{"id":17393,"date":"2022-11-30T12:50:34","date_gmt":"2022-11-30T17:50:34","guid":{"rendered":"https:\/\/d3.harvard.edu\/platform-digit\/?post_type=hck-submission&#038;p=17393"},"modified":"2022-11-30T12:52:41","modified_gmt":"2022-11-30T17:52:41","slug":"beautytech-loreal-leading-the-way","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/beautytech-loreal-leading-the-way\/","title":{"rendered":"#BeautyTech: L&#8217;Or\u00e9al leading the way"},"content":{"rendered":"\n\n\n<p>During my time as a strategy consultant, I heard the term AI used as a buzzword, the next frontier of business. I worked with executives at big incumbents who knew they had to start integrating AI and machine learning into their business operations. But knowing and doing are two very different things, and I&#8217;ve recognized a pattern in that big firms outside of the tech industry often struggle to understand how AI can be used to improve their business, compete better, and expand their market.<\/p>\n\n\n\n<p>L&#8217;Or\u00e9al is an interesting example of a company that has taken real steps to do just that, so much so that it was featured in the podcast <a href=\"https:\/\/sloanreview.mit.edu\/audio\/inventing-the-beauty-of-the-future-loreals-stephane-lannuzel\/\"><em>Me, Myself and AI<\/em><\/a>, which highlights AI successes to understand why only 10% of companies succeed with AI.<\/p>\n\n\n\n<p>The podcast episode is an interview with Stephane Lannuzel who serves as L&#8217;Or\u00e9al&#8217;s Beauty Tech Program Director. Based on this interview and other research, my understanding is that L&#8217;Or\u00e9al uses AI to create (and capture) value in three key ways: (1) To improve its existing business operations; (2) To expand its portfolio into service offerings; and (3) To instill a tech-savvy culture within the business.<\/p>\n\n\n\n<p><strong>IMPROVING EXISTING BUSINESS OPERATIONS<\/strong><\/p>\n\n\n\n<p>L&#8217;Or\u00e9al is improving its existing operations by integrating AI into the product development cycle and marketing. It has developed algorithms to retool its research and development processes such that it is faster and more efficient. In the same vein as how Moderna uses algorithms to identify protein sequences, L&#8217;Or\u00e9al is using algorithms to predict the performance of ingredients when doing product formulation. This creates value by speeding up the time to market for new products and by improving the quality and efficacy of the product for their customers. This has presented challenges via resistance to change among R&amp;D employees who prefer the old way of doing R&amp;D or are worried about losing their jobs. This is a common challenge when implementing AI and requires education of employees (which is addressed more later in this post).&nbsp;<\/p>\n\n\n\n<p>Second, they have developed an internal tool called TrendSpotter, which detects new beauty trends early across academia, research, and social media. This could include new trending ingredients or new application trends. These insights can feed into the product development cycle to get new products to market which capitalize on these trends. The tool creates value because it is very important to identify trends early since the product development cycle can take up to 12-18 months. The TrendSpotter also helps improve marketing efficacy because L&#8217;Or\u00e9al can leverage its existing product portfolio to target new trends and even be early participants of trends. I would imagine that identifying ingredient trends early would also be a procurement advantage as the company can purchase inputs at lower prices before the trend explodes.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/trendspotter-loreal.png\"><img loading=\"lazy\" decoding=\"async\" width=\"780\" height=\"269\" src=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/trendspotter-loreal.png\" alt=\"\" class=\"wp-image-17420\" srcset=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/trendspotter-loreal.png 780w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/trendspotter-loreal-300x103.png 300w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/trendspotter-loreal-768x265.png 768w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/trendspotter-loreal-600x207.png 600w\" sizes=\"auto, (max-width: 780px) 100vw, 780px\" \/><\/a><figcaption>Trendspotter announcement from L&#8217;Oreal website<\/figcaption><\/figure>\n\n\n\n<p>Third, L&#8217;Or\u00e9al is using machine learning to better understand its customers\u2019 satisfaction with their products. They mine ratings and reviews and apply natural language processing to get a sense of the areas in which they can improve. For example, certain products leak for many customers, they can pinpoint the problem as a packaging issue as the products all share the same packaging.