{"id":522,"date":"2021-04-12T22:02:53","date_gmt":"2021-04-13T02:02:53","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-peopleanalytics\/submission\/nestle-people-analytics-and-gender-equity\/"},"modified":"2021-04-12T22:02:53","modified_gmt":"2021-04-13T02:02:53","slug":"nestle-people-analytics-and-gender-equity","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-peopleanalytics\/submission\/nestle-people-analytics-and-gender-equity\/","title":{"rendered":"Nestl\u00e9: People Analytics and Gender Equity"},"content":{"rendered":"

The article \u201cHow Nestl\u00e9 uses People Analytics to Measure Gender Pay Gap and Equity\u201d explains the company\u2019s effort to leverage data and analytics to measure gender pay gap and equity. The company initiated the project after the CEO made statements at the United Nations and the International Labor Organizations that they are taking diversity and inclusion really seriously. The team led by Jordan Pettman, Global Head of People Analytics at Nestl\u00e9, has developed a model using R to understand pay and made it accessible to everyone by building a front end that enables someone that isn\u2019t familiar with analytics. Pettman is very confident about the approach and thinks that \u201cit’s a really powerful demonstration of the fact that approaching these problems in an analytical way enables non-analytics people to really have genuine impact, both on the business, given that this is a real business initiative, but on people\u201d.<\/p>\n

In my opinion, this is a great initiative for several reasons.<\/p>\n

    \n
  1. Visualize the gender inequality issue<\/strong><\/li>\n<\/ol>\n

    One of the biggest issues in solving gender inequality at workplace is people\u2019s ignorance or push back saying that there is no such inequality. Even when many women are saying that they are not treated equally, some people just don\u2019t listen or even say that it is women\u2019s fault because women are not working as hard as men. The beauty of having data here is that data can support the argument that women are not treated equally. With data, the argument becomes a \u201cfact\u201d.<\/p>\n

      \n
    1. Enables companies to think about what to measure<\/strong><\/li>\n<\/ol>\n

      Having people analytics in this space is also effective in forcing companies to think about how they should measure their progress in terms of gender equality. It is so prevalent in many companies that they only say what they have done (e.g., unconscious bias trainings) but do not track the specific metric they are trying to improve on.<\/p>\n

        \n
      1. Clarifies the goal <\/strong><\/li>\n<\/ol>\n

        When companies have to think about the metrics, it also forces them to clarify their goal in terms of gender equality. Are we trying to increase the number of female managers? Or are we trying to achieve equal pay? Being very specific on the goal is key to make a difference.<\/p>\n

          \n
        1. Keep people accountable<\/strong><\/li>\n<\/ol>\n

          When there is a clear goal and clear metrics, it makes people accountable. Many companies have been talking about gender equality for such a long time but haven\u2019t made much progress because no one is seriously responsible for it. These metrics should not be just for HR but for senior executives and managers across businesses.<\/p>\n

          Any considerations?<\/strong><\/p>\n

          YES. There are many considerations we have to be aware of when using analytics to achieve gender equality. Firstly, data itself can be biased. For example, when we use evaluation data, the evaluation data itself can be biased because of the informal process or unconscious biases etc. We need to be very careful about these embedded biases. Secondly, if the data are biased, building a model out of such data will further accelerate the biases. Having a biased model is dangerous as it may encourage some of the behaviors companies are trying to get rid of. Third, before conducting any of these analytical activities, it is critical that senior management, not just CHRO but CEO, must be 100% supportive of the initiative. Otherwise, the analysis would be run just for the sake of analysis and the implication would never be implemented to have an actual impact.<\/p>\n","protected":false},"excerpt":{"rendered":"

          Nestl\u00e9 has started an interesting and powerful analytic approach to achieve gender equity.<\/p>\n","protected":false},"author":18523,"featured_media":526,"comment_status":"open","ping_status":"closed","template":"","categories":[],"class_list":["post-522","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-peopleanalytics\/assignment\/lpa-2021-blog-assignment\/","yoast_head":"\nNestl\u00e9: People Analytics and Gender Equity - Leading with People Analytics<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-peopleanalytics\/submission\/nestle-people-analytics-and-gender-equity\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Nestl\u00e9: People Analytics and Gender Equity - 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