Identifying Patterns and Interpreting Data

Covering Assessment Criterion 1.4 of 3CO02 Principles of Analytics, this video focuses on the interpretation stage of working with organisational data — the point at which raw figures and qualitative responses are transformed into findings that can inform real decisions. The video addresses both numerical and qualitative data sources, drawing on examples such as exit interviews, employee surveys, and focus groups to illustrate why different types of information demand different analytical approaches.

For qualitative data, the video examines thematic analysis as a structured method, walking through the process of coding text, grouping related codes, and arriving at defined themes. Illustrative examples drawn from employee feedback — including comments relating to career development and recognition — show how this method works in practice. On the quantitative side, the video covers pattern recognition techniques including trend analysis, correlation, distribution, and demographic variation, alongside practical tools such as frequency tables, cross-tabulation, and line graphs. The role of benchmarking and contextual factors — among them labour market conditions, historical performance, and organisational circumstances — is addressed in relation to interpreting what a given figure, such as a turnover rate, actually means in context.

The video also sets out several common pitfalls in data interpretation, including confusing correlation with causation, drawing conclusions from small samples, cherry-picking results, and overlooking context when a metric appears to shift. It closes by considering how multiple calculation types — percentages, averages, thematic findings, and benchmarks — work in combination when investigating a people issue such as high turnover, and what determines when each tool is appropriate.