{"id":27653,"date":"2021-02-02T10:01:59","date_gmt":"2021-02-02T10:01:59","guid":{"rendered":"https:\/\/www.ceo-na.com\/?p=27653"},"modified":"2021-02-02T16:31:24","modified_gmt":"2021-02-02T16:31:24","slug":"six-problem-solving-mindsets-for-very-uncertain-times","status":"publish","type":"post","link":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/business\/management-leadership\/six-problem-solving-mindsets-for-very-uncertain-times\/","title":{"rendered":"6 problem-solving mindsets for very uncertain times\u00a0"},"content":{"rendered":"

Great problem solvers are made, not born.<\/span><\/p>\n

<\/p>\n

Great problem solvers are made, not born. That\u2019s what we\u2019ve found after decades of problem solving with leaders across business, nonprofit, and policy sectors. These leaders learn to adopt a particularly open and curious mindset, and adhere to a systematic process for cracking even the most inscrutable problems. They\u2019re terrific problem solvers under any conditions. And when conditions of uncertainty are at their peak, they\u2019re at their brilliant best.<\/span><\/p>\n

Six mutually reinforcing approaches underly their success: (1) being\u00a0<\/span>ever-curious<\/span><\/i>\u00a0about every element of a problem; (2) being\u00a0<\/span>imperfectionists<\/span><\/i>, with a high tolerance for ambiguity; (3) having a\u00a0<\/span>\u201cdragonfly eye\u201d<\/span><\/i>\u00a0view of the world, to see through multiple lenses; (4) pursuing\u00a0<\/span>occurrent behavior<\/span><\/i>\u00a0and experimenting relentlessly; (5) tapping into the\u00a0<\/span>collective intelligence<\/span><\/i>, acknowledging that the smartest people are not in the room; and (6) practicing\u00a0<\/span>\u201cshow and tell\u201d<\/span><\/i>\u00a0because storytelling begets action.<\/span><\/p>\n

\"\"<\/p>\n

1. Be ever curious\u00a0<\/b><\/b><\/p>\n

As any parent knows, four-year-olds are unceasing askers. Think of the never-ending \u201cwhys\u201d that make little children so delightful\u2014and relentless. For the very young, everything is new and wildly uncertain. But they\u2019re on a mission of discovery, and they\u2019re determined to figure things out. And they\u2019re good at it! That high-energy inquisitiveness is why we have high shelves and childproof bottles.<\/p>\n

When you face radical uncertainty, remember your four-year-old or channel the four-year-old within you. Relentlessly ask, \u201cWhy is this so?\u201d Unfortunately, somewhere between preschool and the boardroom, we tend to stop asking. Our brains make sense of massive numbers of data points by imposing patterns that have worked for us and other humans in the past. That\u2019s why a simple technique, worth employing at the beginning of problem solving, is simply to pause and ask\u00a0<\/span>why<\/span><\/i>\u00a0conditions or assumptions are so until you arrive at the root of the problem.<\/span><\/p>\n

Natural human biases in decision making, including confirmation, availability, and anchoring biases, often cause us to shut down the range of solutions too early.<\/span> Better\u2014and more creative\u2014solutions come from being curious about the broader range of potential answers.<\/span><\/p>\n

One simple suggestion from author and economist Caroline Webb to generate more curiosity in team problem solving is to put a question mark behind your initial hypotheses or first-cut answers. This small artifice is surprisingly powerful: it tends to encourage multiple solution paths and puts the focus, correctly, on assembling evidence. We also like thesis\/antithesis, or red team\/blue team, sessions, in which you divide a group into opposing teams that argue against the early answers\u2014typically, more traditional conclusions that are more likely to come from a conventional pattern. Why is\u00a0<\/span>this<\/span><\/i>\u00a0solution better? Why not\u00a0<\/span>that<\/span><\/i>\u00a0one? We\u2019ve found that better results come from embracing uncertainty. Curiosity is the engine of creativity.<\/span><\/p>\n

2. Tolerate ambiguity\u2014and stay humble!<\/b><\/p>\n

When we think of problem solvers, many of us tend to picture a poised and brilliant engineer. We may imagine a mastermind who knows what she\u2019s doing and approaches a problem with purpose. The reality, though, is that most good problem solving has a lot of trial and error; it\u2019s more like the apparent randomness of rugby than the precision of linear programming. We form hypotheses, porpoise into the data, and then surface and refine (or throw out) our initial guess at the answer. This above all requires an embrace of imperfection and a tolerance for ambiguity\u2014and a gambler\u2019s sense of probabilities.<\/span><\/p>\n

The real world is highly uncertain. Reality unfolds as the complex product of stochastic events and human reactions. The impact of COVID-19 is but one example: we address the health and economic effects of the disease, and their complex interactions, with almost no prior knowledge. We have to be comfortable with estimating probabilities to make good decisions, even when these guesses are imperfect. Unfortunately, we have truckloads of evidence showing that human beings aren\u2019t good intuitive statisticians. Guesses based on gut instinct can be wildly wrong. That\u2019s why one of the keys to operating in uncertain environments is epistemic humility, which Erik Angner defines as \u201cthe realization that our knowledge is always provisional and incomplete\u2014and that it might require revision in light of new evidence.\u201d<\/span><\/p>\n

