Understanding and interpreting raw data types in people practice

Covered in this video are the two primary data types that people practitioners encounter when working with evidence: quantitative data, represented by numerical metrics such as absence rates, time-to-hire figures, training completion percentages and turnover statistics, and qualitative data drawn from sources including exit interview transcripts, open-ended survey responses, focus group discussions and grievance records. The video addresses AC 2.1 of 5CO02 by focusing on what it means to interpret rather than merely gather these data types, with particular attention to the conditions under which a figure or a narrative account can be considered meaningful rather than misleading.

For quantitative analysis, the video covers reliability checks on data sources, the significance of response rates, and the importance of examining an appropriate time period before identifying trends. It also addresses statistical measures including the mean, median and standard deviation, and explains why each has a distinct role depending on the distribution of data and the presence of outliers — using salary data as a concrete illustration of when one measure may be more representative than another. The discussion of turnover figures introduces the question of contextual interpretation, including sector benchmarking and the relevance of which employee groups are leaving.

On the qualitative side, the video covers thematic analysis as a systematic method for identifying recurring patterns across narrative sources, and introduces the distinction between manifest content and latent content as a framework for reading beyond what respondents explicitly state. A concrete example involving how an employee describes a manager's availability is used to illustrate latent interpretation, and the relationship between qualitative findings and quantitative patterns — such as how return-to-work interview data might explain a measurable rise in absence — is examined as part of the broader interpretive process.