{"id":64931,"date":"2022-04-16T22:31:48","date_gmt":"2022-04-17T02:31:48","guid":{"rendered":"https:\/\/www.shortform.com\/blog\/?p=64931"},"modified":"2022-04-27T23:04:30","modified_gmt":"2022-04-28T03:04:30","slug":"a-learning-organization","status":"publish","type":"post","link":"https:\/\/www.shortform.com\/blog\/a-learning-organization\/","title":{"rendered":"A Learning Organization Is Built Off These 3 Techniques"},"content":{"rendered":"\n

What is a learning organization and why do you need one? How do you successfully build one? <\/p>\n\n\n\n

A learning organization uses failures to improve its operations and innovate solutions to tough problems. According to the book Black Box Thinkin<\/em>g, clarifying feedback, breaking down the problem, and finding opportunities to innovate are the most effective ways for you to build a learning organization. <\/p>\n\n\n\n

Read on to learn about the top three techniques you can use to build a learning organization.<\/p>\n\n\n\n\n\n\n\n

Technique #1: Clarify Feedback<\/strong><\/h2>\n\n\n\n

First, clarify feedback to build a learning organization. While iteration \u00e0 la the MVP is often effective, feedback is sometimes misleading. For example, if you try to test the effect of coffee on college students but give it to every<\/em> test subject, you\u2019ll have no basis on which to contextualize the results. <\/p>\n\n\n\n

To combat this, Syed argues, you need to run a randomized control trial (RCT). By comparing a control group to the test group, you clarify the effect of what you\u2019re testing. <\/p>\n\n\n\n

Here\u2019s how an RCT works: Experimenters randomly divide participants into two groups, subjecting one to the experimental variable and giving the other a placebo (or nothing). The difference between the groups\u2019 results reveals the actual effect of the experimental variable<\/strong>. <\/p>\n\n\n\n

For example, a learning organization developing a nootropic (brain-boosting) supplement would give the real pill to one group and a placebo pill to the other. Then they\u2019d compare the groups\u2019 results to determine the pill\u2019s actual efficacy.<\/p>\n\n\n\n

(Shortform note: In addition to using a placebo, researchers should conduct the trial as a double-blind<\/a>. This means that neither the researchers nor the test subjects know whether they receive the treatment or the placebo. This prevents bias from skewing results: If researchers don\u2019t know who has the treatment, their beliefs about its effectiveness can\u2019t influence how they interpret the proceedings of the experiment.) <\/p>\n\n\n\n

After testing, experimenters take the feedback and adjust their theory or product accordingly. Then they\u2019ll repeat, keeping a tight loop between the feedback and the next iteration, until they reach a well-tested result. <\/p>\n\n\n\n

Continuing the example, the nootropic company could use the data from testing to improve their product or decide whether it\u2019s ready for the market.<\/p>\n\n\n\n

(Shortform note: RCTs aren\u2019t always the right solution<\/a>, for a few reasons. If your sample size is too small (20 or fewer), the test can\u2019t guarantee a strong effect because outliers can skew the data. Sometimes, an RCT isn\u2019t ethical\u2014for example, a test to determine the efficacy of an individualized tutoring program might favor some students while leaving others behind. Because it\u2019s random, there\u2019s no way to ensure that students with the greatest need receive help. Finally, RCTs only reveal simple causal effects: They can tell you that A \u2192 B. But real-world causation is often complex and nonlinear\u2014for example, a pill may reduce your cholesterol while also throwing off your sleep patterns and causing hair loss.)<\/p>\n\n\n\n

Technique #2: Break Down the Problem<\/strong><\/h2>\n\n\n\n

Iteration and randomized control trials often work wonders, but some problems are too immense, too complex, or lack a viable control group<\/strong>. If you\u2019re the US president, for example, you can\u2019t run tests on the whole country\u2014nor do you have a second country to act as a control group.<\/p>\n\n\n\n

For a learning organization to handle this, Syed explains, you need to break the problem down into smaller challenges and accumulate small wins<\/strong>. For example, to fix a struggling economy, you\u2019d first identify the smaller issues: runaway inflation, irresponsible financial speculators, a population crushed with debt, and so on.<\/p>\n\n\n\n

