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Concepts like MECE, Interviewing, Brainstorming and preparing the audience for steercoms, while may seem common sensical, are sidestepping professional landmines in consulting. The other life lesson on handling work like balance and avoiding burnout are still work in progress and a lot has changed since the book was written. The client can mess up. Politics, rivalry, not willing to cooperate, feeling threatened by restructuring. Paraphrase what you hear in your own words. Confirm whether you understand correctly. This also gives chances for the interviewee to add or amplify important points. Charles Conn: Availability bias is the one that I’m always alert to. You think you’ve seen the problem before, and therefore what’s available is your previous conception of it—and we have to be most careful about that. In any human setting, we also have to be careful about biases that are based on hierarchies, sometimes called sunflower bias. I’m sure, Hugo, with your teams, you make sure that the youngest team members speak first. Not the oldest team members, because it’s easy for people to look at who’s senior and alter their own creative approaches. When I went to work with Gordon Moore at the Moore Foundation, the problem that he asked us to look at was “How can we save Pacific salmon?” Now, that sounds like an impossible question, but it was amenable to precisely the same type of disaggregation and allowed us to organize what became a 15-year effort to improve the likelihood of good outcomes for Pacific salmon.
Always wear impeccable clothing and groom yourself like you are being judged. Power dressing is called that for a reason Chapter 7: The Fact-Based Approach This chapter explains the importance of using data to support one’s arguments. It provides advice on how to gather and analyze data effectively, and how to present data in a way that is compelling and persuasive.Look for abnormal patterns (things that are especially good or bad). That’s where all the insights lie. Charles Conn: It can be revolutionary. There are some areas in which the pattern recognition of large data sets and good algorithms can help us see things that we otherwise couldn’t see. But I do think it’s terribly important we don’t think that this particular technique is a substitute for superb problem solving, starting with good problem definition. Many people use machine learning without understanding algorithms that themselves can have biases built into them. Just as 20 years ago, when we were doing statistical analysis, we knew that we needed good model definition, we still need a good understanding of our algorithms and really good problem definition before we launch off into big data sets and unknown algorithms.
Practice: Practice your presentation before delivering it to ensure that you are comfortable and confident. This will also help you identify any areas that need improvement or clarification. Know your audience: It’s important to tailor your presentation to your audience. Consider their needs, goals, and level of expertise. This will help you choose the right tone, level of detail, and type of content to include. Too generalist (though I believe one should not expect secret recipes or detailed problem-solving algorithms from such a book.. I was still very eager for some level of detail or specificity)Simon London: Problem solving is a really interesting piece of terminology. It could mean so many different things. I have a son who’s a teenage climber. They talk about solving problems. Climbing is problem solving. Charles, when you talk about problem solving, what are you talking about? When you spend more time at client location than with your peers it is very easy to lose sense of belonging. Don't forget it's the client>>firm>>you.
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