{"id":89,"date":"2020-12-03T11:15:23","date_gmt":"2020-12-03T16:15:23","guid":{"rendered":"http:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/?p=89"},"modified":"2020-12-03T11:19:37","modified_gmt":"2020-12-03T16:19:37","slug":"lessons-from-heathrow-airports-data-informed-customer-service-strategy","status":"publish","type":"post","link":"https:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/2020\/12\/lessons-from-heathrow-airports-data-informed-customer-service-strategy\/","title":{"rendered":"Lessons from Heathrow Airport\u2019s Data-Informed Customer Service Strategy"},"content":{"rendered":"\n

A while ago, before international travel was restricted due to the global pandemic, I made my way to London Heathrow International Airport to catch a flight back home after a business trip. To cater for what I expected was going to be a long wait at the security check, I arrived at the airport well ahead of the recommended time. Heathrow Airport, after all, is reputed to be one of the world\u2019s busiest airports in terms of passenger traffic. I wasn\u2019t taking any chances.<\/p>\n\n\n\n

Instead of the dread I expected, I was pleasantly\nsurprised. The process was quick and smooth. It took much less time than I had\nanticipated. To boot, the security officers were very courteous and helpful. I\nwondered if I was just lucky to have arrived at a slow time. <\/p>\n\n\n\n

After some inquiry, I concluded that my\nexperience could most likely be attributed to a data-informed customer feedback\nsystem that Heathrow airport had implemented to improve service delivery. Let\nme explain. <\/p>\n\n\n\n

The\nSmiley Face Terminal<\/strong><\/p>\n\n\n\n

While en route to the departure lounge to wait\nfor my flight, I absentmindedly pressed one of the smiley\nface buttons on a terminal<\/a> indicating how I felt to the question,\n\u201cHow was your security experience today?\u201d Much like one would do on a social\nmedia post. I didn\u2019t think much of it until I arrived at the lounge and looked\nup at the large electronic panels to locate my departure gate. <\/p>\n\n\n\n

Next to lists of departing flights, each one\nof the electronic panels had a dashboard with bar graphs showing levels of\ncustomer satisfaction with the airport\u2019s performance on a number of service\nperformance targets. The bar graphs showed how each of the five terminals in\nHeathrow had performed in service level performance targets, such as security\nwait times of less than five minutes.<\/p>\n\n\n\n

It was fascinating to see that all the\nterminals had achieved their targets 98% of the time over the month. For\nexample, one bar graph showed that a terminal had scored 4.21 and above out of\na possible high score of 5 in customer satisfaction level. I had a light bulb\nmoment when I realized that the smiley face terminal I had just encountered was\na tool for collecting feedback from travelers about their experience. <\/p>\n\n\n\n

Immediately, I applied my investigative skills\nto find out how Heathrow came up with this tool and how it was implemented.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

The\nHappyOrNot Innovation<\/strong><\/p>\n\n\n\n

An internet search of \u201csmiley face terminal\u201d\nbrought up articles in the New Yorker <\/a>and the Telegraph<\/a> describing this innovation. I\ndiscovered that it was developed by a small Finnish startup led by a programmer\ncalled Heikki V\u00e4\u00e4n\u00e4nen. As the story goes, Heikki liked to give feedback to\nestablishments he patronized, but filling out surveys was inconvenient.\nApparently, he is not alone.<\/p>\n\n\n\n

Heikki saw this as a business opportunity and\ndeveloped the so-called \u201cHappyOrNot\u201d terminals. The terminals have buttons with\nsmiley faces (made ubiquitous by social media), ranging from very happy to\ndissatisfied, for customers to register their level of satisfaction. They are\nsimple to use and send data directly to people who are interested in the\nresults. <\/p>\n\n\n\n

Heathrow Airport implemented the HappyOrNot\nterminals to improve customer satisfaction levels ahead of the expected influx\nof international visitors for the 2012 Summer Olympics. They positioned\nHappyOrNot terminals so that passengers could use them as they cleared\nsecurity. Airport executives were able identify problem locations in real time,\nand address the issues quickly. At the time, Heathrow security\u2019s over-all\npassenger-satisfaction scores are reported to have risen by more than half. <\/p>\n\n\n\n

