Headquartered in Germany, Symrise AG is a leading producer of fragrances and flavors with € 3.2 billion in revenues in 2018 . The company designs and produces aromatic ingredients for perfumes, personal care and household products, as well as food and beverages. Very often, these flavors determine if the consumer subconsciously likes or dislikes a product. Symrise’s additives are responsible for such a wide range of product characteristics—freshness in toothpaste, the special scent of perfumes, etc.—that the average consumer interacts with the company’s products up to 20–30 times a day .
The process of inventing new scents is the core of the company’s business model. To stay competitive, Symrise needs to be at the forefront of product innovation while frequently introducing new products to the market. This innovative capability is what differentiates the company from its competitors, especially in its fragrance business. However, crafting new scents combines art and science and is, as such, a process difficult to fully control and predict. Therefore, Symrise is looking to push the boundaries in its invention process. The company recently tested artificial intelligence (AI) software called Philyra developed in cooperation with IBM .
Philyra uses advanced machine learning algorithms to create new and innovative fragrances .
Even after years of experience and training, skilled perfumers are largely dependent on trial and error to find new promising combinations of ingredients. This could soon change. The software Philyra uses machine learning algorithms to scan through thousands of raw materials to identify novel combinations of fragrance raw materials and to autonomously design new formulas. The algorithm is trained with 1,300 fragrance raw materials (synthetics and natural extracts), historic formulas (Symrise contributed a database with 1.7 million tested combinations), and information as to which formulas were previously successful . By adding information about specific target customer groups, preferences, and sales data, the software can even suggest a formulation that had not been tried before and is, for example, particularly likely to be successful among Brazilian millennials—which was the first product actually introduced for the cosmetics company O Boticário, the second-largest beauty chain in Brazil . One of the two versions smells like “fenugreek seeds, green cardamom pods, carrot seed, all wrapped with a milky, buttery, rich base note” and the other “is a fruity, floral scent—seemingly aimed at girls—and has scents of Osmanthus tea with lychee and patchouli” . Both have received extremely positive reviews.
It turns out that the algorithm is particularly helpful when it comes to combinations that seem unlikely to harmonize . In contrast to human beings, the Philyra software is not biased due to the complete absence of any predisposition to the world of smells and fragrances. Only after Philyra comes up with a novelty, an experienced perfumer fine-tunes the product and emphasizes certain features to give the fragrance a unique character. This approach offers the advantage of letting the highly trained (and well-paid) perfumer concentrate on the art piece of the innovation process without spending time on the combinatory exercise.
However, this collaboration between man and machine also creates challenges. Every perfumer has a certain style, prefers certain raw materials with which they are experienced, and often wants to create a perfume that will be recognized as their composition—like a cook who has a personal note. The Philyra program requires the perfumer, who tends to be a strong personality, to radically change their methods, which could lead to some frustration and objection. Symrise has tried to mitigate these challenges by publicly emphasizing that the software will never replace perfumers but is supposed to support them and allow them to be even more creative . This assurance also seems important in making sure that the association of fragrances with craftmanship, arts, and creativity does not vanish in the eyes of the consumer, as this could over time push down consumers’ willingness to pay.
It seems likely that solutions such as Philyra will become standard tools in the development process of new fragrances. As the competitive advantage of Symrise will depend more and more on data analysis and machine learning, the company will have to increasingly hire expertise and insource data capabilities. With its vast database of fragrances, the company is uniquely positioned to develop proprietary software that will help it to secure a competitive advantage. Collaboration between data scientists and perfumers seems only to be a continuation of the art and science that have produced fragrances from time immemorial. While the collaboration with IBM was used to gain publicity, future generations of AI software will be employed behind the curtain to protect the magic that surrounds our favorite perfumes.