Summary:<\/em><\/strong> \u00a0McKinsey says platform companies will represent 30% of global business revenue by next year (2020).\u00a0 Here are some lessons and examples to help mature companies evaluate where they can create AI\/ML-enabled platforms to remain competitive.\u00a0 This is a long topic so this will be Part 1 of 2.<\/em><\/p>\n \u00a0 As data scientists increasingly become critical resources in enabling companies\u2019 exploration and exploitation of their digital resources, it\u2019s also increasingly important that data scientists can provide accurate and focused business guidance.\u00a0 If that seems like a mouthful, try these two scenarios.<\/p>\n Scenario 1:<\/strong> Joe is asked to recommend a portfolio of AI\/ML projects that will improve performance, provide measurable ROI, and have relatively low risk of failure.<\/p>\n Scenario 2:<\/strong> Joan is asked to plan AI\/ML projects that will maximize the value of the company, protect against competitors, and create the fastest possible market, revenue, and margin growth.<\/p>\n Pretty much any of us could do a competent job with the first scenario.\u00a0 We\u2019d look at the current business and try to find opportunities where traditional ML could be used like scoring, forecasting, or optimization.\u00a0 If we\u2019re sufficiently advanced we\u2019d also look for AI opportunities like the application of NLP or image processing.\u00a0 Since we weren\u2019t asked to challenge the fundamental business model, we just looked to places where we could paste on AI\/ML.\u00a0<\/p>\n In our previous article we called this \u201cAI-Inside\u201d or \u201cApplied AI\u201d<\/u><\/em><\/a>.\u00a0 It\u2019s not necessarily bad to do this.\u00a0 It\u2019s walk-before-you-run; get some experience; earn some buy-in.\u00a0 What it\u2019s not in any sense of the word is transformational.<\/p>\n Scenario 2 invites Joan to look deep for opportunities to really change the business with AI\/ML.\u00a0 As we identified in our last article, this transformational strategy is increasingly called \u2018Platform Strategy\u2019<\/u><\/em><\/a>,<\/u><\/em> or \u2018Platformication\u2019.<\/p>\n Here\u2019s the kicker.\u00a0 McKinsey says that by 2020 (next year!) platform businesses will account for 30% of global business revenues<\/strong>.\u00a0 So if you\u2019re just now finding out about platform strategy, you and your company are about to see the backsides of many of your competitors as they rush ahead to take your customers and disrupt your markets.\u00a0 It\u2019s no exaggeration to say that platform strategy represents the basis for the next industrial revolution in worldwide business.<\/p>\n So the first part of this lesson is this:\u00a0 if you\u2019re asked to help your company define its \u2018digital journey\u2019 because your CXO read an article that said you have to get value from your data, don\u2019t generalize.\u00a0 Be prepared to engage in a conversation about whether this is incremental change or whether AI\/ML can create really wide-moat transformational change.<\/p>\n<\/p>\n Platform Strategy<\/strong><\/span><\/p>\n We devoted the last article to providing a definition of Platformication and some structure around how to think about it.\u00a0 If you haven\u2019t read that, start there first<\/u><\/em><\/a>.<\/p>\n No Agreed Path to Platformication<\/strong><\/span><\/p>\n We\u2019ve grown comfortable and familiar with the famous tech names in Platformication that started out with this strategy as a goal.\u00a0 Amazon, eBay, Etsy, Airbnb, Uber, OpenTable, Travelocity all set out to create businesses in which they owned none of the delivery resources, had no inventory, and had only the goal of creating large ecosystems of buyers and sellers.\u00a0 As they say, these now-giants weren\u2019t encumbered by their own prior success.<\/p>\n What\u2019s important to our exploration here is how mature companies can identify platform opportunities<\/strong> and how those can be implemented alongside their existing business models or even completely replace them.\u00a0 We\u2019ll start with some lessons learned and guidelines and then illustrate them with company examples.<\/p>\n<\/p>\n Lessons, Guidelines, Examples<\/strong><\/span><\/p>\n MassMutual Insurance<\/em><\/strong><\/p>\n MassMutual has embraced several flavors of platform.\u00a0 Its RetireSMART platform is an interactive content site where individuals planning for retirement can view quality content as well as several financial forecasting tools designed to show readiness for retirement.<\/p>\n MassMutual partnered with Envestnet – Yodlee data aggregation platform to bring together client assets from other financial firms including 401Ks that may still be housed at prior employers.<\/p>\n One lesson is that it\u2019s not necessary to build all the features of the platform yourself and partnering may be an option as it was here.<\/p>\n \u00a0<\/p>\n Other insurance companies are increasingly willing to cross-sell competitors\u2019 products to maintain and consolidate their client relationships.\u00a0 The traditional insurance business is an inefficient pipeline style model relying on carriers, distributors, and agents.<\/p>\n Where information is fragmented, that is sellers know a lot more than buyers, platforms aggregate the supply side adding transparency and the ability to compare offers making the consumer\u2019s experience nearly frictionless.