Cognitive Mapping is a form of Causal Mapping developed and popularised by Colin Eden and Fran Ackermann (Eden, 1988, Eden & Ackermann, 2001, Ackermann and Eden, 2001). This paper reports on research in progress to develop, test, and employ extensions to cognitive mapping to support decision making in the context of problem formulation and solutions derivation, comparison, and choice. The paper describes extensions to the method and notation, include the use of colour (or bolding) to indicate whether nodes are desirable or undesirable, the conception of two forms of cognitive maps, the first of which focuses on the current, undesirable context and the second on a desired, future context (and how to achieve it), and a procedure for developing and converting between these two forms of cognitive maps. The paper also describes the current state of the research on coloured cognitive maps, open issues, and planned and proposed future research. Cognitive Mapping is a form of Causal Mapping developed and popularised by Colin Eden and Fran Ackermann (Eden, 1988, Eden & Ackermann, 2001, Ackermann and Eden, 2001). Cognitive Maps are related to concept maps (sometimes called mind maps). In mind maps, though, the links can have any meaning, while in cognitive maps, links are only causal (as described below). Eden & Ackemann's work has focussed primarily on the context of strategic planning and decision making about organisational strategies. The author's work instead focuses on decision making in a context of problem solving, particularly on problem analysis and formulation and the transition to solution identification, analysis, and choice. This paper describes an enhanced version of this diagramming technique as developed by the author. The enhancements given in this paper to the cognitive mapping technique as developed by Eden and Ackermann include … 1. A conceptualisation of two forms of problem statements and two corresponding forms of cognitive maps: “problems as difficulties” and “problems as solutions” 2. A procedure for straightforward conversion between these two forms of cognitive maps 3. Colouring of nodes to indicate desirability or undesirability 4. An overall process for problem analysis with cognitive maps David Kroenke has defined a problem as “A perceived difference between what is and what should be” [emphasis added]. It is argued in this paper that the above enhancements provide a straightforward way to analyse a problem, because it aids in exploring first the what is about the problem situation and then effectively transitioning to exploring the what should be in the problem situation. Thus it explores both problem diagnosis first and then problem solution derivation second.
Section 2 gives an overview of the enhanced cognitive mapping notation, including coloured nodes (enhancement 3 above). Section 3 gives an overview of a new procedure for problem analysis with cognitive maps (enhancement 4 above), which includes a conceptualisation of two forms of problems (enhancement 1 above). Sections 4 through 6 describe each of the three stages in the procedure (Problem Diagnosis, Cognitive Map Conversion, and Solution Derivation) in more detail. Section 7 describes the current state of the research, open issues, and planned future research. The paper concludes with a summary and review of the more important points covered in the paper. 2. An Enhanced Notation: Coloured Cognitive Maps
used: nodes and arrows. See figure 1 for a summary of the notation.
Nodes are drawn with circles or ovals (or some other convenient symbol) and represent some aspect of a problem, whether it be the problem itself, an undesirable consequence or implication of the problem, a cause of the problem, some planned action relating to the problem, or potential solutions to the problem. Text is placed within each node, which captures the meaning of the node. The text in the node can also be split into two parts or poles, which are separated by an ellipsis symbol (“…”). The text in these poles represents opposites and the ellipsis is read as “as opposed to”. For example, the text in a node might be “Poor service … excellent service”. This would be different from “Poor service … acceptable service”.
An extension proposed in this research is that the nodes of a CM can be coloured to indicate whether the node represents something that is desirable or something that is undesirable. Green coloured nodes represent desirable circumstances and red coloured nodes indicate undesirable circumstances. Generally, one of the poles in a node should be desirable and the other one undesirable, with the colour corresponding to the primary pole (the text that comes first). Where colour cannot be used, another indication is needed, such as bold print and darker lines for undesirable nodes (as used throughout this paper). An advantage of using coloured (or bold) nodes is that it gives a quick visual indication of the desirable vs undesirable parts of the CM without needing to read the details of the text.
- Goal, activity, problem,
cause, implication, etc. - Poles separated by ellipsis, - Red/bold = undesirable, Green = desirable
- Causal or contributory - Plus sign or minus sign (plus assumed if absent) + or
Nodes are connected to each other with arrows. Arrows represent some degree or amount of causality between the nodes, i.e. the node at the tail of the arrow causes (to some extent) the node at the head of the arrow. Figure 2 shows three generalised examples of causality in
The arrows may optionally have plus or minus signs attached to them. If a sign is omitted, a plus sign is assumed. If a minus sign is attached, it means that the causality is reversed; instead of the node at the tail of the arrow causing the node at the head of the arrow, the node at the tail prevents the node at the head or causes its opposite pole. Table 1 also shows alternative meanings for the arrow when it has a minus sign attached.
