How Does Analysis of Competing Hypotheses (ACH) Improve Intelligence Analysis?

Summary and Critique by Michael Z
Richards J. Heuer, Jr., 16 October 2005

The meat of Heuer’s article really begins with him first explaining how Analysis of Competing Hypotheses (ACH) aids in the search for information at the very beginning stages of analysis. He notes that it is in this first step that “ACH does the most to help the analyst avoid being caught by surprise.” This is achieved by forcing the analyst to consider a much wider array of information that would otherwise be pursued by the analyst and is further achieved by casting a different perspective on what the analysts already knows as a result of their focus on rejecting hypotheses. Heuer takes time to contrast ACH with what he calls a “satisficing” approach in which an analyst knowledgeable on the topic of analysis develops a favored hypothesis and seeks evidence to confirm it. Ultimately Heuer states that while such an approach is efficient and and oftentimes safe, that it does not protect the analyst from surprise and cannot distinguish that certain pieces of evidence may be consistent with more than the favored hypothesis.

Heuer then explains how ACH is beneficial in the assembly and organization of information used in analysis. He explains that all three forms of ACH abide by the basic principles of decomposition and externalization, which he notes as two principles which are present in all simple tools that analysts use to overcome limitation in human cognition. All three forms of ACH achieve through the use of of an analytical matrix that allows the user to break down the issue into its component parts. Heuer then goes into detail as to how each three forms of ACH, (Manual ACH, Automated ACH, and Bayesian ACH), utilize their own matrix in order to assist in making judgements.

The next section of the article focuses on how ACH assists the analyst in the actual analysis of the information. In this section he notes a great distinction between Bayesian ACH and the other two forms of ACH, and this is that Bayesian ACH provides the analyst with an algorithm that supplies the analyst with an answer, while the other two forms of ACH are instead utilized as a process that aids in the analysts ultimate judgement on the issue. After which he then goes into further detail about each ACH method.

In the next section of the article Heuer takes note of the advantages of ACH during the writing of a report. One of the greatest benefits provided by ACH is the consideration of alternative viewpoints beyond the ultimately proposed analytical theory. Another advantage listed is that ACH allows for one to present the consideration and rationale that each piece of evidence was given and provided for the ultimate analysis. In provided such information in the report readers can more easily understand how exactly the final analytical judgement was achieved.

Critique:

Overall I am very satisfied with Heuere’s explanation and presentation on how analysis can benefit from ACH at each step of the denoted analytical process. This method of presenting and explaining ACH flowed logically and allowed the ready to immediately grasp how ACH would improve their analysis.

However I felt like the article would have benefited from further discussion of how the analyst navigates each step of the process along each type of ACH. For example an explanation of how an analyst decides which categories to utilize in Automated ACH and how they make judgements about the weight and reliability of each piece of evidence. Ultimately though this is a very minor criticism of an otherwise great explanatory article by the developer of ACH himself.