How Does Analysis of Competing Hypotheses (ACH) Improve Intelligence Analysis?
Summary and critique by Jared Leets
Richards Heuer Jr discusses the three different approaches to Analysis of Competing Hypotheses (ACH) and four significant steps in the intelligence analysis process which include researching relevant information, organizing information to help with analysis, reviewing the information to make a credible evaluation, and finally writing the product.
Heuer Jr states that when searching for information, the purpose is to get the analyst to challenge his or her initial mindset. Researching alternative hypotheses helps the analyst broaden his or her search for information that they typically would not look for. When analysts initially work with ACH they consider it beneficial due to the fact that it forces them to think about evidence and outcomes that had never occurred to them. In the first step ACH is an easy strategy for questioning a complex problem. Every analyst should seriously consider questioning their traditional way of answering a question to a problem.
The second step is organizing the information. Two principles, decomposition and externalization, exist to help cope with human mental perception and memory. Decomposition refers to breaking down the problem while externalization refers to removing the problem out of someone’s head and writing it down in order to simplify the problem and show the variables. The purpose is to show all of the evidence and what type relationship they share if any. The three types of ACH manual, automated, and Bayesian all have their differences. The manual ACH views only the relationship between each individual piece of evidence and hypotheses. The matrix will assist the analyst in evaluating evidence that is most indicative in opposing hypotheses
The automated ACH allows analysts to place evidence in categories. The categories include date, type of source, credibility of source, and the relevance of the source. By sorting the evidence it makes it much easier for the analyst to put all his or her efforts towards the most convincing evidence. The Bayesian ACH places more importance on the relationship between the evidence and hypotheses. It typically has multiple sets of hypotheses, which tend to increase judgments that must be made in the analytical process.
Heuer Jr states that in the third step, analyzing the information, the automated ACH will sort the evidence by categories while the Bayesian ACH will give a mathematical algorithm that shows the analyst a possible answer. Sorting evidence by relevance in categories significantly helps with intelligence analysis. Heuer Jr explains that in the automated version an analyst can compare evidence from a clandestine source or open source can help reveal deception from a source. While the inconsistency and weighted inconsistency scores can produce an accurate estimate, the analyst must use their own judgment in the end. According to Bayesian ACH proponents, they claim that using an Inconsistency Score or Weighted Inconsistency Score is problematic since it relies on incomplete information. A Bayesian inference is ideal for making probabilities bases on judgments from intelligence analysts. However, it is very complex, time consuming, and requires a Bayesian methodologist to help the analyst when it is being conducted. Proponents state that this displays how complex an intelligence problem can be and that one single analyst cannot make a judgment call without help from other sources. In the final step, writing the product, Heuer Jr says each ACH has its benefits and can help the analyst in reinforcing what their research has revealed or shows the analyst an alternative path for additional research.
ACH has it benefits and its obstacles. For example, it is very good at helping an analyst see alternative hypotheses and pieces of evidence and weighing that evidence to help make a correct decision. In any intelligence project an analyst must think from different points of views. ACH can help an analyst go step by step and see if their current hypothesis will answer the intelligence requirement. However, ACH can also have its issues. As Heuer Jr explains, when weighing evidence it is easy to be biased, especially when deciding how credible or relevant a piece of evidence is. In addition, software can only help an analyst come to a decision. If an analyst says that ACH told them the answer and base everything off of that, they will likely lose credibility. In the end, ACH can help with intelligence analysis by helping the analyst think of different ideas to address the problem and support their research, but it can also be a problematic if analysts rely too much on it as software cannot answer problems in the intelligence profession.
Source: Heuer Jr, Richards. (October 16, 2005). How Does Analysis of Competing Hypotheses Improve Intelligence Analysis? Pherson Associates. http://www.pherson.org/wp-content/uploads/2013/06/06.-How-Does-ACH-Improve-Analysis_FINAL.pdf