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decision maker understand the limitations of differing analytical tools and allow for these in the decision making process?

. Was the decision maker fully able to comprehend all aspects of the analysis output?

Unsystematic development error

. Did events arise during the course of the process that derailed the analysis or analyst?

. What impact did unexplained variance or random factors have on the outcome of the analysis task?

Errors of analysis can occur in one, or combination of several, of these categories.

Having located the source, or sources, of error, only then is corrective action effective.

Four-level hierarchical model of analysis failure

Whatever the reasons experienced for CI analysis failures, it is valuable to identify why it happens and this is represented in a four-level model for identifying the barriers to generating effective CI analysis. These four levels, and the primary factors associated with each, are illustrated in Table 1.

While each of these sections warrants a full discussion on its own, for the purposes of this paper, the concentration will be on the aspects which, it is proposed, can be most effectively influenced by the individual analyst. Some of these factors may be present in other categories and it is recognised that there may be secondary or tertiary impact at other levels.

Causes of failure at individual analyst level

The CI analysis task is fundamentally performed by individuals, although they will also co-operate and collaborate with others to get their tasks accomplished. From consulting and educational assignments, as well as research, it has been possible to observe the following hindrance factors as being primarily present at the level of the individual analyst.

Different natural analytical abilities

People rely on a limited set of mental models, have preconceptions on issues and exhibit a wide range of cognitive bias when reviewing information (Clayton & Kimbrell, 2007). People also think differently. Some, in a left-brained, analytical, logical and verbal fashion, whereas right-brained people tend to be creative, holistic and spatial (Hines, 1987). Innovation is a right-brain activity, not a left-brain activity yet both educational institutions and business organisations reward left-brain work, while discouraging rightbrain thinking (Pink, 2005). This is important when viewed in light of analysis being a mixture of both scientific and non-scientific techniques. In other words, analysis benefits from the adoption of a whole-brain approach to thinking (Spreng & Grady, 2010).

Naturally limited mental capacities

The content and context facing most CI analysts have become more complicated, complex and fast moving in recent years. Having said that, the brain’s natural abilities to effectively process additional information has not evolved to match this. The popular view is that we only use 10% of our brain’s ability and while one could argue with the figure, it is clear that human beings still only use a limited percentage of their brain capacity (Sousa, 2009). Scientific record though, still does not have a sense of what that percentage might be (Klingberg, 2009). In his influential article, Miller (1956) suggested that the magical number describing our natural information processing capabilities is seven things at one time, plus or minus, two. This could be a major problem for CI analysts who often have a far higher number of issues to keep in their mental calculus at any one time. Although information technology systems have developed to assist in the analysis task, we still have to use our brains in the same way as we have always done (Shacham, Cutlip, & Brauner, 2008).

Table 1.    Four-level hierarchical model of analysis failures.

Level                                                     Nature of problem

Natural motivation

Given a choice between a more difficult, and a less difficult task, with identical outcomes, the majority of people would opt for the easier task. As may be coming patently obvious by now, analysis is not an easy