Unlocking EBITDA
Engineering-Led Cost Transformation for Portfolio Companies
Challenge ASI Solution Value
Key Challenges
  • Opaque cost structures for high value parts
  • Volatile input costs
  • Scattered data across teams
  • Limited visibility into drivers
Our Framework
  • Part-level costing using xcPEP
  • Supplier cost mapping via xcPROC
  • Should Costing of each and every part
  • Unified data layer for decision-making
Business Impact
  • EBITDA uplift
  • Faster time-to-insight
  • Improved exit multiples
  • Sustained competitive edge
Core Technology Platforms
xcPROC
Procurement Intelligence
xcPEP Costing Engine
Precise Should Costing
xcPEP Idea Module
Automated Design & Commercial Idea Generation
Build - Operate - Transfer Engagement Model
Phase 1: Build
Detailed Should-Costing Foundation
Phase 2: Operate
Idea Generation & Implementation
Phase 3: Transfer
Cost Engineering Function Handover
  • Data mapping from drawings and teardown
  • Teardown analysis of proprietary and competitor products
  • Alignment of cost models with company's reality
  • Development of raw material, LHR, MHR databases aligned to company’s products and supply chain
  • Supplier & route mapping
  • Should costing of everything the company makes and buys
  • Engineering idea generation: design / material / supplier / process / packaging changes
  • Engineering idea implementation
  • Commercial idea generation: negotiation gaps, alternate suppliers, import/export data
  • Commercial idea implementation
  • Cost Engineering Function is created inside the company
  • Full handover of platform and processes
  • Training, documentation, and continued support
Deliverables & Outcomes
Immediate
  • Baseline costing
  • Quick-win ideas
Medium-Term
  • Operational improvement
  • Margin expansion
Long-Term
  • Exit readiness
  • Value creation
Feature ASI Engineering Management Consultants
Core Offering Technology platforms (xcPEP & xcPROC) and engineering services Project-based strategic advice and high-level analysis
Methodology Engineering-led, data-driven should costing and design-to-value Financial analysis, industry benchmarks, and top-down strategy
Data Granularity Granular, part-level data grounded in real manufacturing logic (e.g., material grades, machine cycle times, tooling costs) High-level, aggregated industry data and benchmarks
Cost Model Transparent and defensible; based on a single source of truth for all inputs and calculations Often opaque; relies on proprietary models and aggregated data
Value Creation Focuses on building internal, sustainable capabilities within the portfolio company (Build-Operate-Transfer model) Delivers project-based findings and recommendations, often leading to ongoing dependency
Scalability Highly scalable, enabling continuous cost optimization across multiple products and teams through a single platform Typically project-specific, requiring new engagements for each new initiative
Auditability Full audit trail of every cost input, idea, and version of the cost model; downloadable reports for validation Findings are often high-level and difficult to audit at a granular, part-level
Goal To empower the client with a self-sufficient, data-driven cost engineering function To sell project engagements and provide strategic advisory services
Outcome Long-term, compounding cost savings and enhanced enterprise value through institutionalized capabilities Short-term gains from project-specific recommendations and strategy