{"id":12601,"date":"2020-10-18T11:55:00","date_gmt":"2020-10-18T10:55:00","guid":{"rendered":"http:\/\/revva.net\/?p=12601"},"modified":"2024-01-12T20:05:21","modified_gmt":"2024-01-12T20:05:21","slug":"hotel-data-between-gut-instinct-analytics","status":"publish","type":"post","link":"https:\/\/imssc.org\/biflix\/hotel-data-between-gut-instinct-analytics\/","title":{"rendered":"Hotel data: between gut instinct and Analytics"},"content":{"rendered":"<p>In past articles, I\u2019ve been offering telltales about managers and business owners who systematically ignored whatever data told them. And the grim results that decision (or lack of it) brought to their companies. Their stance was understandable, though. Those episodes refer to a time where \u201cdata-driven\u201d, \u201cbusiness intelligence\u201d and \u201canalytics\u201d were largely unknown terms in our environment. But in the past few years, I am observing an equally interesting (and destructive) trend. Which is decision makers opting to get and put in place BI tools (even data science teams!), only to <strong>dismiss<\/strong> their data-based outcomes.<strong> Yep, there&#8217;s still a clash between gut instinct and Analytics.<\/strong><\/p>\n<p>Some of these stakeholders would show off at trade fairs, elevating their profiles though abundant use of tech buzzwords. Others would trust their IT staff (which usually know close to nothing about business, and as much as their employers about BI), spending a fat check on something nobody can milk off.<\/p>\n<h5>Data-driven my a$$<\/h5>\n<p>When it comes to put their data to use, said decision makers would still follow <strong>hunches<\/strong>, rather than take rational, fact-based resolutions.<\/p>\n<p>The identikit of such gut-driven decision makers is quite obvious: usually old-school, self-made, non-analytical persons. Such characters are identifiable with a simple test: show them a graphic or two with their own data. But on a different format, not their usual tabular reporting. Depending on their reaction to the test, I will know if the war is over. After all, they made it all this way without any help from bloody data, didn\u2019t they? I get it, time to give up. Under no circumstances they&#8217;ll accept suggestions from a computer.<\/p>\n<p>Please note I am not criticising anybody here. Especially people who actually made it on their own, by pure guts (mental or not). They have all my admiration and respect. But their brainwork and decision process roots on <strong>feelings.<\/strong> They made up their minds long before data was available and served. Since I know no way to eradicate that deep ingrained habit, I\u2019d rather throw the towel and wave goodbye, with my sincere best wishes.<\/p>\n<h5>Confirmation biased boss<\/h5>\n<p>Then there\u2019s the middle (aged?) batch, those who recognise the need for data-driven decisions, and act upon that recognition. Yet, they tend to use data only to <strong>confirm<\/strong> their hunches. I confess I was one of these characters when I owned a tour operator. This is known as <strong>confirmation bias<\/strong>, and it sucks, unless we\u2019re talking about love interests here. It\u2019s probably worse than ignoring data insights! At enterprise level, where analysts and data scientist are brought in to solve business problems, the issue would spread exponentially. Either the specialists shape findings to please the big boss\u2019 ideas (consciously or not), or they iterate the analysis ad infinitum, offering as much solutions and interpretations as members the data team has, squared.<\/p>\n<h5>Freshmen data jockeys<\/h5>\n<p>The next generations of managers are learning at universities the absolute need for data decision processing and the relevant skills. So for a while we will witness interesting company-wide battles between young hotshot and old farts. Until one day, the decision-taking process will be entirely left to a collection of <strong>neural network<\/strong> algorithms (or whatever technology will be available then). At that point, managers will be able to focus on what they do best: complain, delay payments and play office golf.<\/p>\n<p>Be aware though, that there are already industries (finance and insurance, for instance) successfully working with those artificial neural networks, and other things we backward travel traders might see as science fiction. Except airlines -and to some extent, large branded chains- we hoteliers only spend in innovation when our competitors are benefitting from it, not before. Apparently, we have a high degree of risk aversion on our DNA. If only we knew that risk management is also part of data management (see article <a href=\"https:\/\/imssc.org\/biflix\/hoteldatasiloskiller\/\" target=\"_blank\" rel=\"noopener\">here &gt;&gt;<\/a>), which can also be automated through data-driven processes!<\/p>\n<p>Thanks for reading<\/p>\n<p><em>Marcello Bresin<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The clash between gut instinct and analytics in the hotel industry&#8217;s data landscape is ongoing. <\/p>\n","protected":false},"author":1,"featured_media":4503,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[73],"tags":[84,93],"class_list":["post-12601","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-strategy","tag-data-management","tag-strategy"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Hotel data: between gut instinct and Analytics - BIFLIX<\/title>\n<meta name=\"description\" content=\"Hotel data: between gut instinct and Analytics. 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