IJAHP Essay: Ishizaka/Visual management for decision analysis International Journal of the Analytic Hierarchy Process 141 Vol. 9 Issue 1 2017 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v9i1.475 VISUAL MANAGEMENT FOR DECISION ANALYSIS Alessio Ishizaka Centre for Operational Research and Logistics, Portsmouth Business School, University of Portsmouth, Portsmouth PO1 3DE, United Kingdom Alessio.Ishizaka@port.ac.uk ABSTRACT Visual management has been recently recognized as an excellent way to convey decisions in a clear and convincing way. AHP already used visual techniques for evaluating the pairwise comparisons and performing a sensibility analysis. In this paper, we introduce a new descriptive tool GAIA that can be coupled with AHP in order to visualize the entire problem on a unique plane. https://doi.org/10.13033/ijahp.v9i1.475 Keywords: Visual management; GAIA; descriptive tool 1. Introduction It is well-known today that the Analytic Hierarchy Process (AHP) is an extremely useful method. Several reviews have compiled their success stories (Zahedi 1986; Golden, Wasil et al. 1989; Shim 1989; Vargas 1990; Saaty & Forman 1992; Forman & Gass 2001; Kumar &Vaidya 2006; Omkarprasad & Sushil 2006; Ho 2008; Liberatore & Nydick 2008; Sipahi & Timor 2010; Dung, Luan et al. 2016). In this paper, we argue that the usefulness of AHP can be enhanced with visual management techniques. Visual techniques have long been used in AHP for evaluating the pairwise comparisons ( Figure 1) and performing a sensibility analysis ( Figure 2). They have been integrated into the main software that supports AHP, and greatly facilitated the decision-making process (Ishizaka & Labib 2009). However, visual techniques cannot only facilitate the decision-making process but can also be used as a descriptive tool that explains the whole problem (Nemery, Ishizaka et al. 2012). In the next section, we present GAIA, a method that was first coupled with AHP by Ishizaka and Siraj et al. (2016). https://doi.org/10.13033/ijahp.v9i1.475 mailto:Alessio.Ishizaka@port.ac.uk https://doi.org/10.13033/ijahp.v9i1.475 IJAHP Essay: Ishizaka/Visual management for decision analysis International Journal of the Analytic Hierarchy Process 142 Vol. 9 Issue 1 2017 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v9i1.475 Figure 1. Graphical scale Figure 2. An example of four possible graphical sensitivity analyses in Expert Choice 2. Graphical Analysis for Interactive Aid (GAIA) The idea of GAIA is to visualise on a plane as much information as possible related to a problem (Mareschal & Brans 1988). For this purpose, we can use the dimensionality reduction technique of the principal component analysis (PCA). The PCA is applied on the local priorities of AHP entered in a matrix. Data are displayed on a plane with the two axes having the maximal and next-to-maximal dispersions https://doi.org/10.13033/ijahp.v9i1.475 IJAHP Essay: Ishizaka/Visual management for decision analysis International Journal of the Analytic Hierarchy Process 143 Vol. 9 Issue 1 2017 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v9i1.475 (Collins, Ishizaka et al. 2017). These two axes correspond to the first two principal components. Figure 3. GAIA plane 3. Interpreting the GAIA plane An illustrative example of a GAIA plane with more than two criteria is given in Figure 4, where the criteria are represented by four vectors (see blue arrows emanating from centre) and the alternatives are represented by dots. The decision stick (labelled as DMG) represents the performance direction taking into account all criteria. The reading is done by projection on the relevant arrow. For example, alternative 3 is the best performing alternative overall, but on criterion 4, alternative 1 is the best. An angle between two vectors represents the degree of correlation between the two criteria, i.e. the smaller the angle between the two arrows, the more correlated they https://doi.org/10.13033/ijahp.v9i1.475 IJAHP Essay: Ishizaka/Visual management for decision analysis International Journal of the Analytic Hierarchy Process 144 Vol. 9 Issue 1 2017 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v9i1.475 are. For example, criterion 1 and 2 are closely correlated, but criterion 3 and 4 have an almost negative correlation. Finally, if alternatives are close, they have a similar level of performance on the different criteria (e.g. alternative 2 and 4). Figure 4. Example of the obtained GAIA graph 4. Conclusion A multi-criteria decision making method can only be helpful if the decision-maker understands the reasons underpinning the prescribed results. Otherwise, she and/or her team will not accept the results, and it will end in unproductive change management resistance. Visual management is a tool that has long been helpful in structuring the problem, eliciting the pairwise comparisons and analyzing the sensitivity of the ranking. This paper presented GAIA, which allows for the whole problem to be visualized on a unique page. In my consulting experience, a picture has always been the best way to explain results. I strongly believe that AHP will become even more popular if it is used in correlation with GAIA. https://doi.org/10.13033/ijahp.v9i1.475 IJAHP Essay: Ishizaka/Visual management for decision analysis International Journal of the Analytic Hierarchy Process 145 Vol. 9 Issue 1 2017 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v9i1.475 REFERENCES Collins, A., A. Ishizaka, et al. (2017). Film production incentives, employment transformation and domestic expenditure in South Africa: visualizing subsidy effectiveness. International Journal of Cultural Policy advance online publications., 1-14. Doi: doi.org/10.1080/10286632.2016.1255206. 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