{"id":10091,"date":"2019-12-04T07:06:18","date_gmt":"2019-12-04T12:06:18","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-digit\/submission\/symrise-and-ibm-new-fragrances-created-by-ai\/"},"modified":"2019-12-04T07:06:18","modified_gmt":"2019-12-04T12:06:18","slug":"symrise-and-ibm-new-fragrances-created-by-ai","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/symrise-and-ibm-new-fragrances-created-by-ai\/","title":{"rendered":"Symrise and IBM: New Fragrances Created by AI"},"content":{"rendered":"

Headquartered in Germany, Symrise AG is a leading producer of fragrances and flavors with \u20ac 3.2 billion in revenues in 2018 [1]. 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\u2019s additives are responsible for such a wide range of product characteristics\u2014freshness in toothpaste, the special scent of perfumes, etc.\u2014that the average consumer interacts with the company\u2019s products up to 20\u201330 times a day [2].<\/p>\n

The process of inventing new scents is the core of the company\u2019s 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 [3].<\/p>\n

Philyra uses advanced machine learning algorithms to create new and innovative fragrances [4].<\/em><\/strong><\/p>\n

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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 [5]. 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\u2014which was the first product actually introduced for the cosmetics company O Botic\u00e1rio, the second-largest beauty chain in Brazil [3]. One of the two versions smells like \u201cfenugreek seeds, green cardamom pods, carrot seed, all wrapped with a milky, buttery, rich base note\u201d and the other \u201cis a fruity, floral scent\u2014seemingly aimed at girls\u2014and has scents of Osmanthus tea with lychee and patchouli\u201d [3]. Both have received extremely positive reviews.<\/p>\n