Part of the ARBI ecosystem
ARBI.
Insights · decision topics

What business issues need attention?

Insights surfaces the business topics that require a decision. Want to explore how things connect instead? Go to Explore →

The ARBI decision chain
Reality→Insight→Business Risk→Decision→Scenario→Outcome

Every ARBI intelligence object follows a structured chain from workforce reality to business outcome. Reality is measured. Insights explain. Risks quantify exposure. Decisions define action. Scenarios model alternatives. Outcomes estimate business value creation or protection.

logistics
Last-Mile Revenue Risk
$42M at risk · High
Open workspace
mining
Production Growth Risk
$55M at risk · High
Open workspace
energy
Asset Reliability Risk
$48M at risk · High
Open workspace
manufacturing
Factory Productivity Risk
$38M at risk · Elevated
Open workspace
Ask the Executive CopilotRetrieve across the intelligence memory — answers cite sources, confidence and reasoning.
Underlying object model

Realities

— The certified, current state of the workforce — the ground everything else stands on.
Reality
Driver Attrition

Last-mile driver attrition is running well above plan and accelerating, draining capacity from the network faster than hiring can replace it.

21.4%
annualized voluntary attrition
source · mart_movement (SDF-2)

Insights

— A causal interpretation — what is driving what, and how confident we are.
Insight
Schedule Instability Drives Attrition

Week-to-week shift volatility is the dominant, controllable driver of driver attrition — ahead of pay. Drivers with unstable schedules leave at roughly twice the rate of those with stable ones.

Schedule volatility → fatigue & income unpredictability → disengagement → exit
confidence · high

Business Risks

— The business value at risk if the reality holds.
Business Risk
Revenue Exposure

If driver attrition holds at the current trajectory, unmet delivery capacity puts a material share of regional last-mile revenue at risk over the next four quarters.

$42.0M
revenue at risk (4 quarters)
Capacity shortfall × contribution margin on at-risk delivery volume
horizon · 4 quarters

Decisions

— A concrete, costed choice the intelligence supports.
Decision
Workforce Optimization

Stabilize driver schedules and rebalance routes to cut controllable attrition before adding headcount — protecting capacity at a fraction of the hiring cost.

  • Stabilize schedules (fixed shift patterns + 2-week visibility)
  • Raise pay across the board
  • Hire ahead of attrition

Scenarios

— A modeled future — assumptions run forward over reality.
Scenario
Human + AI Logistics

An AI scheduling agent proposes stable, fatigue-aware rosters; human dispatchers approve and handle exceptions. Modeled forward over certified reality to project the attrition and capacity effect.

Schedule stability uplift: +35%AI roster adoption: 70% of depotsAttrition elasticity: -1.3
Controllable attrition down ~8.5 pts; capacity restored to plan within 3 quarters.

Outcomes

— The business value created or protected.
Outcome
Revenue Protected

Under the Human + AI Logistics scenario, schedule stabilization protects the majority of at-risk last-mile revenue and avoids the cost of over-hiring.

$28.0M
revenue protected
Schedule stability→Attrition avoided→Capacity restored→Revenue protected
projected · next 4 quarters