<\/p>\n\n\n\n<p><strong>EXPANDING INTO SERVICE OFFERING<\/strong><\/p>\n\n\n\n<p>While L&#8217;Or\u00e9al has historically been a consumer goods company, they are using AI to develop a services portfolio. This currently consists of two services. The first is a virtual try-on service which allows you to try products on using computer vision and augmented reality. I haven\u2019t tried this service, but I am skeptical of its usefulness. Similar technologies that I\u2019ve tried have not worked well for me. A big reason why is that color matching using computers is difficult as coloration is not always accurately depicted using computers. I suspect that this would be a big challenge for virtual try-ons as the purpose is to see what looks good on you. <\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/loreal-service.png\"><img loading=\"lazy\" decoding=\"async\" width=\"780\" height=\"515\" src=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/loreal-service.png\" alt=\"\" class=\"wp-image-17419\" srcset=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/loreal-service.png 780w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/loreal-service-300x198.png 300w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/loreal-service-768x507.png 768w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/loreal-service-600x396.png 600w\" sizes=\"auto, (max-width: 780px) 100vw, 780px\" \/><\/a><figcaption>Virtual try-on app<\/figcaption><\/figure>\n\n\n\n<p>The second service is a skin diagnostic tool which seeks to increase personalization by suggesting products that work well for the customer\u2019s skin type and problems. They have also announced a product called Perso, which is an at-home tool to assist with this service. This is an interesting concept from L&#8217;Or\u00e9al because it has such a wide portfolio of brands and products. My hope is that these tools will also promote inclusivity, which is a big issue in the beauty industry. By gathering data on more skin types, colors, etc., hopefully they will better serve a wider array of customers.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/loreal-service-2.png\"><img loading=\"lazy\" decoding=\"async\" width=\"741\" height=\"710\" src=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/loreal-service-2.png\" alt=\"\" class=\"wp-image-17423\" srcset=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/loreal-service-2.png 741w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/loreal-service-2-300x287.png 300w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2022\/11\/loreal-service-2-600x575.png 600w\" sizes=\"auto, (max-width: 741px) 100vw, 741px\" \/><\/a><figcaption>Skincare service which identifies products to target particularities of customer&#8217;s skin<\/figcaption><\/figure>\n\n\n\n<p><strong>INSTILLING A TECH-SAVVY CULTURE<\/strong><\/p>\n\n\n\n<p>One of the challenges of implementing AI into a big traditional incumbent is that the existing workforce is not skilled or educated about the benefits and implementation of AI. This creates a cultural problem of resistance, but also means that it is harder to spread knowledge and know-how for how to leverage opportunities for AI implementation. L&#8217;Or\u00e9al is addressing this by developing a tech and data university for employees which spans both technical and managerial curricula. Offering opportunities to upskill serves several purposes. First, it signals to employees the importance of tech and AI in the company\u2019s strategy and future vision. Second, it indicates a desire to invest in employees and bring them along in this vision. This is important for counteracting resistance and driving a cultural change within the organization. Finally, it democratizes AI knowledge within the organization which facilitates that decentralization of the integration process and gives license to individual teams to help drive creative AI-based solutions.<\/p>\n\n\n\n<p>Overall, I\u2019m bullish on L&#8217;Or\u00e9al&#8217;s ability to continue building AI into its business activities to create and capture value. I think they should focus on deepening use of AI for back-end activities more so than for the consumer-facing areas, as the technology is not where it needs to be and there\u2019s a lot of competition in these areas. One other area they need to be cognizant of and actively work to prevent, is bias. Inclusivity is already a hot button topic in beauty and AI has the capacity to exacerbate this. This should be a key priority for L&#8217;Or\u00e9al.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>L&#8217;Or\u00e9al is successfully integrating AI, a challenging feat for a large incumbent outside of the tech industry<\/p>\n","protected":false},"author":19360,"featured_media":17430,"comment_status":"open","ping_status":"closed","template":"","categories":[],"class_list":["post-17393","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/machine-learning-3\/","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>#BeautyTech: L&#039;Or\u00e9al leading the way - Digital Innovation and Transformation<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-digit\/submission\/beautytech-loreal-leading-the-way\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"#BeautyTech: L&#039;Or\u00e9al leading the way - 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