Jeydoo Control Center

The Control Center is the core configuration module of Jeydoo Smart Plan AI. It enables administrators to define AI behaviour, planning priorities, and decision-making preferences used during employee shift scheduling.

Within this module, administrators can manage how the AI operates through a centralized settings interface. Each feature can be individually enabled or disabled, providing flexibility in configuring scheduling logic.

Administrators can also adjust feature weightings using sliders. These settings determine the relative importance of each function when the AI generates schedules, allowing the system to align with operational priorities and preferences.

Functions Available

Enable or disable individual features

Adjust feature weighting using sliders to influence AI scheduling decisions

The Control Center currently consists of the following features:

Work Time Monitor
Habit AI (Learning Mode)
Revenue Maximizer
Fairness Algorithm
Compliance Lock

1. Work Time Monitor

The Work Time Monitor is a Control Center feature that gives priority to employees with the lowest Work Time Account (AZK) balance when assigning shifts. This helps ensure that employees who still need to complete their working hours are scheduled first.

This feature is applicable only to employees with the Employment Type = Mini-Jobber, as only Mini-Jobbers maintain an AZK (Work Time Account) balance.

1.1 Purpose

The purpose of this feature is to:

Help Mini-Jobbers fulfil their required working hours.
Reduce unused or outstanding AZK balances.
Prevent excessive overtime and unnecessary payroll payouts.
Improve fairness and efficiency when assigning available shifts.

1.2 Business Logic

When Work Time Monitor is enabled, Smart Plan AI will:

Retrieve the current AZK account balance of all eligible Mini-Jobbers.
Compare the AZK balances of employees who are eligible for the shift.
Prioritize employees with the lowest AZK account balance during AI suitability scoring.

2. Habit AI (Learning Mode)

Habit AI is a Control Center feature that analyses historical employee working patterns and uses these patterns to support future shift scheduling.

The purpose of this feature is to help Smart Plan AI identify recurring work habits, such as an employee who commonly works on a specific day or time. These learned patterns can then be considered when generating future schedules.

Habit AI applies to all employment types.

2.1 Data Source

Habit AI reads time booking data directly from Jeydoo CMP, which serves as the single source of truth for time booking records and employee work patterns.

This includes historical time booking records that are synced from TBP, as well as manual additions, edits and corrections maintained by administrators in CMP.

2.2 Historical Pattern Definition

A historical pattern is identified when the processed time booking data shows a recurring or similar working pattern within a period of 6 months.

For example, if an employee regularly works on Tuesday mornings over the analysed period, Habit AI may identify this as a learned working pattern.

2.3 Business Logic

When Habit AI is enabled, Smart Plan AI will:

Analyse historical time booking data from CMP.
Identify recurring working patterns for each employee within the defined analysis period.
Use the identified patterns as part of the AI suitability scoring when generating future shift schedules.
Give preference to employees whose historical working patterns best match the shift being generated.

Open Question / Remark

Should administrators be able to approve or reject AI-discovered patterns before Smart Plan AI uses them in future scheduling?

This may help prevent temporary or exceptional working arrangements from being treated as long-term employee habits.

3. Revenue Maximizer

The Revenue Maximizer is a Control Center feature that helps maximise business performance by identifying top-performing sales employees and recommending their scheduling during periods of high customer traffic.

3.1 Purpose

The purpose of this feature is to:

Maximise sales opportunities during peak business hours.
Ensure experienced sales employees are scheduled when customer demand is highest.
Improve overall business performance through intelligent workforce planning.

3.2 Data Source

The Revenue Maximizer uses data from multiple sources:

Jeydoo CMP – Historical sales performance data
Magicline / AIDOO – Peak business hour data

3.3 Business Logic

When Revenue Maximizer is enabled, Smart Plan AI will:

Analyse historical sales performance from Jeydoo CMP.
Identify top-performing sales employees based on the defined evaluation logic.
Retrieve peak business hour information from Magicline or AIDOO.
Give preference to scheduling top-performing sales employees during identified peak business hours.

Open Question / Remark

The detailed calculation logic for determining a top-performing sales employee is yet to be finalised and discussed.

4. Fairness Algorithm

The Fairness Algorithm is a Control Center feature that promotes fair and balanced shift distribution among employees. Administrators can define what "fairness" means for their centers by configuring a set of predefined fairness scenarios, as well as providing additional free-text input to the AI.

Through these configurations, each center establishes its own set of fairness rules that guide how shifts and schedules are assigned to employees.

This feature applies to all employment types.

4.1 Purpose

The purpose of this feature is to:

Promote fair shift distribution among employees.
Reduce repetitive assignment of weekend or undesirable shifts.
Support company-specific scheduling policies.

4.2 Business Logic

When the Fairness Algorithm is enabled, Smart Plan AI will:

Read the fairness rules configured by the administrator.
Apply these rules during schedule generation.
Prioritise schedules that best satisfy the configured fairness criteria while balancing other active Control Center settings.

Open Question / Remark

As fairness varies between centers, the method of configuring fairness rules requires further discussion.