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Below, Jon McNeill shares five key insights from his new book, The Algorithm: The Hypergrowth Formula That Transformed Tesla, Lululemon, General Motors, and SpaceX<\/em>.<\/p>\n McNeill is a serial entrepreneur and business leader. He was president of Tesla during a period of rapid growth, later helped take Lyft public, and today works with leadership teams as a board member at companies like General Motors and Lululemon and as the CEO of his venture fund, DVx Ventures.<\/p>\n What if the biggest obstacle to growth isn\u2019t what you\u2019re missing, but everything you\u2019ve added? The fastest teams win by questioning, cutting, and simplifying far more than anyone else.<\/p>\n Listen to the audio version of this Book Bite\u2014read by McNeill himself\u2014in the Next Big Idea app<\/a>, or\u00a0buy the book<\/a>.<\/em><\/p>\n Organizations don\u2019t slow down because people are lazy or untalented. They slow down because they are surrounded by invisible rules. Rules that once made sense. Rules no one remembers creating. Rules that quietly become handcuffs.<\/p>\n One of the most powerful habits is treating every requirement as guilty until proven innocent. When someone says, \u201cWe have to do it this way,\u201d the real question is: Why?<\/em> Is it a law? Is it physics? Or is it just how we\u2019ve always done things?<\/p>\n One of the clearest examples is about Tesla in China. There was a long-standing norm that foreign automakers could not fully own their businesses in China. It was treated as a hard rule, but we found a way for the Chinese officials to make an exception. After sustained negotiations over 14 months, Tesla secured the go-ahead for the first 100% foreign-owned auto business in China, retaining financial ownership even while the land remained formally owned under China\u2019s system. That did not happen by accepting the requirement. It happened by interrogating it.<\/p>\n When organizations want to move faster, their instinct is almost always to add another tool, another layer, another approval, another meeting. But speed rarely comes from addition. Speed comes from subtraction.<\/p>\n Take Tesla\u2019s push to reduce friction in buying a car online. The experience was painfully complex. It took 64 clicks to complete the purchase journey. Elon Musk set a stretch goal to get it down to 10 clicks. The work started by deleting steps customers did not value and then attacking the biggest sinkhole\u2014financing paperwork. The team asked which documents were truly required by law versus simply inherited by the banks and lawyers we had worked with. That led to a potential breakthrough the industry had not even considered: a one-click loan or lease document, pursued directly with banks.<\/p>\n \u201cIf a step disappeared tomorrow, would the customer notice?\u201d<\/p>\n<\/blockquote>\n Deletion also showed up earlier in that same flow. Tesla realized customers were drowning in choices, with hundreds of thousands of potential combinations. That complexity created more clicks, slowed conversion, and complicated manufacturing and supply chain. So, the team simplified everything, eliminating countless combinations and pushing customers toward core packages aligned with what they wanted.<\/p>\n Ask yourself, if a step disappeared tomorrow, would the customer notice? If the answer is no, you could probably delete it.<\/p>\n A lot of work inside most organizations exists simply to support other work. Reports created so other reports can be written. Meetings held to prepare for meetings. Complexity that is managed by roles that should not exist because the complexity should not exist.<\/p>\n When you delete aggressively, clarity emerges, decision-making speeds up, and ownership sharpens. There\u2019s simply less drag.<\/p>\n If the process is hard to explain, it\u2019s too complicated. If you can\u2019t explain something, you can\u2019t repeat it reliably. And if you can\u2019t repeat it reliably, you can\u2019t scale it.<\/p>\n This shows up everywhere, not just in manufacturing. One of the best examples I\u2019ve seen is from a completely different world: Alinea, the Michelin three-star restaurant in Chicago.<\/p>\n From the customer\u2019s perspective, it\u2019s theatrical. It feels complex, even magical. But backstage, the kitchen is the opposite of magical. It\u2019s engineered. Everything is designed around simplicity and repeatability. Tools and appliances are placed to eliminate unnecessary movement. Stations are arranged so chefs barely have to turn their heads. The choreography is so tight that plating steps can happen within seconds.<\/p>\n \u201cEverything is designed around simplicity and repeatability.\u201d<\/p>\n<\/blockquote>\n When the standard is perfection at speed, you cannot survive on complexity. The only way it works is by stripping out extra steps, removing variation wherever it does not add value, and locking in a system that people can execute the same way, every time.<\/p>\n That\u2019s what simplification really is. Not making things smaller. Making them repeatable, because that\u2019s what scales.<\/p>\n I am not talking about cutting corners. I mean making decisions, testing, learning, and improving in short cycles. Fast teams catch problems early and fix them while they are still small.<\/p>\n One of the best examples from my career comes from Lululemon and the Winter Olympics. Lululemon\u2019s product development process was not built for extreme deadlines. Then, in late 2021, Lululemon won the contract to outfit Team Canada for the Winter Olympics and Paralympics in Beijing. The catch was simple and brutal: The athletes needed the gear in about four months. So, the Lululemon team had to compress time in a way that normally would have sounded impossible. They did two key things:<\/p>\n What makes things move in your organization? What do you do weekly, or daily, that turns talk into action? For speed, you need a system that keeps decisions and progress on a short leash.<\/p>\n Automation is powerful, but only after the system works. Too many organizations automate a messy process. All that does is lock in and disguise the mess. Fix the work first, then automate it.<\/p>\n You see this in great startups. Early Amazon did a lot by hand, so they could learn the real process before building tech around it. DoorDash started by doing things manually, too, taking orders and delivering food before they wrote software, because you cannot automate what you do not understand.<\/p>\n Especially now, with AI everywhere, the question is not \u201cCan we automate this?\u201d It\u2019s \u201cShould we?\u201d Use technology to speed up good systems, not to paper over bad ones.<\/p>\n \u201cToo many organizations automate a messy process.\u201d<\/p>\n<\/blockquote>\n You do not need a factory or a product launch to use this. You can apply it to anything that feels slower, heavier, or harder than it should. A weekly meeting that drags. An approval chain that kills momentum. An onboarding process that takes forever. Even the way your household runs when everyone is rushing out the door.<\/p>\n Pick one thing. Write down what people say \u201chas to happen.\u201d Then ask\u00a0why<\/em>. Keep asking until you hit a real constraint, like law, safety, or physics. Everything else is negotiable. Then delete what no one would miss. Simplify what remains until you can explain it in plain language. Speed it up for a week\u2014not to create stress, but to surface what is broken. And only after it works, then let technology help.<\/p>\n Enjoy our full library of Book Bites\u2014read by the authors!\u2014in the Next Big Idea app<\/a><\/em>.<\/p>\n This article originally appeared<\/a> in <\/em>Next Big Idea Club magazine and is reprinted with permission.<\/em><\/p>\nWhat\u2019s the big idea?<\/h2>\n
1. Question every single requirement.<\/h2>\n
2. Delete every possible step in the process.<\/h2>\n
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3. Simplify, simplify, simplify.<\/h2>\n
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4. If you can move faster than everyone else, you will win more often than you should.<\/h2>\n
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5. Automate last.<\/h2>\n
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