Executive book summaries, reviews & webinars of the best business books. Each 8-page text and minute audio summary covers the most important concepts. Executive Book Summaries. Titles are arranged alphabetically. [# – C] [D – F] [G aracer.mobi · aracer.mobi . Start with 4 Free audio summaries of best-selling business books; Find new Many entrepreneurs and business executives barely have enough time to.
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Book summaries can be a useful way to keep up with business thought, posting direct links to the summaries I found (aracer.mobi and some audio). this service is brought to you by an executive coach so many of the titles. Com gives you access to business book summaries, so that you can get ideas from great books into your brain and put them into Download PDF catalog. THE COMPLETE SUMMARY: THE FIVE DYSFUNCTIONS OF A TEAM by Patrick Lencioni. 2 Soundview Executive Book Summaries® aracer.mobi
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This book will show you how to raise your likeability factor. Pink — discover the three elements of true motivation—autonomy, mastery, and purpose — and how to put them into action. Love is the Killer App How to Win Business and Influence Friends by Tim Sanders — find out how by helping others grow to become the best people they can be, you are being loving — and you grow, too. Gerber — how commonplace assumptions can get in your way of running a business, and how to take the steps to succeed The Upside of the Downturn by Geoff Colvin — how to see the recession as a rich opportunity to reinvent your business and lay the groundwork for future growth.
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Validated learning is having testable hypotheses about the world, designing experiments to test those hypotheses, and analyzing the data to evaluate your hypotheses. You have real, quantitative data to show what you have learned. In , Eric and his co-founders at IMVU wanted to build a social network around instant messaging IM , which seemed attractive for its network effects — the more people who join, the more valuable the network is, which makes even more people join.
Because of network effects, the top IM products owned the vast majority of the industry.
Instead, they built a new 3D video game layer on top of IM networks. Users would first join IMVU, a 3D virtual world where they could create avatars and download virtual goods. The IMVU team labored for 6 months on their prototype product. Will it make us look bad? And no one joined. They thought it was a quality problem at first, so they worked on fixing bugs and adding features. Finally, they decided to bring in potential users for interviews.
This is where their epiphany happened. Just like people today have different lives on different social networks Facebook, Twitter, LinkedIn, Instagram, Pinterest, etc. They wanted to make new friends, not bring their existing friends over. When Eric and his team realized this, they threw away almost a year of hard work.
But when they built a product that their customers actually wanted, they started getting traction. They could have saved themselves a lot of pain and time. This Lean Startup summary is going to teach you how to avoid mistakes like this. Put more proactively — how could IMVU have learned what customers wanted earlier, without 6 months of hard engineering? Did they really need to support a dozen IM clients at launch?
Probably not — even connecting just one IM network could have led to the same conclusion, and it would have taken a lot less work. But what if they had tried something even more extreme — what if they pretended to have a working product on their website with a download button, and they measured what users actually wanted by download clicks?
Question: What do you take for granted that you should actually question? How can you test this in the next week? Lean Startup methodology treats building a startup as science: Create a hypothesis. Design an experiment to directly test that hypothesis.
Run the experiment and gather data. Reflect on the data — can you validate or reject your hypothesis? Your hypotheses should revolve around the most important problem of a startup — how to build a sustainable business around your vision. Does the product actually deliver value to the customer? Growth hypothesis: how will the company grow once people start using the product? The best way to understand human preferences is to track behavior of real people, not ask for opinions.
Think about the cheapest, fastest experiment you can run to validate the hypothesis. Simplify the product to the core essentials needed to run the experiment.
Launching early gives you more customer information earlier. Traditionally, you would try to research everything possible about your core user, then build your product to polished perfection, then release with a big launch party. Notice how the same underlying principles apply to vastly different companies and scenarios.
Anecdote: Zappos During the dot-com boom, it seemed like the internet could be a new commerce platform for everything — books, groceries, even pet supplies. Companies like Webvan started business by building massive infrastructures and supply chains, even before they had proven customer demand. Zappos founder Nick Swinmurn took the opposite approach. His first action was to test the hypothesis that people actually wanted to download shoes online.
He took perhaps the simplest approach possible — he went to local shoe stores, took pictures of shoes, and posted them online. With virtually zero start-up cost, Zappos tested customer demand. Furthermore, they measured customer demand in the best way possible —getting people to pay real money. This is a much stronger indication of interest than voicing an opinion on a survey. From this starting point, Zappos could easily run all sorts of deeper experiments — what types of shoes do people want?
What policies matter most to them?
By measuring what people actually do, Zappos can learn true customer preferences. Laundry is primarily done at home or by paid cleaners who wash clothes in river water and hang to dry, often taking over a week to return clothes. Their hypothesis? Customers would pay to have their laundry cleaned and returned within the same day.
To experiment, they launched a simple prototype — a truck with a washing machine mounted on the back. This was just a marketing gimmick — they really took the laundry somewhere offsite and cleaned it there. But it was just enough to test their hypothesis with real customers and find out what they really wanted. In response, they built a more substantial, reputable-looking kiosk. They also found that customers were willing to pay a premium for faster service and ironing.
Through all their learning, Village Laundry Services ended with their final version — a mobile kiosk with its own washer and dryer that could service clothes on site. These two examples seem vastly different on the surface. One was leading the forefront of e-commerce during the dotcom boom. Another was introducing convenience to a developing region.
But the principles were the same: They formed a hypothesis about the core customer need that would drive their business. They started with the bare minimum product needed to test the hypothesis. They studied real user behavior by observing their actions, not simply by asking questions. From this baseline, they could experiment further. No matter your situation or customer need, these principles will apply to you as well.
Part Two: Steer With your startup, your goal is to learn as quickly as you can with disciplined experiments.
What do you believe about your customers that is vital to your business? How are you going to measure this? Next, you run the experiment. Often this means exposing users to the product and collecting data on their behavior. Finally, you analyze the data and reflect — how far off was your hypothesis?
What do you need to change about your strategy? Should you actually change your entire direction? Chapter 5: Leap Every startup begins with a set of hypotheses about how the business will work. As stated above, there are typically two core hypotheses: the Value hypothesis what your users want , and the Growth hypothesis how your startup will grow. Online advertising has matured enough that advertisers know how much they want to pay for which types of ads across the Internet.