ACH je proces o 9ti krocích

Plný ACH proces se řídí následujícími osmi kroky.

1. Definujte otázky

Ujistěte se, že všichni zúčastnění rozumí specifickým dotazům, které je nutné odpovědet.

2. Identifikovat všechny možné hypotézy

Identifikovat možné hypotézy, které je třeba zvážit. Použijte skupinu analytiků s různým hlediskem a proberte možnosti. Hypotézy by měly být vzájemně vylučující, pokud je některá hypotéza pravdivá, musí být všechny ostatné nepravdivé. Více informací po kliknutí.

3. Make a list of evidence and arguments for and against the hypotheses

Remember to include assumptions, logical deductions, and conclusions from other analyses--anything that affects your judgment about the likelihood of any hypothesis. Also include the absence of evidence one would expect to find if a hypothesis were true. We have a dedicated article on evidence as well.

4. Prepare a matrix with the hypotheses across the top and the evidence/arguments down the side

Work horizontally across the matrix to rate each data item\'s consistency or inconsistency with each hypothesis. There is an option to also assess the Credibility of each item of evidence to determine how much weight it should have in the analysis. Check the diagnosticity of the evidence. An item of evidence is diagnostic if it helps you determine that an item of evidence or argument shows that one or more hypotheses may be less likely than the others.

When you\'re done, you should have something like this:

In this example, Hypothesis 1 is looking pretty unlikely. (But remember, that doesn\'t necessarily mean that Hypothesis 2 is correct. Our goal is to refute hypotheses, not prove them.)

5. Reconsider the hypotheses

Have you learned anything that might suggest they should be modified? Check the consistency of your evidence ratings. Discard evidence that has no diagnostic value because it is consistent with all the hypotheses. Identify any gaps in the evidence and arguments that may need to be filled. Delete any evidence that has no diagnostic value because it is consistent with all the hypotheses.

6. Check the Inconsistency or Weighted Inconsistency Score and draw tentative conclusions about the relative likelihood of each hypothesis

The most likely hypothesis is the one with the lowest score. Sort the evidence and arguments by diagnosticity to identify those few items that are most influential in driving your conclusions. Consider the consequences for your analysis if any key item of evidence or argument is wrong, misleading, or subject to a different interpretation? Sort the evidence by type of source and be alert to any indication of possible deception.

7. Compare your personal conclusions about the relative likelihood of the hypotheses with the Inconsistency Score or the Weighted Inconsistency Scores generated by the software

If they differ, figure out why and make appropriate adjustments. See guidance in the sections on Interpreting the Inconsistency Scores. Solicit critical input from other analysts. Draw your final conclusions.

8. Report conclusions, discussing the relative likelihood of all the hypotheses, not just the most likely one

Include discussion of the diagnostic evidence or arguments that enabled you to reject or discount the alternative hypotheses.

9. Identify indicators or milestones for future observation to monitor whether one or more hypotheses might be changing.

That\'s it.

This process can be done on your own or with a group. If you want to do ACH with multiple analysts, the next article will give you some guidance on modifying this 9-step process for collaborative, multi-analyst projects.

Otherwise, skip ahead to learn about hypotheses.