{"id":454,"date":"2017-04-13T18:16:45","date_gmt":"2017-04-13T18:16:45","guid":{"rendered":"https:\/\/www.ashwinl.com\/ideas\/ex-991\/"},"modified":"2017-04-13T18:16:45","modified_gmt":"2017-04-13T18:16:45","slug":"ex-991","status":"publish","type":"post","link":"https:\/\/www.ashwinl.com\/ideas\/ex-991\/","title":{"rendered":"EX-99.1"},"content":{"rendered":"<p><a href='https:\/\/www.sec.gov\/Archives\/edgar\/data\/1018724\/000119312517120198\/d373368dex991.htm'>EX-99.1<\/a><\/p>\n<div class=\"link_description\">\n<p><b>True Customer Obsession <\/b><\/p>\n<p>There are many ways to center a business. You can be competitor focused, you can be product focused, you can be technology focused, you can be business model focused, and there are more. But in my view, obsessive customer focus is by far the most protective of Day 1 vitality. <\/p>\n<p>Why? There are many advantages to a customer-centric approach, but here\u2019s the big one: customers are <i>always<\/i> beautifully, wonderfully dissatisfied, even when they report being happy and business is great. Even when they don\u2019t yet know it, customers want something better, and your desire to delight customers will drive you to invent on their behalf. No customer ever asked Amazon to create the Prime membership program, but it sure turns out they wanted it, and I could give you many such examples. <\/p>\n<p>Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight. A customer-obsessed culture best creates the conditions where all of that can happen. <\/p>\n<p><b>Resist Proxies <\/b><\/p>\n<p>As companies get larger and more complex, there\u2019s a tendency to manage to proxies. This comes in many shapes and sizes, and it\u2019s dangerous, subtle, and very Day 2. <\/p>\n<p>A common example is process as proxy. Good process serves you so you can serve customers. But if you\u2019re not watchful, the process can become the thing. This can happen very easily in large organizations. The process becomes the proxy for the result you want. You stop looking at outcomes and just make sure you\u2019re doing the process right. Gulp. It\u2019s not that rare to hear a junior leader defend a bad outcome with something like, \u201cWell, we followed the process.\u201d A more experienced leader will use it as an opportunity to investigate and improve the process. The process is not the thing. It\u2019s always worth asking, do we own the process or does the process own us? In a Day 2 company, you might find it\u2019s the second. <\/p>\n<p>Another example: market research and customer surveys can become proxies for customers \u2013 something that\u2019s especially dangerous when you\u2019re inventing and designing products. \u201cFifty-five percent of beta testers report being satisfied with this feature. That is up from 47% in the first survey.\u201d That\u2019s hard to interpret and could unintentionally mislead. <\/p>\n<p>Good inventors and designers <i>deeply<\/i> understand their customer. They spend tremendous energy developing that intuition. They study and understand many anecdotes rather than only the averages you\u2019ll find on surveys. They <i>live<\/i> with the design. <\/p>\n<p>I\u2019m not against beta testing or surveys. But you, the product or service owner, must understand the customer, have a vision, and love the offering. Then, beta testing and research can help you find your blind spots. A remarkable customer experience starts with heart, intuition, curiosity, play, guts, taste. You won\u2019t find any of it in a survey. <\/p>\n<p><b>Embrace External Trends <\/b><\/p>\n<p>The outside world can push you into Day 2 if you won\u2019t or can\u2019t embrace powerful trends quickly. If you fight them, you\u2019re probably fighting the future. Embrace them and you have a tailwind. <\/p>\n<p>These big trends are not that hard to spot (they get talked and written about a lot), but they can be strangely hard for large organizations to embrace. We\u2019re in the middle of an obvious one right now: machine learning and artificial intelligence.<\/p>\n<p>Over the past decades computers have broadly automated tasks that programmers could describe with clear rules and algorithms. Modern machine learning techniques now allow us to do the same for tasks where describing the precise rules is much harder. <\/p>\n<p>At Amazon, we\u2019ve been engaged in the practical application of machine learning for many years now. Some of this work is highly visible: our autonomous Prime Air delivery drones; the Amazon Go convenience store that uses machine vision to eliminate checkout lines; and Alexa,<sup>1<\/sup> our cloud-based AI assistant. (We still struggle to keep Echo in stock, despite our best efforts. A high-quality problem, but a problem. We\u2019re working on it.) <\/p>\n<p>But much of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type \u2013 quietly but meaningfully improving core operations. <\/p>\n<p>Inside AWS, we\u2019re excited to lower the costs and barriers to machine learning and AI so organizations of all sizes can take advantage of these advanced techniques. <\/p>\n<p>Using our pre-packaged versions of popular deep learning frameworks running on P2 compute instances (optimized for this workload), customers are already developing powerful systems ranging everywhere from early disease detection to increasing crop yields. And we\u2019ve also made Amazon\u2019s higher level services available in a convenient form. Amazon Lex (what\u2019s inside Alexa), Amazon Polly, and Amazon Rekognition remove the heavy lifting from natural language understanding, speech generation, and image analysis. They can be accessed with simple API calls \u2013 no machine learning expertise required. Watch this space. Much more to come. <\/p>\n<p><b>High-Velocity Decision Making <\/b><\/p>\n<p>Day 2 companies make high-<i>quality<\/i> decisions, but they make high-quality decisions <i>slowly<\/i>. To keep the energy and dynamism of Day 1, you have to somehow make high-quality, <i>high-velocity<\/i> decisions. Easy for start-ups and very challenging for large organizations. The senior team at Amazon is determined to keep our decision-making velocity high. Speed matters in business \u2013 plus a high-velocity decision making environment is more fun too. We don\u2019t know all the answers, but here are some thoughts. <\/p>\n<p>First, never use a one-size-fits-all decision-making process. Many decisions are reversible, two-way doors. Those decisions can use a light-weight process. For those, so what if you\u2019re wrong? I wrote about this in more detail in last year\u2019s letter.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>EX-99.1 True Customer Obsession There are many ways to center a business. You can be competitor focused, you can be product focused, you can be technology focused, you can be business model focused, and there are more. But in my view, obsessive customer focus is by far the most protective of Day 1 vitality. Why? 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