The Data Series policy letters are found in Management Series Volume 1.

They are about logic - how to think correctly and reach correct conclusions.

Let us make an assumption that the mind is a perfect computer.
It always gets the right answer, which is to say CONCLUSION.

The only way it gets a wrong answer (CONCLUSION) is if the data entered into its thinking process is faulty. When it computes with FAULTY DATA it arrives at a wrong answer.

An OUTPOINT is FAULTY DATA TO COMPUTE WITH.

Thus, when one enters FAULTY DATA (an outpoint) into the computer, it arrives at a wrong answer (CONCLUSION).

So, it is not the computing that is to blame for wrong answers, it is the data used to compute with. Thus, you get the following datum, which is the backbone of the Data Series:

REASON DEPENDS ON DATA

The only way you get UNREASON (wrong answers, conclusions) is because you used faulty data to think with. Get it?

All an outpoint is, is a FAULTY DATUM.

UNREASON will inevitably result from thinking with outpoints, when one does not recognize they are OUTPOINTS, and thinks it is VALID DATA.

WHEN YOU USE OUTPOINTS TO THINK WITH, YOU ARE GOING TO GET A WRONG ANSWER, A WRONG CONCLUSION, WHICH IS TO SAY - UNREASON.

The outpoints that cause wrong answers are -

List of Outpoints:
Omitted Data
False Data
Altered Importance
Altered sequence of events
Dropped Out Time

Those are the five primary ones. There are some more refined ones, like:

Contrary Data
Added Inapplicable Data
Incorrectly Included Data
Wrong Target
Wrong Source
Added Time
Assumed Identities that are not Identical
Assumed Similarities that are not Similar
Assumed Differences that are not Different

DRILL

Take an outpoint, like false data, and see how that would result in a wrong answer.

Data - Joe was at home with wife at 8PM last night.

Data - Across town, Mary was murdered at 8PM last night.

False data - Joe was at Mary's house at 8PM last night.

Wrong conclusion = Joe may have murdered Mary.

Data - Joe works at Pete's Bakery in the daytime.

Data - People like Pete's Bakery and happily shop there.

Omitted Data (for Joe) - Pete is a serial killer at night.

Wrong conclusion = Joe thinks Pete is a nice guy who only helps people.

Do you see how using an outpoint to think with causes a wrong conclusion?

Applying the above to the Church - Scientologists have Omitted Data on the Church. Church PR only gives Scientologists positive data about the Church. Thus Scientologists are thinking with the outpoint of Omitted Data about the church. Thus they have reached a Wrong Conclusion that all is well when it isn't.

DATA ANALYSIS consists of looking over a body of data for outpoints.

That would be Data Analysis for a bad Situation.

Data Analysis for a good Situation would be looking over the data for pluspoints.

Pluspoints are valid data to think with.

You simply reverse the list of outpoints given above and you have the pluspoints.

EVALUATION:

Basically, you or a group has a purpose to do something.
That would be your intended product.
Let's say it is to grow tomatoes.

The IDEAL SCENE would be lots of viable tomatoes growing or grown.

The EXISTING SCENE can fall away from, or depart from the IDEAL SCENE.

Let's say the Existing Scene is - no tomatoes to eat or sell

There is a reason for the lack of tomatoes, and that reason is the WHY.

Thus, an investigation is started to find the WHY.

One collects data on the tomato growing operation and finds outpoints.
The outpoint trail leads one to discovery of the SITUATION.
Situation defined is - THE MAJOR DEPARTURE FROM THE IDEAL SCENE.
SITUATION = tomatoes are dying

Why are they dying?

They were growing just fine in June. Now dieing in July. WHAT CHANGED?

We find that on July 1, the water system broke. No water to tomatoes. So:

IDEAL SCENE = lots of tomatoes

EXISTING SCENE = no tomatoes

SITUATION = dieing tomatoes

WHY = no water to tomatoes

HANDLING = fix water system, water tomatoes

The correct WHY and HANDLING will fix the SITUATION thus moving the EXISTING SCENE back towards the IDEAL SCENE.

Pretty simple, really.

Now, take the above and apply it to the church and what we have been doing, meaning collecting data and assigning outpoints to it, all leading up to an Evaluation of the church, and what we are doing here should then start to make sense to you. You now have an Instant Hat on how to do an Evaluation.

So, let's apply the above to the church -

Scientology PURPOSE and PRODUCT = FREE SPIRITUAL BEINGS

IDEAL SCENE = lots of FREE BEINGS produced by the Church

EXISTING SCENE = no FREE BEINGS have been produced by the Church

Now we have an outpoint - OMITTED PRODUCT OF FREE BEINGS

Per the Data Series there is NO SUCH THING as an outpoint, without a Situation.

Where you find an outpoint - there you will find a Situation. Always.

Now we know with stone cold absolute certainty, there is a SITUATION here.

By using Data Analysis we found what that SITUATION is.

For years we have been putting together a chronological history of the church. We then did a Data Analysis and assigned outpoints to it. This told us the SITUATION and further investigation led to discovery of the WHY.

With the SITUATION and WHY known - we devised a HANDLING that will -

Fix the SITUATION thus moving the EXISTING SCENE towards the IDEAL SCENE.

This takes the stops off of the Church product - FREE SPIRITUAL BEINGS !!

Finally, please realize that the Data Series is Ethics technology.

Ron defines out ethics as a non-survival act or CONCLUSION.

Wrong conclusions come from thinking with faulty data (outpoints). When a being uses bank data to compute with - he is using faulty data to think with - thus he gets wrong conclusions and is therefore out ethics.

Ethics are REASON.

Which is to say Ethics is correct thinking that arrives at correct conclusions.

Which is to say - Out Ethics is stinkin thinkin !

The Data Series tells you how to REASON.

So, the Data Series tells you how to be ethical.

Learning the Data Series causes a rise in tone level, because it moves one up out of the Reactive Mind level of thinking, into the Analytical Mind level of thinking – REASON.