Behaviour pattern

What the EmployeePattern is

The EmployeePattern is the behaviour profile that CheckBiz360 builds for each employee automatically and continuously. It is not a one-off report or a monthly summary; it is a cumulative model that captures how the employee works day after day and makes it possible to identify trends that an isolated analysis would not reveal.

Where a traditional report tells you that an employee was late four times in March, the EmployeePattern tells you whether those four late arrivals are an exception in an impeccable history or part of a trend that has been worsening for months. That difference in perspective is what turns raw data into useful intelligence.

How the pattern is built

The system automatically processes the data that already exists on the platform. It requires no additional configuration; it activates from the moment the organisation has employees with attendance records and assigned schedules.

The data sources feeding the pattern are as follows:

Attendance records. Every entry and exit record contributes information on punctuality, real workday length and effective presence. The system accumulates this data and calculates averages, deviations and trends.

Planned schedules. The pattern does not analyse behaviour in the abstract, but always in relation to what was planned. An 18:00 exit is different depending on whether the shift ended at 18:00 or at 17:00.

Tasks and ratings. Completed tasks and the ratings assigned by the manager complement the presence analysis. An employee with perfect attendance but low productivity on tasks generates a different profile from an employee who is rarely absent and handles their responsibilities well.

Accumulated time. The pattern needs enough data to be representative. During an employee's first few weeks of work, the indices should be interpreted with caution. From several months of history onwards, the pattern reflects real behaviour more accurately.

Why the pattern is more valuable than a one-off report

A one-off report captures the state at a given moment. The EmployeePattern captures the direction in which that state is evolving. That difference is critical for people management.

An employee may have one good month in isolation after a conversation with their manager, but if their accumulated pattern shows a sustained negative trend, the good month's figure should not create a false sense of the problem being solved. Likewise, an employee going through a bad quarter for external reasons but with a solid history deserves a different assessment from someone with a chronically irregular profile.

Examples of patterns

Positive patterns

A positive pattern is characterised by consistency and stability. The employee habitually arrives within the punctuality margin, completes their workdays with few deviations, does not accumulate unjustified absences and their task ratings are regularly good. This profile generates high reliability and efficiency indicators and is the one the operational assessment flags as a candidate for promotion.

Another relevant positive pattern is progressive improvement: an employee whose indices were moderate six months ago but show a clear improving trend. This profile indicates that the management actions are working and that the employee has capacity to develop.

Negative patterns

A negative pattern is not defined by an isolated incident, but by repetition. Late arrivals concentrated on certain days of the week, frequent early exits, recurring absences with no formal justification or a deteriorating trend in the indices over the months.

The hardest pattern to detect without a system is slow deterioration: an employee accumulating small deviations week by week, none of them striking enough on its own, but which together represent a significant drift.

How it is displayed in the back office

The EmployeePattern is presented on each employee's record within the operational intelligence module. Managers with access to the module can consult:

• The calculated indicators —reliability, operational efficiency, cost and pattern confidence— with their evolution over time in a chart.
• The behaviour history with the most relevant events.
• The current state of the anomaly flag if it is active.