Practices:Morphological Analysis & Relevance Trees

Morphological Analysis & Relevance Trees are normative forecasting methods which start with future needs or objectives, and then seek to identify the circumstances, actions, technologies, etc. required to meet them.

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Overall description
Morphological Analysis & Relevance Trees originated in strategic planning. They are two of several normative forecasting methods which start with future needs or objectives, and then seek to identify the circumstances, actions, technologies, etc. required to meet them. A relevance tree is an analytic technique that subdivides a broad topic into increasingly smaller subtopics thereby showing 'all' possible paths to the objective, and provides a forecast of associated costs, durations and probabilities for each element. Similarly, morphological analysis involves mapping options to obtain an overall perspective of possible solutions.

When is this method appropriate?
The method can be used to identify problems and solutions, establish feasibility, select the 'optimum' solution and deduce the performance requirements of specific policies, technologies, etc. It may also be used to estimate the overall cost and duration of implementing policies or increase technological performance, thereby scheduling the detailed R&D programme. The purpose of morphological analysis is to organise information in a relevant and useful way in order to help solve a problem or stimulate new ways of thinking. It has often been used for new product development but also in constructing scenarios.

Approach (Step-by-step Guide)
A relevance tree looks much like an organisational chart and presents information in a hierarchical structure. The hierarchy begins at a high level of abstraction and descends with greater degrees of detail in succeeding level of the tree. The entries at a particular level are intended to describe, in a complete manner, the item to which they are connected in the level above. Ideally, each entry at a particular level is orthogonal, that is, it should not overlap with any other entry, thus being mutually exclusive of other entries. Finally, the items at the same level should be addressed from the same point of view. If done properly, the structure can lead to a clearer understanding of the topic under analysis. Morphological analysis involves mapping a discipline to obtain a wide perspective of existing solutions and future possibilities. The approach can be based on five basic steps: Steps 1, 4, and 5 often stem from a different analysis, whereas steps 2 and 3 form the heart of morphological analysis, as step 2, identification of parameters, involves studying the problem and present solutions with which to develop a framework. This step can involve developing a relevance tree to help define a given topic. Once the parameters are identified, a morphological box can be constructed that lists parameters along a single axis. The second axis is determined by the nature of the problem.
 * Formulation and definition of a problem;
 * Identification and characterisation of all parameters toward a solution;
 * Construction of a multidimensional matrix (morphological box) whose combinations will contain all possible solutions;
 * Evaluation of the outcome based on feasibility and achievement of desired goals; and
 * In-depth analysis of the best options considering available resources.

Pros and cons
Advantages: Relevance tree analysis has demonstrated to be a powerful intellectual stimulus to ensure that a given problem or issue is illustrated in comprehensive detail and that the important relationships among the items considered are shown in both current and potential situations. Morphological analysis allows for two key elements:
 * A systematic analysis of the current and future structure of an industry area (or domain) as well as key gaps in that structure.
 * A strong stimulus for the invention of new alternatives that fill these gaps and meet any requirements imposed.

Potential drawbacks: The development of relevance trees or morphological analysis, like most of Foresight methods, requires critical judgement thus the possibility of human error is present. Finally, if the underlying thought processes are not insightful, the outcomes of this method will be weak.

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