HR & People
Absence and shift pattern analysis
Analyse absence, lateness, shift swap, and overtime patterns by team and location to identify where rota design, management practice, or workload is driving avoidable absence.
10–20%
reduction in unplanned absence cost
Opportunity assessment
Minor improvement. Small efficiency gain with limited effect on overall turnover or bottom line.
Relatively straightforward. Off-the-shelf tools handle the core task. Implementation is well-understood with good examples to follow.
Moderate data needs. Works with data most businesses hold, but will likely need consolidation, cleaning, or reformatting before use.
High risk. Significant external exposure or regulatory implications. Requires robust oversight and clear accountability.
Moderate people impact. Part of someone's working day changes. Requires training and some adjustment time, but roles remain broadly the same.
Tooling required
Things to consider
Analyse at team and pattern level, not individual level. Individual absence prediction is intrusive, likely to involve health data, and pushes into territory that is hard to defend to employees or a tribunal.
Absence is very often a symptom of rota design or management quality rather than individual behaviour. Framing the output as a management diagnostic keeps it useful and defensible.
Absence data frequently reveals disability-related absence, which is special category data with specific protections. Aggregate and anonymise before analysis and involve HR in the design.
Experiment starter: Analyse a year of absence by team, day of week, shift pattern, and manager. Take the three teams with the largest unexplained variance and investigate on the ground before drawing any conclusion.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — Risk and GovernanceThis opportunity scores low on risk exposure — read the risk and governance approach before you start.More in HR & People
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