“Design your own …” is a probably a sentence everyone is familiar with these days. Even for the most basic products, you will be able to find a company that will deliver a fully tailored product to exactly fulfill your needs. Customers are getting more and more demanding and expect companies to comply with their increasing needs. However, customer’s preferences vary wide, which leads to that firms offer an enormous amount of different options when customers want to design their own products. Different solutions have been created to deal with this aspect of user fatigue, as the process of customization takes so much time as the decision making process gets to complex, which lead to not purchasing a product at all.

Next to the fact that customers are getting more demanding, they are also getting more lazy. With the introduction of the Internet, customers expect that everything is handed to them and that they have to provide as less effort as possible, as else they will go to a competitor who will hand it to them. An interesting aspect has been research by Dou and al. due, namely an algorithm to increase the optimization of the customization process to find similar preferences in users.

The purpose of the article of Dou and al. is to incorporate an interactive genetic algorithm to solve the optimization problem of product customization. Interactive genetic algorithms use the human evolution to find the optimization point which fits a particular user preferences. The algorithm proposed in the article is a multi-stage interactive genetic algorithm (MS-IGA), which distinguish itself as it divides the population of the traditional IGA’s into several stages according to functional requirements of a certain product.

The MS-IGA is integrated in the process of designing a car console by a nonprofessional. The different stages the users had to go to were divided into the overall layout, instrument panel, steering wheel etc. There are some striking conclusions that can be established when comparing the MS-IGA to a traditional IGA:

– The algorithm guides users through the whole design process by the means of different stages, whereby the user can evaluate the product-in-process after every stage, compared to other algorithms where the users could only evaluate the end product.

– Due to the test of the car console design, the algorithm proved to be an effective solution for mass customization and production.

This algorithm can be of great value to companies to better serve their demanding customers, as these customers now might quit during the customization process as it takes too long. However, maybe we need to have a critical look at our shopping behavior and the crazy drive to have a product that nobody has. Of course, everyone wants to be unique, but is that really related to how customized your belongings are? I don’t think so.

References

Dou, Runliang, Chao Zong, and Guofang Nan. “Multi-stage interactive genetic algorithm for collaborative product customization.” Knowledge-Based Systems92 (2016): 43-54.

Hildebrand, Christian, Gerald Häubl, and Andreas Herrmann. “Product customization via starting solutions.” Journal of Marketing Research 51.6 (2014): 707-725.