{"id":27318,"date":"2018-11-06T07:37:37","date_gmt":"2018-11-06T12:37:37","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/how-coca-cola-is-leveraging-machine-learning-in-the-hyper-competitive-cpg-industry\/"},"modified":"2018-11-06T07:41:05","modified_gmt":"2018-11-06T12:41:05","slug":"how-coca-cola-is-leveraging-machine-learning-in-the-hyper-competitive-cpg-industry","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/how-coca-cola-is-leveraging-machine-learning-in-the-hyper-competitive-cpg-industry\/","title":{"rendered":"How Coca Cola is Leveraging Machine Learning in the Hyper-competitive CPG Industry"},"content":{"rendered":"

Major shifts are occurring in the food & beverage industry as consumers look beyond legacy CPG brands and towards new, interesting, and perceived healthier alternatives1<\/sup>. As these customer desires continue to intensify, it is critically important for the larger companies to drill-down their focus to the consumer level. Coca Cola is embodying this strategy by utilizing machine learning to personalize its product development and enhance its placement and delivery. It is drastically important for Coca Cola to leverage its power of scale through substantial investments in this megatrend so that it can thrive in the new era of the food and beverage industry.<\/p>\n

In the short term, Coca Cola is leveraging machine learning heavily in its product development. One example is the launch of Cherry Sprite2<\/sup>. The company first debuted its interactive soda fountain dispensaries in 2009 where restaurant and retail guests could add a splash of different flavors to their favorite Coca Cola drinks3<\/sup>. The company cleverly collected the data of the vast flavor combinations and leveraged machine learning to identify the most popular versions. Using the analysis, Coca Cola was able to identify a large market for Cherry Sprite and launched the product nationally. Leveraging machine learning, the company was able to bring product development to the consumer level and make decisions based on their individual preferences.<\/p>\n

In addition to product development, Coca Cola is also utilizing machine learning in the short term for product delivery. Specifically, it is upgrading consumer interaction with its vending machines4<\/sup>. The company is doing so by finding new patterns in foot traffic and demand to best locate its machines for maximum utility. On top of that, it is also fine tuning each unit. Utilizing machine learning to analyze purchasing behavior and customer data, the vending machines will be able promote appropriate products for that area and offer discounts related to that specific unit. Additionally, the machine will also be able to adjust its \u201cmood\u201d to the setting (e.g., promoting more water if it is in a gym). By leveraging this technology, Coca Cola is further enhancing the personalization of its product placement.<\/p>\n

Long term, Coca Cola is looking to use machine learning to improve its placement in brick-and-mortar retail5<\/sup>. The company historically managed a very labor-intensive process for its store-level audits; the procedure used to both understand how its goods are placed on the shelf next to competitors and determine any out-of-stock items that needed to be replenished. To avoid the tedious and costly process, Coca Cola invested in a machine learning technology to analyze images of shelves taken via a mobile phone. By leveraging this new technology, the company could conduct corporate-level marketplace surveys six times a year instead of twice. Looking forward, this machine learning mechanism will only prove more important as competition on the shelf becomes even more fragmented. Coca Cola must be able to react to developments rapidly and this technology will enable the company to be nimbler and better equipped to fend off its competition.<\/p>\n

Although Coca Cola has made great strides at leveraging machine learning in several areas so far, there is still more to do to ensure it is maximizing its opportunity. In the short term, the company must continue to focus on product development at the consumer-level. Although Coca Cola has done so in terms of new flavor combinations for existing products, the company should also think beyond line extensions and leverage the machine learning data to also develop new and innovative brands. By doing so, Coca Cola will be better able to compete with new entrants to the food & beverage market that are currently winning by delivering new solutions.<\/p>\n

Over the longer term, Coca Cola should continue to streamline its supply chain. The company has made great strides at developing a more cost-effective manner to evaluate its distribution channel. It should now leverage that process and incorporate machine learning further upstream. Specifically, the company should use its learnings at the store level to better manage its production scheduling and raw material purchases. By doing so, it can increase its profitability and drive value to the P&L not only via top-line improvements but also deductions in cost of goods sold. Additionally, by better managing its inventory, Coca Cola will be in a better cash flow position and will have more capital available to invest back into its machine learning project.<\/p>\n

Coca Cola has made great progress in utilizing machine learning to personalize its product development and enhance its product placement. However, the food & beverage industry is becoming increasingly competitive each day. With competition rising and industry margins already slim, will Coca Cola continue to allocate adequate investment dollars into machine learning for the long-term?<\/p>\n

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Sources:<\/strong><\/p>\n

1\u00a0\u00a0\u00a0 <\/sup>Back, Aaron. \u201cFood Companies Can’t Figure Out What Americans Want to Eat.\u201d\u00a0The Wall Street Journal<\/em>, Dow Jones & Company, 5 June 2018, www.wsj.com\/articles\/food-companies-cant-figure-out-what-americans-want-to-eat-1528200000<\/a>.<\/p>\n

2\u00a0\u00a0\u00a0 <\/sup>Marr, Bernard. \u201cThe Amazing Ways Coca Cola Uses Artificial Intelligence And Big Data To Drive Success.\u201d\u00a0Forbes<\/em>, 18 Sept. 2017, www.forbes.com\/sites\/bernardmarr\/2017\/09\/18\/the-amazing-ways-coca-cola-uses-artificial-intelligence-ai-and-big-data-to-drive-success\/#4e8cd56078d2<\/a>.<\/p>\n

3\u00a0\u00a0\u00a0 <\/sup>Moye, Jay. \u201cSprite Cherry and Sprite Cherry Zero Are First National Brands Inspired by Coca-Cola Freestyle.\u201d\u00a0The Coca-Cola Company<\/em>, 13 Feb. 2017, www.coca-colacompany.com\/stories\/fountain-favorites-sprite-cherry-and-sprite-cherry-zero-become-first-national-brands-inspired-by-coca-cola-freestyle<\/a>.<\/p>\n

4\u00a0\u00a0\u00a0 <\/sup>\u201cCoca-Cola Is Using AI to Put Some Fizz in Its Vending Machines.\u201d\u00a0Digital Food & Beverage 2019<\/em>, WBR Insights, foodandbeverage.wbresearch.com\/coca-cola-artificial-intelligence-ai-omnichannel-strategy-ty-u.<\/p>\n

5\u00a0\u00a0\u00a0 <\/sup>Cheng, Andria. \u201cCPG Brands Are Leveling The Playing Field By Bringing This Digital Tool Into Brick-And-Mortar Retail.\u201d\u00a0Forbes<\/em>, 31 May 2018, www.forbes.com\/sites\/andriacheng\/2018\/05\/31\/one-new-area-cpg-brands-are-leveling-the-playing-field-against-online-retailers\/#79293b543abb<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

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