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How long is 10000 hours realistically?

about 1 year and 51 days The idea that 10,000 hours (about 1 year and 51 days total) of practice is what you need to gain expertise in performance-based fields was initially popularized in Malcolm Gladwell's bestseller Outliers.

hbr.org - A Fast Track to 10,000 Hours of Practice - Harvard Business Review

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Have you completed your 10,000 hours of deliberate practice?

The idea that 10,000 hours (about 1 year and 51 days total) of practice is what you need to gain expertise in performance-based fields was initially popularized in Malcolm Gladwell’s bestseller Outliers. The research results he focused on emphasized the benefits of practice for fine-motor activities like playing the piano. But more recent studies show the upside of the 10,000-hour benchmark for collaborative knowledge work — the type of expertise required to create, or lead, or grow a company. For most of us, of course, logging that much deliberate practice may seem unattainable in today’s time-scarce business environments. Employees barely have enough time to complete job responsibilities, no less find extra hours to practice their skills. (Even if your company generously put aside two-and-a-half work weeks per year for you to practice skills, it would still take you 100 years before you hit the 10,000 hour benchmark). But what if deliberate practice was your job, and the way your organization did business? Then you and colleagues could feasibly hit this threshold for mastery in as little as 5 years. Here are three tips, grounded in our recent Babson Executive Education study of over 500 companies, to accelerate this process: Try experimentation. Previous studies show that experimentation is one of the most fundamental forms of deliberate practice we can engage in. By performing more of their work in the form of experiments, employees can synchronously advance projects while putting hours in toward their 10,000. This synchronicity can result in stronger organizational performance, according to our data. Experimentation-oriented organizations, one-quarter of our survey sample, are more than 4 times as likely to have achieved greater than 20% growth over the past year compared to others in the sample. How is an experimental approach different than business as usual? Much of conventional organizational work is about planning and analyzing how to act, often on a large scale; risk is controlled by repeatable processes and standard routines. Rather than planning to do things, experimenting means doing things in a new way on a small scale. You get quick feedback, allowing you to make timely adjustments and improvements. On seeing the results of your action, practitioners can adopt the new way, discard it, or modify it and try again. Maximize your opportunities to experiment. By understanding a variety of ways to experiment, employees can create more opportunities to accrue their 10,000 hours. Donald Schon’s seminal work on reflective practice identifies three basic experimentation strategies, each of which we found at play in our own research: Move testing is when you take action to produce an intended change. For instance, a technology vendor in our sample wanted to create a new, lower-cost offering to target customers who couldn’t afford its custom software. Employees experimented by removing pricey features and consulting services from one of its products and purchase the software off-the-shelf. The move allowed the company to study intended benefits, as well as unanticipated changes. For example, the company discovered it would need to transition key R&D personnel onto the new product team to develop and sustain the offering. The same firm also engages in exploratory experimentation for initiatives with high levels of uncertainty, such as “trying out new concepts in [totally] new markets.” This approach is about taking action only to see what happens. While exploratory experimenters intentionally avoid making predictions, often because they don’t have reliable data, their actions generate data that can enable informed decisions and adjustments.

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Hypothesis testing is a way of trying out and comparing competing hypotheses. One firm we studied told us that “despite all indications, a competitor launched a product two years ahead of expectations, resulting in potentially significant losses for us in the US.” Various division heads offered their take on how the company might respond. Rather than use her intuition to place a big bet on one response, the CEO asked each executive to test their hypothesis inside their division. After carefully monitoring experimental results, she then selected the most promising approach as a corporate response. “We successfully reduced the top line losses of millions of dollars,” the CEO observed. As a result of “this success story,” employees report that hypothesis testing is “now a key approach to reacting to any alarming change or threat in the marketplace.” Focus on the social side of experimentation. Our research shows that experimentation in organizations is social and highly collaborative. By networking with like-minded experimenters and teaching to uninitiated colleagues, you create additional opportunities to accelerate your way toward 10,000 hours. Begin by asking a few tough questions. Where are the project delays? Is there a big idea in the innovation pipeline that never seems to go anywhere? These are situations that are ripe for experimentation. One senior manager at an agriculture products firm described how an “inexperienced team’s analysis paralysis” was preventing them from developing a marketing strategy for entering a lucrative geographic area. In response, the manager is helping the team to devise experiments to test competing hypotheses. Not only is he helping to break the impasse, but he is starting others on their own journey toward 10,000 hours.

hbr.org - A Fast Track to 10,000 Hours of Practice - Harvard Business Review

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