Contrast this with the Transportation Security\nAdministration (T.S.A.) feedback system that the New Yorker writer encountered\nat Palm Beach International Airport. Customers were invited to scan a QR code\nto inform T.S.A. of their experience. After scanning the QR code, the writer\nended up with a link to T.S.A.\u2019s general customer-service web page. <\/p>\n\n\n\n

The writer then had to search for a form which\nrequired him to provide his full name and email address to create an account so\nhe could then log in to provide feedback! Hardly the way to encourage customer\nfeedback!<\/p>\n\n\n\n

Data-Informed\nDecision Making<\/strong><\/p>\n\n\n\n

Organizational and business leaders all over\nthe world are increasingly applying innovative ways to gather and analyze\ncustomer feedback to gain insights to improve their systems.   Management scholars have called this concept\norganizational learning. The term \u201clearning organization\u201d was made popular by\nPeter Senge in his book The Fifth Discipline<\/a>.<\/p>\n\n\n\n

One characteristic of learning organizations\nis that they need to be able to detect and correct errors. To do this, an\norganization needs to be able to seek out and seriously consider feedback about\nthe work employees are engaged in, the wider environment, and its performance.<\/p>\n\n\n\n

In the past, organizations collected and then\nanalyzed data \u201coff-line\u201d in order to determine corrective actions to take.\nModern technology, however, has now made it possible to learn at the very\nmoment of action. <\/p>\n\n\n\n

Heathrow Airport, for example, has a key\nperformance index of getting travelers through security in 5 minutes or less.\nHappyOrNot terminals have proven to be an effective tool for the officials to\ncollect real-time data from customers on how they are performing on this\nservice target. Actionable insights enable airport officials to pinpoint\nproblem areas and attend to them immediately, thus increasing their\ncompetitiveness as an air transportation hub. <\/p>\n\n\n\n

Data from customer feedback is not only useful\nin the scenario just described involving single-loop feedback – a response that\ntells you you need to adjust how you\u2019re acting. Insights from data can also\ngenerate double-loop feedback –  a\nresponse that tells you that your approach or strategy needs to change. Data\nare not only useful in detecting discontinuities between strategy and\nperformance in the present, but also among possible visions, strategies, and\nspecific goals for the future that an organization has.<\/p>\n\n\n\n

Organizations that are going to be competitive\nin the fast-paced, interconnected and globalized world where large amounts of\ndata and automation are the norm, are going to be organizations that are quick\nto learn and adapt at every level of the organization. Data-informed decision\nmaking is crucial for individuals, teams, organizations and larger institutions\nto become more capable of self-transformation with the result that they are\nmore creative, more aware, more just, and more sustainable. <\/p>\n\n\n\n

About the Author<\/h4>\n\n\n\n
\"\"
Peter Maribei, PhD is the Associate Director of Education Abroad at Miami University \u2013 Oxford. He manages faculty led study away and study abroad programs. Over the course of his career, he has developed international internship and exchange programs and taught students from the Americas, Europe, and Africa. His scholarly interests lie in experiential learning strategies that contribute towards the development of moral imagination, intercultural competence and socially responsible leadership <\/figcaption><\/figure>\n","protected":false},"excerpt":{"rendered":"

A while ago, before international travel was restricted due to the global pandemic, I made my way to London Heathrow International Airport to catch a flight back home after a business trip. To cater for what I expected was going to be a long wait at the security check, I arrived at the airport well […]<\/p>\n","protected":false},"author":3098,"featured_media":90,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"_s2mail":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-89","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-datascienceintheindustry"],"_links":{"self":[{"href":"https:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/wp-json\/wp\/v2\/posts\/89","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/wp-json\/wp\/v2\/users\/3098"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/wp-json\/wp\/v2\/comments?post=89"}],"version-history":[{"count":0,"href":"https:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/wp-json\/wp\/v2\/posts\/89\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/wp-json\/wp\/v2\/media\/90"}],"wp:attachment":[{"href":"https:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/wp-json\/wp\/v2\/media?parent=89"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/wp-json\/wp\/v2\/categories?post=89"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.miamioh.edu\/the-center-for-analytics-and-data-science\/wp-json\/wp\/v2\/tags?post=89"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}