you have to keep getting in FP No. P The Why is not that FP No. I is out-we have gotten that in as a practiced action. Why does it keep sliding out in this area? There could be several things actually.

If you have to keep saying "Get in C/S Series 25 so that you do have a D of P so that people do come in and are invoiced and so forth," you are obviously running into a Why of why something keeps sliding out.

What is a recommendation? Actually-usually-it would be recommended if somebody else were going to execute it. You have a recommended program and then from a recommended program you have an executed program, so at that moment you shifted your hat. You're no longer an evaluator, you're an executor or an executive.

If your evaluations, that wind up in Whys that wind up in recommendations, are going to autonomously function-that is to say, singly and by itself function-without regard to any other entity or activity, the next thing you know you're going to have fourteen or fifteen programs which are in direct collision which will produce sufficient confusion to reduce the stats. Then you, yourself, will wonder if you've found the right Why because it didn't work. Whereas the reason could be entirely different. The reason is your recommendation was in collision with other Whys and recommendations and so operated to block other actions which were vital to the continuous operation of an activity. You can kill your own recommendation.

If you were in a position where you were going to independently of other evaluators execute all your actions, you might wind up with a mess-you've got your neck out as an evaluator.

The essence of a recommendation is "agreed-upon" and after there is a recom­mendation, there is an "agreed-upon" before there is execution.

An agreed-upon action means that you'd have to agree with other bodies of data which people had-not their personality-other bodies of data. If you have data which is contrary to an action which is being proposed, you could be put in a position of canceling or trying to cancel or recommending a cancellation of a senior's order. Therefore one has to have "agreed-upon" before execution.

When you are collecting data you have a torrent of data coming in. You are collecting data, collecting data, collecting data, collecting data. If that data is not evaluated, it is useless. It is just a useless expense. The only way that data is of any value at all is if evaluations are done on it.

Any independent order given without the benefit of the other evaluations would be a risk. It isn't agreed upon person to person, it's agreed upon data to data. The only agreement would be on whether there is a situation or a no-situation, a good situation or a bad situation or a no-situation. There'd have to be agreement on that point and there would have to be an agreement on the Why. Only then could you get a coordinated recommendation.

You've got to do evaluations. If you don't do evaluations you'll be insufficiently informed to be a competent agreer or disagreer. You'll be insufficently informed to be sufficiently efficient to get the show on the road.

Take advantage of the tremendous volumes of data which come in and, by doing evaluation, provide a sufficient running record of any and all existing situations in your line of country so that there is a general view of what is going on so that the data can be looked at, looked up and one is sufficiently informed so that he can make efficient judgments-and that will decrease the amount of work done on this and that, that doesn't really handle anything.

And it amounts to fewer orders which can then be enforced. It amounts to prosperity because one of the Whys we find on occasion is that there are too many orders drifting around which haven't been executed. One winds up operating on somewhat of a jammed communication line just jammed by volume. The guy that's reading all this stuff is out there and he's got noise and he's got this and they've got bill collectors and he's got something else and so on. He never has time to read it. He doesn't know what the situation is and so forth.

One could also, without proper evaluation, easily issue an order into an area with a hidden Why-which could destroy it.

And the speed of action determines the degree of loss-and that is a rule. The speed of action also determines the degree of gain. And speed has a price. An organization which is not doing well, its Why not accurately found for eight months is a loss for eight months each succeeding week. If an organization should be making fifteen thousand dollars and is only making two thousand dollars you're losing thirteen thousand a week every week that you don't handle it. It's speed of gain or loss.