3. A Procedure for Analysing Problems with Cognitive Maps In order to make effective use of cognitive maps for problem analysis, a procedure is needed to guide the user(s) of cognitive maps as to what specific actions to perform and how. The procedure for problem analysis proposed in this paper is divided into three stages (see figure
difficulties. The second stage is to convert the cognitive map of the problem as difficulties into a cognitive map of the problem as solutions. The resulting cognitive map is incomplete, but a basis for progressing in the third stage. The third and final stage is solution derivation, in which the cognitive map of the problem as solutions is expanded with various candidate or potential solutions. Each of these three stages is described in more detail in sections 4 to 6.
of a Problem as
4. Problem Diagnosis: Analysing the Problem as Difficulties It is a key assumption of this research that effective problem solving requires problem solver(s) to develop a sufficiently rich understanding of the current, problematic situation (the decision context) before proceeding to solution choice. The problem solvers need to understand what is undesirable about a problematic situation, why it is problematic to the stakeholders, and what the causes of the problem are – i.e. what things allow the undesirable circumstances to exist. These all need to be carefully analysed in order to develop the rich understanding necessary to come up with effective and appropriate solutions to the problem. Cognitive Maps (CMs) can be used to support this by drawing CMs that focus on the current situation (or context) and what is undesirable about it. We call these CMs of the “Problem as
undesirable (coloured red or bolded). However, some nodes will still likely be desirable ones.
up by beginning with an initial statement of the problem in one node, splitting that into separate nodes of it is a composite, rather than elementary, problem. Then other nodes are added that explore the consequences of the problem (which are what makes it undesirable) and the causes of the problem. There is a 10-step procedure for carefully doing this, as shown below.
problem and connect with arrows from the problem to the implication/consequence. Note that a problem may have desirable as well as undesirable consequences, so colour the nodes appropriately. 3. Make sure the node text is clear and unambiguous, using opposite poles to clarify. 4. Add nodes further above for implications of the implications, etc., and connect with arrows. Again, colour the nodes appropriately. 5. Add nodes below the problem node for causes and connect with arrows from the cause to the problem. 6. Add nodes further below for causes of causes, etc. and connect with arrows. 7. Add nodes above causes for other consequences of causes, including desirable ones, and connect with arrows.
necessary, split complex nodes into two or more nodes and rejoin with new arrows.
Symptom, Implication, or Consequence
Problem
Cause problem relate to each other. This is captured with the causal arrows. Note as well that the cognitive map in Figure 5 could still be further expanded with other causes toward the bottom (e.g., poor work skills) and other implications or consequences toward the top (e.g., lower profit). It is also important to be sure that you have identified and included all of the relevant aspects of the problem in your cognitive map of a problem as difficulties.
Lower … normal repeat business
Poor … good customer service
Work done poorly … well Too much … right amount of work
Insufficient … enough time
Once a problem is fully analysed and diagnosed, then we can begin thinking about solutions.
Improvement of a Symptom or Implication
Solving or Alleviation of a Problem
Elimination or Reduction of a Cause secondary pole and what was once the secondary pole is transformed into the primary pole. The colour of each node is also changed to indicate the change. In switching the poles, usually, one must modify the text for poles of nodes so it makes sense and is appropriate for its colour (desirability). In CMs of problems as solutions, the text of the nodes should be in the imperative tense, i.e. a command, with an action verb first followed by an object noun, such as “Do this” or “Stop doing that”. The text is usally changed to be elimination or reduction of causes, solving or alleviation of problems, or improvement of symptoms or implications. There is a step-by-step procedure for carefully doing this, which is given below. Cognitive Map Conversion: Procedure to Convert the CM of the Problem as Difficulties to a CM of the Problem as Solutions Reverse all nodes to make undesirable nodes desirable and desirable nodes undesirable 1. Change colour of all nodes – red to green and green to red. 2. Switch the opposite poles of the text – primary pole to secondary, secondary pole (if present) to primary.
a. Elimination or reduction of causes b. Solving or alleviation of problems c. Improvement of symptoms or implications
Once an initial cognitive map (CM) of a problem as solutions has been derived from the CM of the problem as difficulties, it needs to be enhanced to explore different potential solutions and the consequences if one was to implement one or more of the potential solutions. Solutions cause the reduction or elimination of causes and therefore indirectly solve or alleviate problems. Possibly, a solution may directly solve or alleviate a problem, but the causality of such a link must be considered carefully to determine whether it is correct. One should also explore undesirable consequences of implementing a solution as well and append those to the CM accordingly. There is a five-step procedure for carefully doing this, which is shown below.
