Gathering and analyzing collaboration data helps companies guide employees on best behaviors, and more.
Video meetings are business as usual these days, but not all companies are reaping full value from this mode of collaborative work. Many fail to take advantage of what video meetings can tell them about how employees behave throughout the day, and therefore are missing out on the opportunity for data-driven decision making.
Collaboration data is one of the data types that most companies have at their disposal for gaining insight into employee experience. In analyzing collaboration data, team leaders, IT, HR, and other business managers can gain an overview of how often, in what ways, and with whom employees are digitally interacting throughout the day via applications such as team chat and video meetings. Optionally, employees see their own collaboration data for an individualized view on usage and positive and negative behavioral patterns.
Of the 500 companies that participated in Metrigy’s global Employee Experience: 2023-24 research study, 53% are using collaboration data. This is the second most-used type of data, behind engagement data, which 61.3% of companies use. Engagement data gathered from enterprise social networking and elsewhere shows how much an employee participates and engages digitally with the company and peers. The two types of data, along with employee sentiment—in use by 51.7% of companies—help form a well-rounded view of employee experience.
But understanding employee behavior is just the first step. Additional value comes for companies that use the data to guide their employees toward positive improvements in factors such as productivity and wellness that affect their overall experience. Team leaders or HR executives might evaluate the collaborative behavior of the best-performing teams against the collaborative behavior of under-performing teams, for example.
Companies already using collaboration data can analyze the data from video meetings to understand meeting behavior, based on factors such as number of participants, frequency, and duration. Analyzing the data can tell them:
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