<\/p>\n Carriers, distributors and agents benefit from a low cost solution to support the consumer and gain substantially in their ability to analyze the resulting data from interactions to better design products and target appropriate audiences.<\/p>\n Westlaw Edge<\/em><\/strong><\/p>\n Here\u2019s a slightly different platform model.\u00a0 Westlaw had long sold legal research information to the highly fragmented law office market.\u00a0 Their platform strategy however is to provide that information on a subscription basis enhanced by AI search capability.<\/p>\n The network benefit is to relieve lawyers of the tedious work of establishing citations in support of their cases.\u00a0 The super-benefit of using AI\/ML enabled search is to alert the attorney for law that has been indirectly overturned and even alert for \u201cOverruling Risk,\u201d meaning the case has likely been implicitly overturned by another case.\u00a0 The software can accurately tag implicitly overturned cases 80 to 85% of the time.<\/p>\n \u00a0<\/p>\n La Ruche Qui Dit Oui<\/em><\/strong><\/p>\n This French startup seeks to become the platform between local food producers (those most likely to participate in farmers markets) and consumers who want quality and freshness, and also want to support local farm-to-table culture.<\/p>\n The name translates rather inelegantly in English to roughly \u2018the beehive that says yes\u2019, or perhaps more accurately many small buyers and sellers coming together to make this transaction easy.\u00a0 Essentially they have added a layer of ecommerce to farmers markets allowing:<\/p>\n On the supply side they promise:<\/p>\n InsureMyTrip, Squaremouth, TravelInsurance.com<\/em><\/strong><\/p>\n These are all platforms that have emerged recently and are in head-to-head competition around the highly fragmented travel insurance business.\u00a0 These are fairly complex policies purchased by vacationers who want to protect their investment from unforeseen interruption.\u00a0 However, the differences among different policies (if it\u2019s not written it\u2019s not covered) and the fragmentation among relatively small providers results in a classic imbalance of knowledge between buyers and sellers.<\/p>\n Two lessons here:<\/strong><\/p>\n \u00a0<\/p>\n This is a long topic with many lessons and examples.\u00a0 To keep this readable we\u2019ll split this into two parts.\u00a0 Be sure to see the balance in our next article:<\/p>\n AI\/ML Lessons for Creating a Platform Strategy \u2013 Part 2<\/strong><\/p>\n \u00a0<\/p>\n \u00a0<\/p>\n Other articles on AI Strategy<\/strong><\/p>\n A Radical AI Strategy – Platformication<\/u><\/em><\/a><\/p>\n Now that We\u2019ve Got AI What do We do with It?<\/u><\/em><\/a><\/p>\n Capturing the Value of ML\/AI \u2013 the Challenge of Offensive versus Defensive Data Strategies<\/u><\/em><\/a><\/p>\n The Case for Just Getting Your Feet Wet with AI<\/u><\/em><\/a><\/p>\n The Fourth Way to Practice Data Science \u2013 Purpose Built Analytic Modules<\/u><\/em><\/a><\/p>\n From Strategy to Implementation \u2013 Planning an AI-First Company<\/u><\/em><\/a><\/p>\n Comparing the Four Major AI Strategies<\/u><\/em><\/a><\/p>\n Comparing AI Strategies \u2013 Systems of Intelligence<\/u><\/em><\/a><\/p>\n Comparing AI Strategies \u2013 Vertical versus Horizontal.<\/u><\/em><\/a><\/p>\n What Makes a Successful AI Company<\/u><\/em><\/a> \u2013 Data Dominance<\/u><\/em><\/span><\/p>\n AI Strategies \u2013 Incremental and Fundamental Improvements<\/u><\/em><\/a><\/p>\n \u00a0<\/p>\n Other articles by Bill Vorhies<\/u><\/em><\/a><\/p>\n \u00a0<\/p>\n About the author:\u00a0 Bill is Contributing Editor for Data Science Central.\u00a0 Bill is also President & Chief Data Scientist at Data-Magnum and has practiced as a data scientist since 2001.\u00a0\u00a0\u00a0 He can be reached at:<\/p>\n Bill@DataScienceCentral.com<\/a> or<\/span> Bill@Data-Magnum.com<\/a><\/p>\n<\/div>\n Go to Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" Author: William Vorhies Summary: \u00a0McKinsey says platform companies will represent 30% of global business revenue by next year (2020).\u00a0 Here are some lessons and examples […] Read More<\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":463,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[26],"tags":[],"_links":{"self":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts\/1988"}],"collection":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/comments?post=1988"}],"version-history":[{"count":0,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts\/1988\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media\/457"}],"wp:attachment":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media?parent=1988"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/categories?post=1988"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/tags?post=1988"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}<\/a><\/p>\n
<\/a>Here are some bullet points to get you back into thinking about this:<\/p>\n
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<\/a>Other Insurance Companies, Distributors, and Agents<\/em><\/strong><\/p>\n
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