Recent research shows that we are better at solving problems when we think in terms of odds rather than certainties.<\/span> For example, when the Australian research body Commonwealth Scientific and Industrial Research Organisation (CSIRO), which owned a core patent on the wireless internet protocol, sought royalties from major companies, it was initially rebuffed. The CSIRO bet that it could go to court to protect its intellectual property because it estimated that it needed only 10 percent odds of success for this to be a good wager, given the legal costs and likely payoff. It improved its odds by picking the weakest of the IP violators and selecting a legal jurisdiction that favored plaintiffs. This probabilistic thinking paid off and eventually led to settlements to CSIRO exceeding $500 million.<\/span> A tolerance for ambiguity and a willingness to play the odds helped the organization feel its way to a good solution path.<\/span><\/p>\n

To embrace imperfectionism with epistemic humility, start by challenging solutions that imply certainty. You can do that in the nicest way by asking questions such as \u201cWhat would we have to believe for this to be true?\u201d This brings to the surface implicit assumptions about probabilities and makes it easier to assess alternatives. When uncertainty is high, see if you can make small moves or acquire information at a reasonable cost to edge out into a solution set. Perfect knowledge is in short supply, particularly for complex business and societal problems. Embracing imperfection can lead to more effective problem solving. It\u2019s practically a must in situations of high uncertainty, such as the beginning of a problem-solving process or during an emergency.<\/span><\/p>\n

3. Take a dragonfly-eye view<\/strong><\/p>\n

Dragonfly-eye perception is common to great problem solvers. Dragonflies have large, compound eyes, with thousands of lenses and photoreceptors sensitive to different wavelengths of light. Although we don\u2019t know exactly how their insect brains process all this visual information, by analogy they see multiple perspectives not available to humans. The idea of a dragonfly eye taking in 360 degrees of perception6<\/sup><\/a>\u00a0is an attribute of \u201csuperforecasters\u201d\u2014people, often without domain expertise, who are the best at forecasting events.<\/p>\n

Think of this as widening the aperture on a problem or viewing it through multiple lenses. The object is to see beyond the familiar tropes into which our pattern-recognizing brains want to assemble perceptions. By widening the aperture, we can identify threats or opportunities beyond the periphery of vision.<\/p>\n

Consider the outbreak of HIV in India in the early 1990s\u2014a major public-health threat. Ashok Alexander, director of the Bill & Melinda Gates Foundation\u2019s India Aids Initiative, provided a brilliant example of not just vision but also dragonfly vision. Facing a complex social map with a rapidly increasing infection rate, he widened the problem\u2019s definition, from a traditional epidemiological HIV transmission model at known \u201chot spots,\u201d to one in which sex workers facing violence were made the centerpiece.<\/p>\n

This approach led to the \u201cAvahan solution,\u201d which addressed a broader set of leverage points by including the sociocultural context of sex work. The solution was rolled out to more than 600 communities and eventually credited with preventing 600,000 infections. The narrow medical perspective was sensible and expected, but it didn\u2019t tap into the related issue of violence against sex workers, which yielded a richer solution set. Often, a secret unlocks itself only when one looks at a problem from multiple perspectives, including some that initially seem orthogonal.<\/p>\n

The secret to developing a dragonfly-eye view is to \u201canchor outside\u201d rather than inside when faced with problems of uncertainty and opportunity. Take the broader ecosystem as a starting point. That will encourage you to talk with customers, suppliers, or, better yet, players in a different but related industry or space. Going through the customer journey with design-thinking in mind is another powerful way to get a 360-degree view of a problem. But take note: when decision makers face highly constrained time frames or resources, they may have to narrow the aperture and deliver a tight, conventional answer.<\/p>\n

Read the rest of six problem-solving mindsets in the full McKinsey article here<\/a>.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

Great problem solvers are made, not born.<\/p>\n","protected":false},"author":22,"featured_media":28436,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1069,43],"tags":[99,1385,4105,184,4107,4106],"class_list":["post-27653","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-editors-choice","category-management-leadership","tag-ceo","tag-ceo-northam","tag-decision-making","tag-mckinsey","tag-problem","tag-problem-solving"],"_links":{"self":[{"href":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/wp-json\/wp\/v2\/posts\/27653","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/wp-json\/wp\/v2\/users\/22"}],"replies":[{"embeddable":true,"href":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/wp-json\/wp\/v2\/comments?post=27653"}],"version-history":[{"count":5,"href":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/wp-json\/wp\/v2\/posts\/27653\/revisions"}],"predecessor-version":[{"id":28789,"href":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/wp-json\/wp\/v2\/posts\/27653\/revisions\/28789"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/wp-json\/wp\/v2\/media\/28436"}],"wp:attachment":[{"href":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/wp-json\/wp\/v2\/media?parent=27653"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/wp-json\/wp\/v2\/categories?post=27653"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/servidor-mxigen1.com\/ceona-antiguo\/wp-json\/wp\/v2\/tags?post=27653"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}