{"id":50,"date":"2026-08-07T17:34:29","date_gmt":"2026-08-07T17:34:29","guid":{"rendered":"https:\/\/smallhrtools.com\/blog\/?p=50"},"modified":"2026-08-08T11:52:04","modified_gmt":"2026-08-08T11:52:04","slug":"bradford-factor-explained-trigger-points","status":"publish","type":"post","link":"https:\/\/smallhrtools.com\/blog\/bradford-factor-explained-trigger-points\/","title":{"rendered":"The Bradford Factor Explained: Formula, Trigger Points, and Fair Use"},"content":{"rendered":"\n

Short answer:<\/strong> the Bradford Factor scores absence as S\u00b2 \u00d7 D<\/strong> \u2014 the number of separate absence spells<\/em> squared, times total days<\/em> absent. Squaring the spells makes ten one-day absences score 1,000<\/strong> while a single ten-day illness scores just 10<\/strong>, deliberately flagging the frequent-short-absence pattern that disrupts teams most and correlates strongest with disengagement. Used with judgment and clear trigger bands, it’s a genuinely useful early-warning signal. Used as an automatic disciplinary tripwire, it’s a lawsuit and a morale problem. This post covers both halves.<\/p>\n\n\n\n

The formula, and why spells are squared<\/h2>\n\n\n\n
\n

Bradford Factor = S\u00b2 \u00d7 D<\/strong>
S = number of separate absence spells in the period (usually a rolling 52 weeks)
D = total days absent across those spells<\/p>\n<\/blockquote>\n\n\n\n

A “spell” is one continuous absence, whatever its length: out Monday\u2013Wednesday with flu is one spell, three days. The squaring is the whole point of the metric \u2014 it encodes the operational reality that frequency hurts more than duration<\/strong>. One planned two-week absence can be covered; ten unpredictable Mondays cannot. Cover is arranged eleven times, work is re-planned eleven times, and the team absorbs the uncertainty every week.<\/p>\n\n\n\n

Three employees, same total days, wildly different scores<\/h2>\n\n\n\n

All three missed 10 working days<\/strong> in the last 12 months:<\/p>\n\n\n\n

Employee<\/th>Pattern<\/th>S<\/th>D<\/th>Score<\/th><\/tr><\/thead>
Asha<\/td>One surgery, 10 consecutive days<\/td>1<\/td>10<\/td>10<\/strong><\/td><\/tr>
Ben<\/td>Two flu bouts, 5 days each<\/td>2<\/td>10<\/td>40<\/strong><\/td><\/tr>
Chirag<\/td>Ten separate single days, mostly Mondays<\/td>10<\/td>10<\/td>1,000<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Same absenteeism rate<\/em> \u2014 a plain rate calculation treats them identically (which is why you track both; the Absenteeism Rate Calculator<\/a> computes rate and Bradford Factor side by side). The Bradford lens says: Asha needs a get-well card and a phased return; Ben is unremarkable; Chirag’s pattern needs a conversation \u2014 this month, not at the annual review.<\/p>\n\n\n\n

Standard trigger bands<\/h2>\n\n\n\n

Most organisations that use the Bradford Factor adopt bands like these (calibrate to your own workforce before adopting):<\/p>\n\n\n\n

Score<\/th>Typical response<\/th><\/tr><\/thead>
0\u201349<\/td>No action \u2014 normal life happens<\/td><\/tr>
50\u2013199<\/td>Informal, supportive check-in: “I noticed a pattern \u2014 is everything OK?”<\/td><\/tr>
200\u2013399<\/td>Formal review meeting; attendance expectations documented<\/td><\/tr>
400\u2013499<\/td>Written warning territory; occupational health referral considered<\/td><\/tr>
500+<\/td>Final warning \/ disciplinary process<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Two calibration notes. First, run the numbers on your current workforce before<\/em> setting bands \u2014 in a customer-facing shift environment a 50 threshold might flag a third of your staff; in a small office it might flag no one for years. Second, use a rolling 52-week window<\/strong>, not the calendar year: a fixed January reset lets a December pattern vanish, and invites exactly the wrong kind of gaming.<\/p>\n\n\n\n

Where the Bradford Factor goes wrong<\/h2>\n\n\n\n

The metric has well-documented failure modes, and every one of them comes from removing human judgment:<\/p>\n\n\n\n