Continue to chunk down the problems until you have something small enough to take action on<\/strong>. Then, start testing ideas. Maybe you test a free financial literacy<\/a> course in one town, with a similar town as a control, instead of testing on the whole country. If it works, you can try to scale it; if not, you can adjust and try again.<\/p>\n\n\n\n

Over time, many little successes accumulate into big results. Maybe the course doesn\u2019t work until the 15th iteration, but that little success can scale and help solve the larger problem. Then move on to the next small problem<\/a>, and the next, and keep building toward that larger success.<\/p>\n\n\n\n

The Origin of the Black Box<\/strong>
In 1949, a British airline called De Havilland began flying its new jet airliner, the Comet. This was the first modern passenger jet\u2014but just a few years later, Comets began crashing. By 1954, seven Comets had disintegrated or crashed. In investigating the crashes, Australia\u2019s Department of Civil Aviation<\/a> faced a lack of meaningful data. They had no recordings of flight data\u2014speed, positioning, fuel levels\u2014nor any recordings of cockpit conversations, so they couldn\u2019t deduce the cause of the crashes.\u00a0One Australian researcher, David Warren, realized that if they had such recordings, they could better understand what had happened<\/a>. Over the next four years, he developed a prototype black box to record flight data and the interactions between crew members in the cockpit.\u00a0His invention caught the eye of British aviation authorities in 1958, and it sparked a movement to integrate black boxes into all civilian airliners. By 1962, Warren had developed a standard model, and his technology soon spread around the world. This step\u2014from having no <\/em>data on crashes to over two dozen measures of flight data and in-cockpit happenings\u2014enabled significant improvements in airline safety.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Technique #3: Find Opportunities to Innovate <\/strong><\/h2>\n\n\n\n

Up to a point, you can iterate, test, and break down the problem. But eventually, your efforts will outweigh the gains from each marginal improvement. This is because surface-level iteration improves on an existing paradigm, but it doesn\u2019t fundamentally change it.<\/p>\n\n\n\n

To move further as a learning organization, Syed explains that you need to go beyond the \u201clocal maximum,\u201d the highest point of improvement for a given paradigm. For example, you can only shoot an arrow so far with a shortbow, so you\u2019d need to develop a new tool to surpass that distance. <\/p>\n\n\n\n

(Shortform note: In Blue Ocean Strategy<\/em><\/a>, W. Chan Kim argues that success comes from finding a \u201cBlue Ocean,\u201d or uncontested market<\/a>. Syed\u2019s \u201clocal maximum\u201d corresponds to Kim\u2019s \u201cRed Ocean,\u201d a heavily contested market. To move beyond that obvious, crowded arena, think beneath the surface-level function of products to discover the underlying function. For example, home gym equipment serves the same purpose as fitness classes or a gym membership: To help the user get fit and feel good. Knowing that, you could ask \u201cIs there some untapped approach to home fitness that we could create?\u201d, thus going beyond current conventional options.) <\/p>\n\n\n\n

To go beyond the local maximum, you need to find<\/em> and confront<\/em> some unexamined problems in the current paradigm<\/strong>:<\/p>\n\n\n\n

  1. To find<\/em> an opportunity to innovate, consider the recurring problems<\/strong> with the technologies you use. For example, a medieval archer might\u2019ve noticed that human-powered shortbows couldn\u2019t reach distant targets. <\/li>
  2. Then confront<\/em> that problem, asking how things could be better. Maybe the archer asked, \u201cWhat could propel these arrows more forcefully than human muscle?\u201d Now he\u2019s begun to invent the crossbow, and he did it by looking for an opportunity to change things at a deeper level.  <\/li><\/ol>\n","protected":false},"excerpt":{"rendered":"

    What is a learning organization and why do you need one? How do you successfully build one? A learning organization uses failures to improve its operations and innovate solutions to tough problems. According to the book Black Box Thinking, clarifying feedback, breaking down the problem, and finding opportunities to innovate are the most effective ways for you to build a learning organization. Read on to learn about the top three techniques you can use to build a learning organization.<\/p>\n","protected":false},"author":15,"featured_media":17393,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[45,14],"tags":[601],"class_list":["post-64931","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business","category-management","tag-black-box-thinking","","tg-column-two"],"yoast_head":"\nA Learning Organization Is Built Off These 3 Techniques - Shortform Books<\/title>\n<meta name=\"description\" content=\"Do you want to build a learning organization? 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