To gather meaningful engagement data, try these uncommon tactics

Your annual survey of the entire workforce is probably giving you dated, generic information. Frequent, individualized questions can provide insights that will inspire better performance.

Engagement survey considerations

Engagement has various meanings; in analytics, it tends to denote data from an annual survey.

Engagement surveys were once a boon to HR; now they seem passé. The idea that we’ll do a huge annual project, spend months analyzing the data, and take action a year or more after whatever was driving the scores seems anachronistic.

Perhaps it’s a good time to consider the different ways we could approach engagement data:

  • Frequent data collection. Pulse surveys—short, frequent surveys—are a step in the right direction. Perhaps we should think of these as the core means of gathering data and driving change, rather than as an optional add-on to the annual process. If pulse surveys are effective, do we need an annual survey?
  • Individualized data. We tend to report engagement in aggregates (e.g., engagement in department X), but fundamentally it’s a metric about individuals. Personalized surveys pointed to specific needs—rather than generalized surveys that ask everyone the same questions—could spur more-targeted action. Attuned.ai, for example, asks questions geared to individual motives. If the goal is to improve individual performance, then engagement data should be about individuals. That will require significant changes to how we gather and use engagement data, though, because it will no longer be anonymous.
  • Looking for data sources other than surveys. If we ask, “Why are we gathering engagement data?” we’ll free ourselves from a narrow focus on surveys. To reduce turnover or improve discretionary effort, we can look for signals in absenteeism and lateness. A more high-tech approach is to experiment with sentiment analysis on company emails to monitor mood changes. We might end up moving away from old definitions of engagement to a suite of measures that help us improve performance.
  • Tightening the link to action. There is no point in gathering data unless we understand how it can drive action. We first must articulate how various results (e.g., numbers above or below a stated threshold) will lead to a set of actions.

David Creelman is an author and CEO of Creelman Research. A version of this post first appeared on TLNT.

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