Methods for identifying patterns, trends, and causes in people practice data

Covering Assessment Criterion 2.1 from 5CO02 Evidence-based Practice, this video focuses on the analytical methods people professionals use to move beyond surface-level description of data and towards substantive interpretation. The video addresses trend analysis, comparative analysis, and cross-tabulation as distinct techniques for interrogating both quantitative and qualitative people practice data. Alongside these, the video examines the relationship between correlation and causation, and introduces root cause analysis as a way of identifying what is genuinely driving observed patterns rather than simply noting that they exist.

Within the discussion of trend analysis, the video covers the use of moving averages — including three-month and six-month calculations — as a way of distinguishing genuine directional change from normal short-term variation, and it differentiates between linear and cyclical trends. Comparative analysis is explored through both internal comparisons across departments, locations, and time periods, and external benchmarking against sector norms, with attention to the methodological caution that organisations define and measure metrics differently. Cross-tabulation is illustrated through an engagement data scenario in which aggregate figures remain stable while disaggregated results by tenure reveal a notably different picture, demonstrating how headline figures can obscure significant underlying patterns.

On causation and root cause analysis, the video covers the conditions that should be considered before treating a statistical relationship as causal, including temporal sequence, logical coherence, and triangulation across multiple data sources. Two structured root cause analysis tools are named and discussed: the five whys technique, applied to a turnover scenario that traces repeated questioning from symptom through to an underlying organisational factor, and the fishbone diagram, which organises potential causes across categories such as people, processes, and policies. These methods are framed throughout in relation to the kinds of people practice evidence referenced in the AC 2.1 indicative content, including absence data, engagement scores, performance ratings, and turnover figures.