{"id":342,"date":"2020-04-13T22:59:27","date_gmt":"2020-04-14T02:59:27","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-peopleanalytics\/submission\/trust-and-the-machine\/"},"modified":"2020-04-15T18:57:34","modified_gmt":"2020-04-15T22:57:34","slug":"trusted-partners-or-the-machine","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-peopleanalytics\/submission\/trusted-partners-or-the-machine\/","title":{"rendered":"Trusted Partners or the Machine?"},"content":{"rendered":"

\u201cIt should be about trust, babe (Be about trust)\u201d – Ashanti & Ja-Rule<\/span><\/i><\/p>\n

 <\/p>\n

Introduction<\/i><\/p>\n

In our first class this semester, back in the halcyon days of our pre-quarantine innocence, Professor Polzer posed a question: Are employees trusted partners in a mission or cogs in a machine? Though we have discussed and debated, pondered and premised for almost a full semester now, these authors feel no less conflicted as to this central tension of people analytics than we did almost three months ago. Indeed, further reading has prompted even more questions: Are People Analytics fundamentally different to other big data disciplines (<\/span>People Are Not Cogs<\/span><\/i><\/a>)? How actionable are our insights (<\/span>People Analytics Must be User Friendly<\/span><\/i><\/a>)? And what is the role of trust in this space (<\/span>The Enemies of Trust<\/span><\/i><\/a>)? These authors would suggest several points to further these discussions:<\/span><\/p>\n

 <\/p>\n

Models are a simplification of reality, but that doesn\u2019t mean they don\u2019t have value.<\/span><\/i><\/p>\n

Initially, there seems to be a contradiction at the heart of our class discussions. We talk about complex human systems and employee-centricity, yet build simple (relatively) mechanistic models that treat employees as mere dependent variables, nodes, or data points. Yet, models are always abstractions of reality. It\u2019s impossible to capture everything–we either lack the data, the understanding, or the computational power. In weather forecasting, economic modelling, or even epidemiological studies, we always simplify reality.<\/span><\/p>\n

The value of models isn\u2019t that they are perfect representations of reality, it\u2019s that they help us understand underlying relationships and focus our attention on what is most important. But this abstraction requires us to adopt a healthy dose of humility in our work. Any system involving humans will be subject to human complexity. Feedback loops, unintended consequences, and difficult-to-quantify factors abound. In People Analytics, perhaps more so than in many other data-based fields, we must be cautious in how we draw conclusions or proscribe action.<\/span><\/p>\n

 <\/p>\n

The employee-employer relationship is two-sided–both parties must want to be trusted partners before such a relationship can emerge.<\/span><\/i><\/p>\n

Trust is a critical component of the relationships an organisation has with its employees. We want our employees to be trusted partners in a joint mission–certainly we do in modern knowledge work where we need employees\u2019 creativity and engagement to co-create value–but employees have to want the same before it can emerge.<\/span><\/p>\n

Currently, most organizations utilize people analytics to measure and address employee engagement, productivity, and other \u201cefficiency\u201d metrics. Though valuable, the evidence linking employee engagement and productivity to overall organizational performance is mixed, or at best, incomplete. But what is clear, is that employee trust is a strong leading indicator of organizational performance in a variety of sectors around the world. Measuring levels of employee trust can provide insights that help employers understand future retention patterns, productivity risks, and early warnings of issues festering beneath the radar.<\/span><\/p>\n

But trust is a complex creature. It\u2019s tougher to measure than simple employee engagement–employees may be outwardly engaged and productive, but internally disengaged due to a trust deficit. It\u2019s also a function of a wide variety of\u00a0 employer-employee interactions, built up through communications, impressions, transparency, recognition, and thousands of other small details.<\/span><\/p>\n

 <\/p>\n

Consequently, the need for organizations to develop better methods of measuring and understanding levels of internal trust has never been greater.<\/span><\/i><\/p>\n

Trust is traditionally measured through organizational surveys, but most employee engagement surveys do not ask the right questions to accurately determine levels of trust. Good questions on organizational trust seek to measure the competence, integrity, and reliability of an organization\u2019s stakeholders (e.g., direct managers or senior executives). But such surveys must be carefully constructed to elicit the right information from employees. Given that poor communication and fear of retribution are often the consequence of trust deficits within an organization, an appropriately designed organizational trust survey should provide respondents with anonymity. Data collected from survey questions like this can be further analyzed by employee tenure, location, compensation, age, gender, etc in order to increase the depth and variety of insights that can be gained.<\/span><\/p>\n

As people analytics continues to be an ever-present resource for organizations in accomplishing their performance goals, we hope that researchers and practitioners in the field increasingly prioritize the creation of actionable and quantifiable systems for measuring and improving organizational trust.\u00a0<\/span><\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

In our first class this semester, back in the halcyon days of our pre-quarantine innocence, Professor Polzer posed a question: Are employees trusted partners in a mission or cogs in a machine? 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