Optimization & Automation – ChordianAI

What We Optimize

Operational Optimization:

• Workforce scheduling and shift planning

• Vehicle routing and logistics

• Production scheduling

• Inventory levels across locations

• Warehouse layout and picking routes

Financial Optimization:

• Budget allocation across initiatives

• Cash management and working capital

• Investment portfolio composition

• Pricing optimization

• Revenue management and yield optimization

Strategic Optimization:

• Product portfolio mix

• Market and customer segment prioritization

• Channel and partnership strategy

• R&D project portfolio

• M&A target selection

Optimization Approaches

ChordianAI selects the right method for each problem.

Linear Programming:

For problems with linear relationships and constraints:

• Production planning

• Workforce allocation

• Transportation problems

• Financial portfolio optimization

Mixed-Integer Programming:

When decisions are discrete (yes/no, which option):

• Facility location

• Project selection

• Scheduling with fixed time slots

• Supply chain network design

Multi-Objective Optimization:

When optimizing for multiple goals:

• Cost vs quality vs speed trade-offs

• Risk vs return

• Customer satisfaction vs resource utilization

Real-World Applications

Workforce Optimization:

Challenge: Schedule 500 employees across 24/7 operations considering skills, labor laws, preferences, vacation, and cost constraints.

Solution: Optimize schedules to minimize labor cost while meeting coverage, reducing overtime by 30%.

Supply Chain Optimization:

Challenge: Optimize inventory across 100 locations with varying demand, lead times, and transportation costs.

Solution: Minimize total supply chain cost while reducing inventory carrying costs 25% and improving service levels 15%.

Pricing Optimization:

Challenge: Optimize prices for 10,000 SKUs considering elasticity, competition, costs, and inventory levels.

Solution: Dynamic pricing adjusted daily, typical revenue increase of 8-12%.

Intelligent Automation

Automation that understands context and makes decisions.

Process Automation:

• Robotic Process Automation (RPA) for repetitive tasks

• Business Process Management (BPM) for complex workflows

• Integration Platform as a Service (iPaaS) for system orchestration

Decision Automation:

• Rule-based for deterministic logic

• Machine learning for pattern-based decisions

• Optimization for complex trade-off decisions

Optimization at Scale

Handle enterprise complexity.

Large-Scale Problems:

• Millions of variables and constraints

• Real-time or near-real-time solutions required

• Distributed optimization across locations

Results:

Organizations using ChordianAI Optimization achieve:

• 15-30% cost reduction in optimized areas

• 20-40% improvement in resource utilization

• 10-25% revenue increase from better decisions

• ROI typically 5-15x in first year