{"id":235,"date":"2020-04-13T17:05:06","date_gmt":"2020-04-13T21:05:06","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-peopleanalytics\/submission\/people-analytics-a-la-francaise\/"},"modified":"2020-04-14T23:12:14","modified_gmt":"2020-04-15T03:12:14","slug":"people-analytics-a-la-francaise","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-peopleanalytics\/submission\/people-analytics-a-la-francaise\/","title":{"rendered":"People Analytics \u00e0 la Fran\u00e7aise"},"content":{"rendered":"

In a few of our class sessions this semester, we have asked whether and how people analytics differs across cultural contexts. I have found these questions interesting, so I thought I would dig into some examples from France<\/strong>. I would like to share what I learned from the following article published in the French magazine L\u2019Expansion[1]<\/strong><\/a><\/em> in October 2016.<\/p>\n

 <\/p>\n

St\u00e9phanie Benz, \u201cTiens, un algorithme a remplac\u00e9 le DRH \u2026\u201d<\/a> (Look, an algorithm has replaced the HR department \u2026<\/em>), L\u2019Expansion<\/em>, October 2016, accessed April 2020.<\/strong><\/p>\n

For a rough English translation, open this page in Google Chrome<\/a> and then ask Chrome to translate it for you<\/a>.<\/p>\n

 <\/p>\n

Here are the two examples from the article that jumped out the most to me.<\/p>\n

 <\/p>\n

AssessFirst: Helping companies recruit personalities, not r\u00e9sum\u00e9s<\/strong><\/p>\n

This Paris-based startup (English website<\/a>) is at the forefront of \u201cpredictive recruiting\u201d (think back to our GROW case in Japan), which reporter St\u00e9phanie Benz deemed \u201cthe latest fashion\u201d in people analytics. Using its database of 15 years of personality tests, AssessFirst helps companies decide whom to hire with an algorithm that predicts which candidates will succeed in a given job posting.<\/p>\n

Benz gives a striking example: one of AssessFirst\u2019s clients, a tool distributor, used the algorithm\u2019s recommendation to hire a florist! She became one of the client\u2019s most successful employees.<\/p>\n

Would a human recruiter for that job, unassisted by AssessFirst\u2019s algorithm, ever seriously consider a candidate whose r\u00e9sum\u00e9 showed experience as a florist? <\/em>Not likely, unless the candidate had a personal referral from a friend.<\/p>\n

 <\/p>\n

Clustree: Tracing the career path that you didn\u2019t know was possible<\/strong><\/p>\n

When founder B\u00e9n\u00e9dicte de Raph\u00e9lis Soissan<\/a> wanted to change careers, she pored over hundreds of r\u00e9sum\u00e9s that looked like hers, trying to figure out what her options might be. She then created a company to make such investigations easier for others. Clustree (English website<\/a>), which at the time of publication had a database of 250 million \u201cprofessional itineraries,\u201d[2]<\/a> uses that database to broaden the range of possibilities for professionals.<\/p>\n

In addition to individuals\u2019 job searches, Clustree has another use case\u2014companies\u2019 internal promotion processes\u2014and de Raph\u00e9lis Soissan has a compelling example to share. A bank using her software ended up offering a Digital Advisor role to one of its HR employees, since Clustree showed that this employee could adapt to this very different job with just a bit of training.<\/p>\n

This example raises basically the same question that the AssessFirst case did:<\/p>\n

How many companies would transfer an HR employee to a role emphasizing digital skills without the benefit of people analytics?<\/em> And my answer is the same: not many, unless the employee used internal networking to get consideration for the job opening.<\/p>\n

Clustree was acquired in January 2020<\/a> by California-based Cornerstone OnDemand<\/a> (a $600 million company), an indication that de Raph\u00e9lis Soissan is onto something.<\/p>\n

 <\/p>\n

My take: Let\u2019s use people analytics to expand<\/em> possibilities<\/strong><\/p>\n

Both of these examples inspire me because we see people analytics (PA) being used to create opportunities for people that probably would not have existed without PA. It\u2019s easy for me as an individual, and future hiring manager, to get behind these use cases. What makes me less comfortable is the thought of PA being used to close off opportunities. And I am probably not the only person who feels discomfort at the latter type of use for PA.<\/p>\n

The modern form of PA is still in its early stages, and for that reason I believe that we as managers should be biased towards using PA to create choices<\/em> for people.<\/p>\n

Does that remind you of anything from RC year?<\/p>\n

\"\"<\/p>\n

Source: \u201cDesign Thinking Defined,\u201d IDEO, https:\/\/designthinking.ideo.com<\/a>, accessed April 2020.<\/p>\n

As we discussed in RC TOM when we did the IDEO case, at the beginning of a venture it\u2019s good to use divergent thinking<\/em> to create choices. Then, later, we can use convergent<\/em> thinking to make choices.<\/p>\n

I would argue that the field of PA is so young that it\u2019s like a new venture on a global scale, so companies should focus as much as they can on using PA to increase divergent, rather than convergent, thinking.<\/p>\n

(Of course, one good counterexample to my argument is the use of PA to screen r\u00e9sum\u00e9s. I would argue that this use case isn\u2019t actually constraining choices that much for many companies; for example, algorithms may filter out r\u00e9sum\u00e9s that recruiters would never have had time actually to read anyway.)<\/p>\n

 <\/p>\n

A cultural coda<\/strong><\/p>\n

I\u2019ll end where I started, with my interest in France. Benz\u2019s article uses the English phrase \u201cpeople analytics\u201d and dubs it \u201can untranslatable expression.\u201d<\/p>\n

In 2016, when she wrote the article, Benz observed that the use of PA was even more nascent in France than in English-speaking countries. She quoted Deloitte partner Philippe Burger<\/a>; according to Burger, French companies were lagging in their adoption of PA tools. One reason is that social partners in France are concerned about the use of data\u2014more concerned than they are in the United States. (See this Wikipedia article<\/a> for an explanation of the term \u201csocial partners,\u201d which we do not typically use in American contexts.)<\/p>\n

That makes me think that the cultural context for PA will be important when we get to our module on Privacy, Control, and the Future of Work. Many people consider Europe to be a global leader in data privacy, so as the field of PA develops in the coming years, I will be interested to track whether its applications in Europe are substantially different from those elsewhere.<\/p>\n

Merci pour votre int\u00e9r\u00eat et merci d\u2019avoir lu jusqu\u2019\u00e0 la fin ! (translation<\/a>)<\/p>\n

 <\/p>\n

Endnotes<\/strong><\/p>\n

[1]<\/a> L\u2019Expansion <\/em>folded in 2017, but it belonged to the Groupe L\u2019Express, which still exists: https:\/\/lexpansion.lexpress.fr<\/a>.<\/p>\n

[2]<\/a> The less literal translation \u201ccareer paths\u201d might be more natural in English, but I like the phrase \u201cprofessional itineraries\u201d because it makes us think of Google Maps. You might say that Clustree provides Google Maps for your career!<\/p>\n

Photo of a Parisian bridge by\u00a0L\u00e9onard Cotte<\/a>\u00a0on\u00a0Unsplash<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

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