Lower …. normal repeat
business Poor … good customer
service Work done poorly … well
Reverse poles of problems, symptoms, implications, or causes 1. Add nodes toward bottom for solutions - how to achieve elimination or reduction of causes.
imperative (command) verb, followed by an object noun.
correct.
As noted in the introduction, this is research in progress. This section describes what has been done so far with coloured cognitive maps, open issues that have been identified, and planned future research.
Other
Desirable Consequence
Improvement of a
Symptom or Implication
Solving or Alleviation of a
Problem Elimination or Reduction of a
Cause Potential
Solution
Detail of How to Achieve the Solution
Other Undesirable Consequence
developed and worked out. Testing and evaluation of the notation and procedures has been limited so far to its use by first year students in a unit titled “Problem Analysis”. The context of the unit is in an Information Systems undergraduate degree program, as a follow-on unit to an Introduction to Information Systems and as a first unit in a stream of units relating to
rigourous evaluation of the new method is needed. More careful gathering of data with student users is possible and could be very enlightening. More formal experimental evaluation is also possible, but evaluation in more naturalistic settings should be conducted.
Increase … lower repeat
business
Improve … poor customer service Do work
well … poorly
Reduce workload … too much work
Provide enough … not enough
time Automate some tasks … continue manually
Take fewer
… same number of orders
Hire more … same number of staff
- Pay costs
of Automating … no cost
Pay staff for overtime … same hours
Reduce …
same income
Increase … same staff costs The form of the notation could be made somewhat more complex to yield finer gradations of perception of the problem and solution context. For example, rather than being just one shade of red or green, the notation could use darker shades of red or green to indicate nodes that are more desirable or undesirable and lighter shades of red or green for nodes that less desirable or undesirable (or even balanced/both). Similarly, the lighter shades of colours (or even white or other colours) could be used to indicate nodes where the desirability vs undesirability is unknown, unevaluated, or an open matter of group debate.
Building on the levels of desirability or undesirability in the nodes and levels of causality in the arrows, one could try to formalise the diagrams and perform forms of automated analyses, which could be used to support comparison of different candidate solutions in a network of candidate solutions and outcomes in a CM of the problem as solutions. The groundwork for this could also be laid at the stage of analysing the CM of the problem as difficulties (before conversion).
other experts might use the technique to interact with client(s) and how useful or well received that might be. Similarly, issues of group interaction using coloured cognitive maps have not been explored. However, Eden and Ackermann have already developed extensive experience and demonstrated value in these areas using regular (non-coloured) CMs.
could be built, similar to Decision Explorer (available from banxia.com), which provides extensive tool support for regular cognitive maps, including editing, navigation, and analysis.
More formal evaluation of the technique in classroom settings is planned. Initially this will be an evaluation of the elementary (unshaded) form of coloured cognitive maps.
consulting environments, through a programme of action research.
The author is also collaborating with a different researcher to build and evaluate a collaborative tool to support student groups in creating, discussing, editing, and using coloured cognitive maps. For the moment, this is planned to be in their elementary (unshaded) form. Such a tool would have not only the purpose of supporting the use of CMs in decision making, but also of supporting learning of the coloured cognitive mapping technique and also being able to aid instructors in supporting and assessing student learning.
Cognitive mapping is a graphical technique that can be used to model parts of a decision context and to analyse problems from problem diagnosis through solution derivation and comparison. This paper has proposed a simple and straightforward way to analyse problems using the coloured cognitive mapping technique. In particular, it has discussed four extensions to cognitive mapping from the existing literature – a conceptualisation of two kinds of problems (problems as difficulties and problems as solutions), the use of coloured nodes to indicate desirability or undesirability of the node, a simple procedure to convert cognitive maps from problems as difficulties into problems as solutions, as well as an overall process encompassing the above three extensions for using cognitive maps to support and facilitate analysis of problem situations. Additionally, the technique supports generation of potential solutions to the problem based on the understanding of the problem situation (context) and analysis and comparison of the potential (candidate) solutions. While a basic approach has been defined, several areas of open research issues remain, some of which are identified in the paper.