Bridgette Claire Brodnyan
Consumer motivation trends in the beauty industry are shifting, and more than ever personalization is the key to modern day customer loyalty. Despite the millions of products on the market, the beauty industry overall has an utter lack of personalization, but artificial intelligence just might be able to change that. Companies are now starting to embrace the uniqueness of each customer, and creating personalized products designed specifically for the individual consumer. New technologies, such as machine learning and artificial intelligence, increase the level of personalization companies can achieve.
Earlier this month, the French cosmetics group L’Oréal announced its acquisition of the Canadian beauty tech company ModiFace. ModiFace is one of the biggest names in BeautyTech today, and has developed over 200 beauty apps for more than 80 brands. Such apps include cosmetics tryout apps and chatbots for Estee Lauder Cos., Smashbox, Allergan, and Coty; Clairol’s 3D hair color simulator; and Sephora’s ColorIQ and upcoming LipIQ technology. This acquisition will allow for L’Oréal to produce more digital services, such as tools to allow customers to test out various beauty products virtually, through augmented reality and artificial intelligence. More specifically, the company is looking to produce an app that would access the user’s camera, so they could try out makeup virtually and in real time. Throughout its existence,L’Oréal has acquired many cosmetics companies, but this would be the first tech company it has taken over. This type of acquisition from such a large player in the beauty industry has the potential to spark the digital acceleration of the industry as a whole.
A question I have is, in what other ways could technology be useful for the cosmetics industry? Is this the extent of it, or do machine learning and artificial intelligence technologies have the ability to truly transform the beauty industry?
Disruptive innovation refers to a new idea or product that drastically changes the way things were previously done. This is something that is very common in many industries, but is much needed within the education industry. Clayton Christensen’s Disrupting Class: How Disruptive Innovation Will Change the Way the World Learns, highlights the difficulties with innovation in education, and how computers and technology could be just the type of digital innovation needed within the educational system. This topic was particularly interesting for me, because I have been working for a company in the EdTech industry for the past year, who’s goal is to enhance the value of K-12 education through the use of innovative technology. One of the main ways personal technology can create disruptive innovation is through its ability to provide for a more individualized education for students. Often times the education system generalizes lesson plans due to a lack of resources or finances, and students who do not learn in the traditional way are the ones who suffer. Online learning presents and alternative solution to this problem, and can allow for the development of child-specific lesson plans. Such a level of individualized instruction would be impossible in the traditional classroom setting. Students with any learning style preferences can benefit from this type of disruptive innovation in the education system, by being presented with the opportunity to take additional classes not offered in the traditional classroom, work at his or her own pace, and focus on what learning styles work best for him/her individually. A question I have is, other than the obvious costs, what other factors are limiting disruptive innovation in education? In what other ways can personal technology create disruptive innovation in education?
Health practitioners’ capacity to understand and think through complex challenges can be enhanced through the use of systems thinking tools. Utilizing systems thinking tools such as BOT or Behavior Over Time graphs along with data from other systems across the healthcare industry can aid in the overall improvement of public health. These tools allow for health practitioners to not only analyze trends, but also analyze the events and systematic forces that play into the development of such trends. Additionally, systems thinking in this way creates the opportunity for health practitioners to discuss freely and creatively, therefore providing a more holistic, deeper understanding of trends in public health. BOT graphs are also useful tools in advancing the systems-level thinking in public health. Studies show systems thinking in public health also increases the engagement of stakeholders surrounding these issues. In my opinion, by applying system thinking, health practitioners can enhance their ability to analyze trends in public health and allow for a heightened sense of creativity surrounding their proposed solutions to these trends. A question I would like to pose is: in addition to BOT graphs and analysis, how else could systems thinking be useful in public health? Is it purely advantageous in an analytical sense, or are there other benefits to systems thinking in public health?