# Smart Product Design Process through the Implementation of a Fuzzy Kano-AHP-DEMATEL-QFD Approach
## 6 Discussion  
Initially, the strength of the proposed approach could be evidenced when a better understanding of customer needs and expectations is required. To reach this goal, the proposed approach used the integration of AHP and a fuzzy Kano model. The results derived from this hybrid method could be seen in Figure 13.  
From this picture, it could be concluded that the results obtained with AHP and Kano were not the same. In this sense, AHP required the customer to perform pairwise comparisons, whereas Kano let the customer free to voice his preference without any restriction. Both scenarios were necessary to understand customer thinking and desires, considering that this adequate understanding would affect how the design actions/characteristics are going to be prioritized. In Figure 13, it could be observed that in AHP and Kano, the preferences were similar but not equal, and the differences were more evident on the importance given to the following customer needs: reliability, less invasive, collateral issues, and communication. Additionally, for AHP, the most important customer needs were collateral issues and accuracy. On the other hand, Kano ranked trustable data and reliability as the most important customer needs. These results evidenced how customer preferences might vary depending on the scenario they are placed in.  
On the other hand, once the design characteristics/actions options were defined, it was necessary to detect how much each one of these impacts on the others; this is very important, considering that one action may potentiate others. That is very important when implementing these characteristics or actions, especially when implementation would be one after the other or when not all of them would be implemented. In this case, it was important to pick in the first place the code change, considering that was a very strong deliverer and had the strongest overall influence (\(D+R\)). The graphic containing the values of \(D+R\) and \(D-R\) could be found in Figure 14.  
The aforementioned results allowed the company to identify that \"code change\" is the design action that mostly impacts customer satisfaction while entailing low investment. On the other hand, other actions, such as \"triple integration\" and \"battery time\", required an additional cost and did not impact clients significantly. In this case, the initial perception was that design actions, such as battery type and 3I, were the more relevant ones. Nevertheless, the proposed QFD process showed that the company should firstly focus on actions like code change that could impact customer satisfaction in a better way. This process could help the company to make better decisions relating to product improvement and development.  
Figure 13: Criteria weights derived from AHP-KANO integration.  
Figure 15 describes how the impact on satisfaction decreased below 1 from installation hardware, and it continued dropping until it became almost zero. This was an important finding because the company now knows that those last four design features do not contribute to customer satisfaction. Now they could focus their attention and effort on implementing actions that would have a relevant impact on customer satisfaction.  
Additionally, the company could now use the cost of each action and relate it to its satisfaction impact. With this information and calculating the money needed to implement each characteristic or action, the company could estimate how much money is needed to invest to increase in one point the customer satisfaction in each design characteristic and maybe compare future actions, to implement actions only if, for example, this relation is greater than a threshold value (dollars/ISDA). This could encourage the design team to work with a target of the impact their actions should have if they imply some money investment.