{"id":655,"date":"2022-04-17T17:21:52","date_gmt":"2022-04-17T21:21:52","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-peopleanalytics\/?post_type=hck-submission&p=655"},"modified":"2022-04-17T17:21:52","modified_gmt":"2022-04-17T21:21:52","slug":"trust-issues-obstacles-to-using-people-analytics-for-dei-efforts","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-peopleanalytics\/submission\/trust-issues-obstacles-to-using-people-analytics-for-dei-efforts\/","title":{"rendered":"Trust Issues: Obstacles to Using People Analytics for DEI Efforts"},"content":{"rendered":"\n\n\n

Algorithms and analytics are often portrayed as inherently objective and neutral, but there are\u00a0several examples<\/a>\u00a0of discrimination manifesting in technical models through biased data and development. It is therefore important to always be wary of unintended bias when leveraging analytics. However, this weariness should not prevent progress; rather, industry leaders and data scientists can utilize analytics to understand and solve the issue. A recent Knowledge at Wharton blog post, entitled\u00a0How Data Analytics Can Help Advance DEI<\/a>, explores how people analytics can work to improve diversity, equity, and inclusion (DEI) efforts in the workplace. The article highlights different obstacles to using data analytics for DEI purposes, including resistance from company leadership and data collection. Yet, there is one word that doesn\u2019t appear in the article that is essential to these efforts: trust. This five-letter word, which has operated in the background of this entire course, is crucial to unlocking the power of people analytics in DEI initiatives and must be present at different stages.<\/p>\n\n\n\n

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Trust in Data Collection<\/h2>\n\n\n\n

Today, corporations can take advantage of passive data about their teams and employees, as well as solicit active data from surveys and employee submissions. In either case, companies must consider the how trust impacts their ability to collect the information they need. When implementing surveys, for example, companies need to engender trust with their employees to ensure that people feel comfortable providing honest responses. This is especially true when seeking data for DEI purposes as those survey questions may ask individuals to share personal information that can be viewed as intrusive. When deciding how to leverage more passive data like employee emails and calendars, corporations must also decide what to share about the analytics they conduct using employee data. Because data scientists need robust and accurate datasets to draw quality conclusions from the analysis, companies planning to utilize data analytics in furtherance of DEI goals must take time to build trust amongst employees, particularly marginalized and minority populations.<\/p>\n\n\n\n

Trust in Implementation<\/h2>\n\n\n\n

Beyond collecting data and employee information, companies must also consider how to build trust once they have results from the analysis. In the first instance, the data scientists responsible must be able to convey the results to leadership in a way that allows everyone to trust the findings and takeaways. This is essential to the process, particularly as the models used become increasingly complex and much more \u201cblack box\u201d in nature. Without trust in the results, companies may hesitate to implement vital DEI initiatives due to lack of buy-in. In the second instance, in addition to being able to trust the output, employees need to believe that company leadership will act upon the data they collect and analyze. When a corporation releases a survey seeking to gather data for DEI efforts, employees that complete the survey will likely expect management to take certain actions afterwards. Thus, analysts and research should communicate to employees what actions they intend to take (and perhaps paths they choose not to pursue) in the aftermath of DEI data analytics and why.<\/p>\n\n\n\n

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Ultimately, as the Knowledge at Wharton article demonstrates, people analytics can play a vital role in addressing issues of bias and inequity in the workplace. In order to do this, however, companies must invest in building trust among employees at various stages of the analytics process.\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"

How can people analytics play a vital role in DEI efforts? 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