When it comes time to gather the information and start the analysis there are number of techniques which are helpful. One of the best general-purpose methodologies for intelligence analysis is Richard Heuer’s Analysis of Competing Hypotheses (ACH). First developed by Heuer between 1978 and 1986 while he was an analyst at the Central intelligence Agency, his methodology draws on the scientific method, cognitive psychology, and decision analysis. The method became widely available for the first time when the CIA published Heuer’s now classic book The Psychology of Intelligence Analysis.

ACH methodology helps analysis overcome cognitive biases common to competitive intelligence. Using ACH forces analysts to set aside their preconceptions and look for inconsistencies in the data that may indicate a flaw in their reasoning. This method forces the analyst to disprove hypothesis rather let their minds jump to conclusions and permit biases and mindsets to determine the outcome before they properly evaluate the evidence.

Simple Example of ACH Matrix

The analysis of competing hypothesis is a very logical process consisting of eight fairly straightforward steps. A summary of the method follows and more complete details can be found in chapter 8 of Heuer’s book.
1. Hypothesis generation. This step requires divergent thinking to ensure all hypotheses are considered, and convergent thinking to ensure that redundant and irrational hypotheses are eliminated from the final set of hypotheses.
2. List evidence and arguments. Evidence should be interpreted broadly to include all factors (assumptions or logical deductions, goals, and standard procedures regarding the entity being assessed) that might have an impact on judgments about the hypothesis.
3. Create a matrix. Take the hypothesis from step one and the evidence from step two and put them into a matrix. This matrix has the question to be answered listed across the top and the hypotheses associated with that question listed in rows beneath it. Possible answers to the question (evidence that the hypothesis is correct) are listed as column headers. Within the matrix, one piece of evidence at a time, the decision is made whether the evidence is consistent with the hypothesis or not. Each cell is marked with a plus or minus depending upon whether consistency exists.
4. Refine the matrix. In this step, the hypothesis is reassessed in light of all the evidence. The hypothesis is reconsidered or reworded to reflect all the significant alternatives.
5. Tentative conclusions. Working down the columns of the matrix, each hypothesis is reviewed to draw tentative conclusions about the relative likelihood of each one.
6. Reevaluate weight of critical evidence. Re-examine key assumptions and pieces of evidence that seem to drive the analysis in a particular direction. Now that the analyst understands the logic of what counts and what doesn’t in the analysis, he or she should go back and examine each piece of it in detail for flaws. Does it make sense whole and in part? This step is key because when analysis turns out to be wrong, it is often because of key assumptions that went unchallenged and later proved invalid.
7. Report conclusions. One of the real strengths of ACH is that it makes the logic behind the analysis transparent to the decision-maker.
8. Milestones for future observation. Because events are dynamic and subject to a variety of influences, analytic conclusions are always tentative. Therefore specify in advance that certain occurrences, if observed, could cause significant changes in the probability of the accepted or alternative hypothesis. Collection of additional information can also suggest possibilities that may occur in the future.